Medical informatics lies at the intersection of computer SCIence and medicine, and understanding critical aspects of both fields provides for more proficient practitioners. Biomedical Informatics: An Introduction to Information Systems and Software in Medicine and Health supplies a cohesive narrative of the multidisciplinary concepts linking the field. This complete medical informatics textbook begins by revIewmg the IT aspects of informatics, including systems architecture, electronic health records, interoperability, privacy and security, cloud computing, mobile healthcare, imaging, data capture, and design issues. Next, the text provides case studies that demonstrate the roll out of electronic health records (ERRs) in hospitals. The third section incorporates four anatomy and physiology lectures that focus on the physiological basis behind data captured in ERRs. Examples include detailed descriptions of the heart and electrical systems, lungs and alveoli, and oxygen exchange. The book includes a primer on the theoretical concepts that underpin the science behind medical informatics, including an Anatomy & Physiology Essentials guide. It also contains a tutorial on application development to help students understand the tools for improving user interfaces for ERRs on mobile platforms. The author uses a student-friendly organizational structure that supplies students with a clear demarcation between essential and optional material. The text supplies clear delineation between Level I, the basic concepts every biomedical informatics professional needs to master; Level II, applied concepts and examples; and Level III, advanced topics. This format allows undergraduate and graduate instructors and professionals in the field to focus quickly on the essential topics, and if interested, delve into Level III advanced topics. The book includes links to documents and standards sources so students can explore each idea described in more detail. Instructor's manual, solutions

Biomedical Informatics: An Introduction to Information Systems and Software in Medicine and Health

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Biomedical
 
Informatics
 
An Introduction to
 
Information Systems and
 
Software in Medicine and Health

David J. Lubliner
 
New Jersey Institute of Technology, Newark, USA 
Illustration by Amy Cassandra Lubliner

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Taylor & Francis Group
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Preface......................................................................................................................vi i
 
Author .......................................................................................................................i x
 
Contributors .............................................................................................................
xi
 1 Introduction to Biomedical Informatics ...........................................................1
 2 Framework for Implementing the U.S. Medical Records Infrastructure ...... 27
 3 Electronic Health Records .............................................................................. 45
 4 Data Interoperability ........................................................................................81
 5 Security ........................................................................................................... 121

5 Security ........................................................................................................... 121
 6 Telehealth .......................................................................................................139
 7 Medical Sensors ..............................................................................................163
 8 Imaging .......................................................................................................... 223
 9 Ethics ..............................................................................................................251
 10 Critical Care Nursing Perspective on the Electronic Health Record .......... 269
 
Cathy Lubliner
 11 	 Healthcare Management Information Technology in the
Full Service Facility ....................................................................................... 309
 
Philomena Diquollo

 12 Future Directions for Biomedical Informatics ..............................................321
 
Appendix A: Application Development for Electronic Health
Records–Mobile Applications Development  ...................................................... 349
 
Daniel Nasello 
Appendix B: Mobile Applications Development ............................................... 367
 
Contents
 
v

vi Contents 
Appendix C : Cascading Style Sheets ................................................................... 381
 
Appendix D : JavaScript ........................................................................................ 393
 
Glossary.................................................................................................................. 401
 
Index ....................................................................................................................... 413

Preface
 
The inspiration for writing this textbook was fourfold: First, to create a cohesive narrative of the multi­
disciplinary concepts linking the Biomedical Informatics field; second, to introduce an improved  text­
book organizational structure so students will have a clear demarcation between essential and optional 
materials; third, to  provide a primer on the theoretical concepts that underpin the science in this field 
including an Anatomy & Physiology essentials guide; and lastly, to provide a tutorial on application 
development so students can understand the tools that can be applied to provide improved user inter­
faces for EHRs on mobile platforms. I believe that the current spate of textbooks could be improved. 
Most textbooks in either health, medical, or biomedical informatics are usually a compendium of dispa­
rate facts cobbled together from distinct concepts, albeit appropriate for this field, lacking the narrative 
and content that ties together concepts.

and content that ties together concepts. 
Most books in this field are written by 20–30 individual authors; although experts in their field, their 
narrow charge and scope limit the cohesive connection between concepts. This textbook attempts to 
build a cohesive narrative beginning with the forces and government mandates that facilitated this expo­
nential rise in the universal acceptance of the structure and standards that created this new discipline. 
Later, the science behind these technologies is explored, including a necessary basic primer on anatomy 
and physiology and in later chapters feedback from nursing experts and managers who have imple­
mented and used electronic health records. The last chapter attempts to define a series of parameters for 
predictive biomedical informatics so professionals can extrapolate forces that may expand or impede 
future desired advances. Technological forces are only one factor that leads to innovation; often financial,

future desired advances. Technological forces are only one factor that leads to innovation; often financial, 
governmental, and intangible public perceptions need to be factored into the equations for predictive 
analysis. Appendices A through D are a basic primer on writing applications for portable devices. These 
devices will play a more important role in healthcare delivery and monitoring in the future. 
The second motivation to writing this textbook was to create a structure that facilitated learning. 
Most books introduce concepts but are not easily structured for the reader or instructor. In a typical 
40-page chapter, how do you determine which concepts are essential facts, which are applied concepts, 
and which ideas fall into the advanced topic realm? The book attempts to create a clear delineation 
between Level I, basic concepts every biomedical informatics professional should master, Level II,

between Level I, basic concepts every biomedical informatics professional should master, Level II, 
applied concepts and examples, and Level III, advanced topics. Undergraduate and graduate instruc­
tors and professionals in the field can quickly focus on the essential topics but if interested can delve 
in Level III advanced topics. I appreciate feedback from the readers regarding unintentional errors or 
suggestions for enhancing future editions. 
The journey of writing this or any book is transformative. The authors believe they are experts in 
their fields, but then after, for example, reading 10,000 pages of the DICOM medical imaging standards 
Parts 1–20, their perceptions evolve and they begin to appreciate the complexities and in-depth interop­
erability that underlie these standards that they were not privy to before. It also leads readers to explore 
and hopefully extrapolate meaning that allows them to begin their own journey of exploration and

and hopefully extrapolate meaning that allows them to begin their own journey of exploration and 
learning. “When you reach that point in life where you realize how little you actually know, that’s the 
vii

viii Preface 
first step in your journey to learning.” This concept has been echoed from the teaching of the Buddha to 
the fictional character Don Juan by Tirso de Molina in 1630. There is always more to learn, and I hope 
this book motivates a few to continue this journey. I have tried to include links to all documents and 
standards sources so students can explore, in detail, each idea described in this book. 
The research process for the book took several years. It was challenging, or agonizing, depending on 
your perspective. The web provides virtually infinite resources, but extracting the wheat from the chaff 
is often difficult. Exploring tenuous linkages between concepts, falling deep into the rabbit hole and 
then trying to extract myself was a challenge. Where do you stop? You could write an entire book on 
MRIs or HL7 standards, but extracting the essential meaning of concepts so students can begin their

MRIs or HL7 standards, but extracting the essential meaning of concepts so students can begin their 
own exploration is difficult. The goal was to create a textbook that would provide a teacher or a student 
with clear, engaging, in-depth explanations and links to resources to explore concepts in more detail if 
desired. 
The book was written to be read in sequential order but allows students the ability to explore topics 
in detail. The structure of the book allows that mode of exploration. Level I of every chapter is recom­
mended. In addition, Chapter 10, “A Critical Care Nurse’s Perspective of EHRs,” should be read. How we 
use technology is as important as the technology itself. Enjoy the journey; this is an exciting, evolving 
field that will transform healthcare. 
David J. Lubliner, PhD 
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Author
 
David J. Lubliner is a member of the faculty at a northeastern university where he runs a medical infor­
matics program that he developed a decade earlier. He earned his PhD in information systems and has 
graduate degrees in biomedical engineering and computer science. He is currently part of a team devel­
oping a handheld medical scanner. Prior to teaching, he worked for 10 years at a Fortune 500 company 
as a divisional vice president of an architecture–computer security group and before that worked as an 
engineer on the Patriot missile system. 
Dr. Lubliner believes we are at the dawn of a new age of medicine, where instant access to data will 
change the current top-down model of healthcare to a more user-centric system. At the beginning of the 
twentieth century, technological advances doubled life spans, and we are poised to recreate that with the 
exponential growth of medical research and real-time access to information, creating a truly universal

exponential growth of medical research and real-time access to information, creating a truly universal 
medical principia of all human knowledge: “Live long and prosper.” 
ix

Contributors
 
Philomena M. DiQuollo is a working health-care IT professional who began her career in nursing and 
transitioned to IT&S 12 years later. Since 1985, she has been working in acute care facilities, implement­
ing clinical and business technology solutions as well as directing day-to-day operations and supporting 
strategic goals at a major urban teaching medical center in New Jersey. Currently, her position is sys­
tem director of analytics within a multifacility health-care system. Philomena DiQuollo is an adjunct 
faculty at New Jersey Institute of Technology, Newark, New Jersey, teaching in the medical informatics 
program. She received her BSN from Seton Hall University, South Orange, New Jersey and MA in nurs­
ing from New York University, New York, New York. In addition, she is a certified professional in health 
information management systems and is American Society for Quality Six Sigma Green Belt certified.

information management systems and is American Society for Quality Six Sigma Green Belt certified. 
She resides in New Jersey and is pursuing a master’s in analytics at Villanova University, Villanova, 
Pennsylvania. 
Cathy Lubliner is a critical care clinical nurse specialist at an academic teaching hospital. She has more 
than 30 years experience in the care of patients with end-stage heart failure, cardiogenic and septic 
shock, pre- and posttransplant procedures, and ventricular assist devices. During the implementation 
of the EHR, she served as one of the “super users” to facilitate the transition of the nursing staff to the 
computer-based documentation system. 
Daniel Nasello is an experienced mobile and web application developer and project manager, who cur­
rently resides in Nutley New Jersey. Having developed some highly successful applications (including 
multiple applications for various singers and actors) and having worked in multiple industries allow

multiple applications for various singers and actors) and having worked in multiple industries allow 
Daniel to bring the experience into the software he develops. Seeing the rapid growth of mobile applica­
tion development, Daniel has created groundbreaking and innovative applications that will be used in 
tomorrow’s market, and he is also developing mobile and web application opportunities in industries 
where they are nonexistent. Daniel currently holds a bachelor’s degree in computer technology a mas­
ter’s degree in information system from the New Jersey Institute of Technology, Newark, New Jersey. He 
is also a part-time instructor at NJIT, where he spearheaded the mobile application development class, 
which is rapidly growing in popularity. 
xi

Level I: Core Concepts .....................................................................................2
 
1.1 	 Introduction ..........................................................................................2
 
1.2 	 Nomenclature ........................................................................................2
 
1.3 	 Textbook Organization ........................................................................5
 
1.4 	 Biomedical Informat ics Challenges ...................................................6
 
1.5 	 Biomedical Informatics Curriculum.................................................7
 
AMIA Core Biomedical Competencies • National League for 
Nursing Informatics • Bachelor’s in Medical/Biomedical Informatics 
Curriculum
 
1.6 Chapter Summaries ............................................................................ 12
 
Glossary ...........................................................................................................24

1.A Appendix ...................................................................................................24
 
1 
Introduction to 
Biomedical Informatics 
1

2 Biomedical Informatics 
Level I: Core Concepts 
1.1 Introduction
 
Biomedical Informatics (BMI) lies at the intersection of information technology (IT) and healthcare/ 
medicine. Integrating complex data, linking medical professionals and patients, staying abreast of the 
lightning changes in both fields, and providing real-time secure data make this field simultaneously 
exciting and challenging. 
The BMI professionals are well versed in IT since they will be working with hospitals’ IT staffs and radiol­
ogists to ensure seamless integration of digital imaging and communications, working with structured data 
and protocols; integrating all forms of wired and wireless data, facilitating secure communication protocols, 
and interfacing with medical professionals and patients will require a broad knowledge of interrelated fields. 
Electronic health records (EHRs) may be the most visible of technologies the BMI  professional facilitates,

Electronic health records (EHRs) may be the most visible of technologies the BMI  professional facilitates, 
incredibly complex in their own right, integrating data from a myriad of sources both internal and external 
and providing expertise in developing user interfaces and facilitating data capture from medical sensors/ 
monitors. Working with medical staff, their role is to customize user interfaces, which requires a knowl­
edge of medical terminology and standards such as ICD10 and SNOMED and knowledge of best practices 
meaningful use regulations. They will be at the forefront of the transition to “medical records 2,” creating 
user-friendly and efficient interfaces via mobile devices tailored to the needs of individual professionals. 
A nurse should not be a data entry specialist, but EHR tools and interfaces should facilitate not hinder their 
profession, so a knowledge of application development and user interfaces is a critical core knowledge.

profession, so a knowledge of application development and user interfaces is a critical core knowledge. 
We are in the infancy of EHR technology, at the awkward stage of barely being able to walk and talk, 
and certainly not user-friendly, spitting up all over users. The baby was born with the help of HIPAA, 
the Stimulus Act, and the Affordable Care Act (ACA). BMI professionals have to guide and support the 
evolution of this infant to stage 2, toddler, walking, talking, and potty training them to be productive 
members of society. Buckle up, there will be all-night feeding sessions, changing dirty diapers, and 
ensuring the child becomes a productive member of society. 
1.2 Nomenclature 
There are a number of medical/biological/health/research informatics fields with sometimes overlapping 
nomenclatures: Defined as “a set or system of names or terms used in a particular science or art, by an indi­

vidual or community.” The intent of this section is to provide precise definitions needed by the Biomedical 
Informatics (BMI) professional. The second goal is to explain the evolution of the term “Biomedical” as a 
more inclusive term rather than the older designation of Medical Informatics. Lastly, a brief description of 
the many related informatics subfields are provided (Figure 1.1). 
This new definition adds two concepts that I believe should enhance the descriptions of the science 
of BMI, i.e. the terms meaning and intuitive user interfaces , essential in the evolution of the science. 
Meaning refers to correlating the growing flood of medical data into an overall systems holistic view 
rather than simply displaying individual data points. The analogy would be between information and

rather than simply displaying individual data points. The analogy would be between information and 
knowledge. The current EHR’s have not been tailored for the unique requirements of diverse health-
care providers and often hinder rather than facilitate care. There are a number of chapters in this text 
describing the nursing perspective and challenges of current EHR implementations and an additional 
appendices that describe developing EHR applications (apps) for mobile devices. 
Definition 
Informatics creates meaning out of chaos; Biomedical Informatics extrapolates meaning from diverse 
biological, medical, nursing, health, and clinical research sources and structures that data via intuitive 
interfaces to enhance healthcare and delivery (Lubliner 2015).

Nomenclature/
Fields 
Biomedical informatics
Medical informatics
Nursing informatics
Translational bioinformatics
Bioinformatics
Clinical research informatics
Biomedical engineering
Consumer health informatics
Health informatics 
Public health informatics 
Organization
(Textbook)
 
Chapter organization
(Diagrams)
 
Level I is comprised of core
topics that a Biomedical
Informaticist should master
 
Level II contains applied
concepts that support the
concepts in Level I
Level III advanced topics,
either for graduate courses or
by instructor prerogative 
Level IV Anatomy and
Physiology (A&P) primer
 
curricula
(Core competencies)
 
American Medical Informatics
Association (AMIA)
National League of Nurses
(NLN) Informatics Curriculum
Bachelors Program in Medical
Informatics in Northeastern
University
 
Chapter
summaries 
3 
FIGURE 1.1 Organization of topics covered in Chapter 1. 
Introduction to Biomedical Informatics

4 Biomedical Informatics 
Biomedical informatics syntax 
Before listing the current accepted nomenclatures for this field, which are sometimes confusing, an explana­
tion of the derivations of the terms will be introduced. The term medicine is derived from the Latin word 
medicina, meaning art of healing. Asclepius was the Greek god of medicine. A physician “practices medicine” 
through diagnosis, treatment, and prevention of disease. Physicians broadly are categorized as medical or sur­
gical. Medicine refers to the practice of  nonoperative medicine. The American Medical Association’s (AMA) 
mission is to “to promote the art and science of medicine and the betterment of public health.” 
Bio is the Greek word for life. It also is defined as “indicating or involving living organisms.” Originally, 
this informatics field was referred to as Medical Informatics, but since medical  refers to a subset of the

this informatics field was referred to as Medical Informatics, but since medical  refers to a subset of the 
health field, a more expansive term Biomedical Informatics was used. Other health professionals, nurses 
also use EHRs so “medical” alone would have been exclusionary. Nursing is defined by the American 
Nursing Association as “the protection, promotion, and optimization of health and abilities, prevention 
of illness and injury, alleviation of suffering through the diagnosis and treatment of human response, and 
advocacy in the care of individuals, families, communities, and populations.” In order not to have a dis­
cipline’s name with a hundred subfields, a compromise was reached that incorporates bio, life and living 
organisms, and medicine, which incorporates diagnosis, treatment, and prevention into BMI. 
Current informatics descriptors 
The following are widely accepted definitions of the various informatics fields related to medicine and 
healthcare.

healthcare. 
Informatics is “a field of study to apply information technology to another field—from healthcare to 
journalism to biology to economics” (Indiana University). 
Two additional BMI definitions: 
Biomedical Informatics  is “the interdisciplinary field that studies and pursues the effective uses of 
biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision mak­
ing, driven by efforts to improve human health” (AMIA Definition) ( http://jamia.bmj.com/content/ 
early/2012/06/07/amiajnl-2012–001053.full) (Table 1.1). 
Biomedical Informatics is “the core scientific discipline that supports applied research and practice in 
several  biomedical disciplines, including health informatics, which is composed of clinical informatics 
( including subfields such as medical, nursing, and dental informatics ) and public health informatics”

( including subfields such as medical, nursing, and dental informatics ) and public health informatics” 
(American Medical Informatics Association [AMIA]). 
Nursing Informatics is the “science and practice (that) integrates nursing and implementation of com­
munication and information technology” (AMIA). 
Translational Bioinformatics is the development of analytic methods to optimize the transformation 
of biomedical data and genomic data, into proactive, predictive, preventive, and participatory health. 
The field of Bioinformatics  has a research focus, analyzes datasets for genomics, proteins, etc. The 
branch of information science concerned with large databases of biochemical and pharmaceutical infor­
mation (world English dictionary) intersects with the field of computational biology. 
TABLE 1.1 Biomedical Informatics Association/Organization 
Name Link 
American Medical Informatics Associations www.AMIA.org

Name Link 
American Medical Informatics Associations www.AMIA.org 
American College of Medical Informatics http://www.amia.org/programs/acmi-fellowship 
Public Health Informatics http://www.amia.org/applications-informatics/ 
public-health-informatics 
International Medical Interpreters Association http://www.imiaweb.org/ 
American Nurses Association—Nursing Informatics http://www.nursecredentialing.org/InformaticsNursing 
Medical Informatics Association Medical Library Association http://www.medinfo.mlanet.org/ 
Association for Computing Machinery Human Computer www.acm.org 
Interfaces SIGCHI

5 Introduction to Biomedical Informatics 
Clinical Research Informatics is the discovery and management of new knowledge relating to health 
and disease. It includes management of information related to clinical trials. 
Biomedical Engineering  is defined as a field dealing with the application of engineering principles 
to medical practice. It also lies at the intersection of electrical engineering and the biological sciences. 
Medical Informatics (often used interchangeably with BMI but the term biomedical is currently the pre­
ferred term used by the leading informatics body in this field the AMIA) is “the science and art of model­
ing and recording real-world clinical concepts and events into computable data used to derive actionable 
information, based on expertise in medicine, information science, information technology, and the schol­
arly study of issues that impact upon the productive use of information systems by clinical personnel” 
(S. Silverstein, MD).

(S. Silverstein, MD). 
Consumer Health Informatics is the field “devoted to informatics from multiple consumer or patient views. 
These include patient-focused informatics, health literacy, and consumer education.” The focus is on infor­
mation structures and processes that empower consumers to manage their own health; for example, health 
information literacy, consumer-friendly language, personal health records, and Internet-based strategies and 
resources. The shift in this view of informatics analyzes consumers’ needs for easier to understand information. 
Health Informatics is “the interdisciplinary study of the design, development, adoption, and applica­
tion of IT-based innovations in healthcare services delivery, management, and planning.” 
1.3 Textbook Organization 
The textbook is structured for both BMI undergraduate and graduate courses. It is sequenced to intro­

duce topics that build on each other. Most chapters have three levels of complexity. Level I is comprised 
of core topics that a BMI professional should master. Level II contains applied concepts that support the 
concepts in Level I. Level III has advanced topics that should be included in graduate courses but can be 
used for undergraduates in selected topic area s. Chapter 7, Medical Sensors, includes a Level IV  section 
on Anatomy and Physiology (A&P) primer. All BMI students should have a basic A&P understanding, 
especially when working with physicians and nurses. Understanding the underlying medical concepts is 
the difference between a technologist and a professional. An BMI professional should aspire to the latter. 
This primer on BMI offers unique perspectives and core foundational materials not found in other text­

books in this field. In-depth examples of concepts introduced are linked to theoretical concepts with included 
real-world examples. In Chapter 3, Electronic Health Records, specific examples of EHRs are included. 
Medical nomenclatures, described in Chapter 4 Data Interoperability, specific HL7 and ICD10 coded mes­
sages and source tables are included so professions can understand the exact message structure exchanged 
between systems. In Chapter 10, a clinical nurse specialist and CERNER EHR expert discusses a current EHR 
implementation, its specific benefits and limitations, and specific recommendations  necessary to evolve into 
the next generation of user-friendly interfaces and improved process flow. In Chapter 7, Medical Sensors, an 
in-depth explanation of electro-chemistry provides students with an understanding of the chemistry, phys­

ics, and electrical foundations needed for capturing and analyzing medical sensor data. Finally, a primer on 
the coding of medical apps, Appendices A through D, introduce a skill set that is essential for the evolution of 
the next generation of medical records; user-friendly interfaces for mobile devices that reduce the IT burden 
to essential data tailored for individual’s medical environments. In 2015, once the core EHR systems are in 
place for most, not all. A significant group of medical professionals dentists, optometrist, mental healthcare 
professionals, and a few others are still in the process of implementing EHR’s implementation. The next 
phase, will be “EHR 2” enhancing the user interfaces for more user-friendly and efficient process flow. 
Three chapters have been written by experts in their field to provide complementary perspectives and

Three chapters have been written by experts in their field to provide complementary perspectives and 
expertise. Two are mastered, prepared nurses who are experts in EHRs from users’ and implementers’ 
points of view. The first is a clinical nurse specialist (MSN, CCRN) and CERNER super user. The second 
is an IT director who implemented a new EHR system in a large medical center. The third is an expert in 
application development for wireless devices. He has taught several courses at a university in application 
development and is pursuing a PhD in Information Systems specializing in user interfaces.

6 Biomedical Informatics 
Bios 
Philomena M. DiQuollo is a working healthcare IT professional who began her career in nursing and tran­
sitioned to IT&S 12 years later. Since 1985, she has worked in acute care facilities implementing clinical and 
business technology solutions as well as directing day-to-day operations and supporting strategic goals at a 
major urban teaching medical center in New Jersey. Currently, her position is system director of analytics 
within a multifacility healthcare system. Philomena DiQuollo is an adjunct faculty at New Jersey Institute of 
Technology teaching in the medical informatics program. She received her BSN from Seton Hall University 
and MA in Nursing from New York University. In addition, Philomena DiQuollo is a certified professional 
in Health Information Management Systems and is American Society for Quality Six Sigma Green Belt 
certified. She resides in New Jersey and is pursuing a master’s in analytics at Villanova University.

certified. She resides in New Jersey and is pursuing a master’s in analytics at Villanova University. 
Cathy Lubliner is a critical care clinical nurse specialist at an academic teaching hospital. She has over 
30 years experience in the care of patients with end stage heart failure, cardiogenic and septic shock, 
pre-and post transplant procedures, and ventricular assist devices. During the implementation of the 
hospital based EHR, she served as one of the “super users” to facilitate the transition of the nursing staff 
to the computer-based documentation/data entry system. 
Daniel Nasello  is an experienced mobile and web application developer and project manager who 
currently resides New Jersey. Having developed some highly successful applications (including multiple 
applications for various singers and actors), Daniel’s variety of experience allows him to bring the expe­
rience of multiple industries into the software he develops.

rience of multiple industries into the software he develops. 
Seeing the rapid growth of mobile application development, Daniel has created groundbreaking and 
innovating applications that will be used in tomorrow’s markets and is developing mobile and web 
application opportunities in industries where they are nonexistent. 
Daniel currently holds a bachelor’s of science in computer technology and a master’s degree from the 
New Jersey Institute of Technology in Information Systems. He is also a part-time instructor at NJIT 
where he spearheaded the mobile application development class, which is rapidly growing in popularity. 
1.4 Biomedical Informatics Challenges 
BMI initially focused on transitioning from paper to EHRs.  The discipline has evolved to incorporate clinical 
research, interoperability standards and enhanced user interfaces. The EHR endeavor is by itself extremely 
complex—creating on-line equivalents for the pharmacy, intake and discharge forms, manual and automated

complex—creating on-line equivalents for the pharmacy, intake and discharge forms, manual and automated 
data capture of real-time monitoring, status notes, etc., all tied into billing and inventory, changing docu­
mentation processes and education, developing secure, HIPAA Title II requirements and IT infrastructure 
for zero downtime and emergency procedures for system outages.  This complex EHR conversion would be 
the equivalent of converting a paper-based corporation to all electronic systems in a few years, develop strate­
gies, training, debug the system, etc. These processes, in corporations, have evolved over many decades and 
still require a great deal of improvement and monitoring. 
The major difference is that in a hospital, medical staffs, especially nurses, are taking care of critically 
ill patients, life and death situations, and then pausing care to enter data into a EHR system. They then

ill patients, life and death situations, and then pausing care to enter data into a EHR system. They then 
have to find the correct dropdown menu, enter the data, and review new medications and directives from 
doctors, and ensure there are no data entry errors, since the wrong dosage or incorrect data entry is not 
just a typo, it can be life threatening—and then move to another patient who is having a code. Prior to 
EHRs, medical staff filled out a tri-fold two-sided form and entered the data, and the process of review­
ing a patient status was simply flipping over a paper-based form to see a comprehensive view of a patient’s 
medical status. Medical professionals did not have to go into an often non-user-friendly system to quickly 
(in reality not so quickly) review a patient status. Can you imagine this scenario with any other disci­
pline—let’s say a pilot who not only is responsible for flying the plane but has to then document passenger

pline—let’s say a pilot who not only is responsible for flying the plane but has to then document passenger 
data, inventory all the food, fuel, and  document passenger issues, and they stop and go back to flying? Try 
doing this during takeoff and landing or an in-flight emergency. Currently, 8–10 hour shifts become 12 hour

7 Introduction to Biomedical Informatics 
with added documentation or patient care suffers since time has to be devoted to data entry. Nonhospital 
EHRs have different issues where additional staff are often required to manage EHR systems. 
Th e  p o s i t i v e  b e n e fi t s ,  i n  t h e  l o n g  r u n ,  w i l l  b e  s u b s t a n t i a l :  p r e v e n t i n g  d u p l i c a t e  t e s t s ,  s h a r i n g 
data between multiple medical practitioners, automatic drug interaction warnings. An evolved 
EHR system can cross-check patient IDs, medications, and procedures to reduce errors that 
are currently the cause of many deaths every year. A report in September 2013 by the Journal of 
Patient Safety  estimates up to 98,000 deaths a year are caused by hospital mistakes. Preventable 
adverse effects add an additional 200,000 injuries  http://journals.lww.com/journalpatientsafety/ 
Fulltext/2013/09000/A_New,_Evidence_based_Estimate_of_Patient_Harms.2.aspx.

Fulltext/2013/09000/A_New,_Evidence_based_Estimate_of_Patient_Harms.2.aspx. 
A seamless system will take a while to evolve. The deadline for the implementation of most EHRs is 
2015. This involves some of the most basic functionality defined by meaningful use standards, which 
rate the functionality of EHRs discussed in Chapter 3. The next phase of EHR implementation, 2015+, 
will not only include specialties that were not in the initial mandates—dentists, optometrists, mental 
health workers, etc.—but enhancing automatic data entry from monitors, radio frequency (RF) tags on 
blood products, supplies and equipment, and user-friendly interfaces to simplify data entry and visual­
ization of medical trends. 
1.5 Biomedical Informatics Curriculum 
Whether a college freshman or an experienced practitioner transitioning to this field—information tech­
nologist, nurse, radiologist, physicians assistant, etc.—guidelines for a course of study need to be quanti­

fied. Three perspectives will be introduced regarding possible Biomedical Informatics curricula. First are 
guidelines from an from an American Medical Informatics Association (AMIA) whitepaper. The second 
is from the National League for Nursing (NLN) which is comprised of nursing educators. Lastly, a current 
Biomedical Informatics bachelor’s degree program in place for 7 years will be described. The intent is to 
assist other programs in creating a curriculum for this new breed of professional. 
The AMIA suggested competencies are comprehensive and ambitious. They recommend that “one can 
select a subset that best complements an individual’s prior experience and future directions.” The AMIA 
curricula list virtually all computer science and IT courses taught at a university, without highlighting a

curricula list virtually all computer science and IT courses taught at a university, without highlighting a 
recommended subset for BMI programs. The last example is a current BS curriculum in medical infor­
matics that illustrates a subset specifically selected to compliment BMI professions with a few targeted 
optional courses. The question arises, should BMI professionals have all these skills and in what depth? 
In the technological AMIA skills list, networking, security, databases are listed; each in its own right is a 
separate field of study; they suggest machine learning, data mining, and simulation and  modeling. Very 
few computer scientists or information technologists are well versed in all those fields. Then, the BMI 
student needs some expertise in A&P, ethics, human computer interfaces. So, in part three, the BS in 
medical informatics/BMI will outline an existing bachelor’s program with optional concentrations so

medical informatics/BMI will outline an existing bachelor’s program with optional concentrations so 
students can pursue their specific interests. One example is a database concentration that suggests three 
available courses including database administration if the BMI student wants to focus on backend sup­
port systems. General requirements and optional concentration needs to be clearly delineated. 
Following are three perspectives for curriculum guidelines 
 1. The AMIA created a document listing core competencies for graduate BMI training in June 17, 
2010, voted and approved by its members. [link to all academic forum documents 2007–2014, 
http://www.amia.org/programs/academic-forum/annual-conference] 
 2.  The NLN informatics curriculum 
 3. A bachelor’s program in medical informatics, in place for the past 7 years at a Northeastern  
University, which provides flexibility for students pursing one of the many informatics sub-

fields designed to accommodate the evolving areas of expertise that will be required as this  
field evolves.

TABLE 1.2 AMIA 10 × 10 Course Outline 
 
AMIA: The 12 units of the on-line portion of the 10 × 10 course 
1. Overview of discipline and its history 
2. Biomedical computing 
3. Electronic health records and health information exchange 
4. Decision support: evolution and current approaches 
5. Standards: privacy, confidentiality, and security 
6. Evidence-based medicine and medical decision making 
7. Information retrieval and digital libraries 
8. Bioinformatics 
9. Imaging informatics and telemedicine 
10. Consumer health, nursing, public health informatics 
11. Organization and management issues in informatics 
12. Career and professional development 
Source: AMIA Curriculum. http://skynet.ohsu.edu/~hersh/ijmi-07–10x10.pdf. 
8 Biomedical Informatics 
1.5.1 AMIA Core Biomedical Competencies 
The AMIA, in June 2010, created a framework primarily of core BMI competencies for graduate students 
acknowledging the diverse backgrounds of individuals transitioning to this field.

acknowledging the diverse backgrounds of individuals transitioning to this field. 
1.5.1.1 AMIA Introductory Course Outline 
The AMIA, a branch of the AMA, has recommended a 10 × 10 single 12-week introductory course  of 
study. This outline provides a structure of representative topics that can be a starting point for this cur­
riculum (Table 1.2). 
1.5.1.2 General Framework AMIA: Core Competencies 
Four Key Areas (Source: AMIA Board White Paper ) 
It defines BMI and specifies core competencies for graduate education in the following disciplines 
(http://jamia.bmj.com/content/early/2012/06/20/amiajnl-2012–001053.full) (Figure 1.2):
 1. Scope and breadth of discipline : BMI investigates and supports reasoning, modeling, simulation, 
experimentation, and translation across the spectrum from molecules to individuals and to popu­
lations and from biological to social systems, bridging basic and clinical research and practice and 
the healthcare enterprise.

 2. Theory and methodology : BMI develops, studies, and applies theories, methods, and processes for 
the generation, storage, retrieval, use, management, and sharing of biomedical data, information, 
and knowledge.
 3.	 Technological approach : BMI builds on and contributes to computer, telecommunication, and 
information sciences and technologies, emphasizing their application in biomedicine.
 4. Human and social context : BMI, recognizing that people are the ultimate users of biomedical 
information, draws upon the social and behavioral sciences to inform the design and evaluation 
of technical solutions, policies, and the evolution of economic, ethical, social, educational, and 
organizational systems. 
1.5.1.3 Specific Core Competencies 
1.5.1.3.1 Technological Approach

1.5.1.3.1 Technological Approach 
BMI builds on and contributes to computer telecommunication and information sciences and technolo­
gies, emphasizing their applications in biomedicine (Table 1.3).

TABLE 1.3 Information Technology 
 Technological: Prerequisite knowledge and skills. Assumes familiarity with 
data structures, algorithms, programming, mathematics, and statistics 
Goals: Fundamental knowledge. Understand and apply technological 
approaches in the context of biomedical problems 
1. Networking, security, databases 
2. Information documentation, storage, and retrieval 
3. Imaging and signal analysis 
4. Machine learning, including data mining 
5. Simulation and modeling 
6. Representation of logical and probabilistic knowledge and reasoning 
7. Natural language processing, semantic technologies 
8. Software engineering 
9 Introduction to Biomedical Informatics 
Background in
biomedicine or 
the biosciences 
mathematical, 
physical or
computer/
information 
sciences or 
engineering 
Background and experience of graduate BMI candidates 
Biomedical Informatics (BMI)
core competencies 
Personalization of 
competencies 
cognitive
and/or social

cognitive
sciences 
FIGURE 1.2  AMIA biomedical informatics core competencies. (From http://jamia.bmj.com/content/early/2012/06/  
07/amiajnl-2012–001053.full.) 
1.5.1.3.2 Biological Foundations 
Population health: detection, prevention, screening, education, stratification, spatiotemporal patterns, 
ecologies of health, and wellness (Table 1.4). 
1.5.1.3.3 Human and Social Context 
Human and social context: Prerequisite knowledge and skills—familiarity with fundamentals of social, 
organizational, cognitive, and decision sciences (Table 1.5). 
1.5.1.3.4 Procedural Knowledge 
Procedural knowledge and skills: Apply, analyze, evaluate, and create systems approaches to the solu­
tion of substantive problems in BMI (Table 1.6). 
The AMIA realizes that students will come from a number of diverse backgrounds and realizes these

The AMIA realizes that students will come from a number of diverse backgrounds and realizes these 
suggested competencies are ambitious and recommends “one can select a subset that best complements 
an individual’s prior experience and future directions.”

TABLE 1.5 Human and Social Contexts 
 Human and Social Context: Prerequisite knowledge and skills. BMI, recognizing that people are the ultimate users of 
biomedical information, draws upon the social and behavioral sciences to inform the design and evaluation of technical 
solutions, policies, and evolution of economic, ethical, social, educational, and organizational systems. 
Familiarity with fundamentals of social, organizational, cognitive, and decision sciences. 
Goals: Fundamental knowledge. Understand and apply knowledge in the following areas: 
1. Design: human-centered design (HCI), usability, human factors, cognitive, and ergonomic sciences and engineering 
2.	 Evaluation: study design, controlled trials, observational studies, hypothesis testing, ethnographic methods, field 
observational methods, qualitative methods, mixed methods 
3.	 Social, behavioral, communication, and organizational sciences: for example, computer-supported cooperative work,

3.	 Social, behavioral, communication, and organizational sciences: for example, computer-supported cooperative work, 
social networks, change management, human factors engineering, cognitive task analysis, project management. 
4.	 Ethical, legal, social issues: for example, human subjects, HIPAA, informed consent, secondary use of data, 
confidentiality, privacy 
5.	 Economic, social, and organizational context of biomedical research, pharmaceutical and biotechnology industries, 
medical instrumentation, healthcare, and public health 
TABLE 1.4 Biological Competencies 
  
Biological: Prerequisite knowledge and skills. Students must be familiar with biological, biomedical, and population health 
concepts and problems including common research problems 
Goals: Fundamental knowledge. Understand the fundamentals of the field in the context of the effective use of biomedical 
data, information, and knowledge. For example

data, information, and knowledge. For example 
1. Biology: molecule, sequence, protein, structure, function, cell, tissue, organ, organism, phenotype, populations 
2.	 Translational and clinical research: genotype, phenotype, pathways, mechanisms, sample, protocol, study, subject, 
evidence, evaluation 
3.	 Healthcare: screening, diagnosis (diagnoses, test results), prognosis, treatment (medications, procedures), prevention, 
billing, healthcare teams, quality assurance, safety, error reduction, comparative effectiveness, medical records, 
personalized medicine health economics, information security, and privacy 
4. Personal health: patient, consumer, provider, families, health promotion, and personal health records 
5.	 Population health: detection, prevention, screening, education, stratification, spatiotemporal patterns, ecologies of 
health, and wellness 
 Procedural knowledge and skills: Apply, analyze, evaluate, and create systems approaches to the solution of substantive

 Procedural knowledge and skills: Apply, analyze, evaluate, and create systems approaches to the solution of substantive 
problems in Biomedical Informatics 
1. Analyze complex biomedical informatics problems in terms of people, organizations, and sociotechnical systems 
2. Understand the challenges and limitations of technological solutions 
3. Design and implement systems approaches to Biomedical Informatics applications and interventions 
4.	 Evaluate the impact of Biomedical Informatics applications and interventions in terms of people, organizations, and 
sociotechnical systems 
5. Relate solutions to other problems within and across levels of the biomedical spectrum 
10 Biomedical Informatics 
TABLE 1.6 Procedural Knowledge and Skills 
1.5.2 National League for Nursing Informatics 
The NLN has 33,000 individual and 1,200 institutional members. They have defined a core framework for

The NLN has 33,000 individual and 1,200 institutional members. They have defined a core framework for 
Nursing Informatics into four curricular threads: IT, communication, issues, and nursing collaboration. 
There is a NLN white paper Preparing the Next Generation of Nurses to Practice in a Technology-Rich 
Environment: An Informatics Agenda introduced in May 2008 whose stated goal is “to prepare the next 
generation of nurses to practice in a technology-rich environment” that outlines its recommendations 
to nursing faculty and administration (see recommendations in the following text) http://www.nln.org/ 
aboutnln/PositionStatements/informatics_052808.pdf.

Health IT Tools Suggest the Curriculum Include Lectures on These Topics) 
1.	 Computerized order entry: Clinical application that allows clinicians to order and process lab tests, medications, 
clinical procedures, and other services electronically. 
2. Health information exchange enables clinical staff to access more information about a patient when it is needed. 
3.	 Electronic prescribing: The use of computing devices to enter, modify, review, and output or communicate drug 
prescriptions. 
4.	 Electronic medical record systems: A basic component of a health IT system, electronic medical record systems have 
the potential to provide substantial benefits. 
5.	 Telehealth: Geographic disparities in access to care can be addressed partially using technologies that allow for 
remote audio, visual, and haptic communication between caregivers and specialists or patients. 
6.	 Clinical decision support: Given the exponential growth in our knowledge of medicine, it is impossible for any

6.	 Clinical decision support: Given the exponential growth in our knowledge of medicine, it is impossible for any 
clinician to know everything he or she needs to know. 
11 Introduction to Biomedical Informatics 
TABLE 1.7 NLN: Information Technology Curriculum 
(
Sour
ce: http://www.nln.org/facultyprograms/facultyresources/facultyresources.htm. 
“Nursing informatics is defined as combining nursing science, information management science, and 
computer science to manage and process nursing data, information, and knowledge to deliver quality 
care to the public” (HRSA, 2008). Nursing informatics facilitates the integration of data, information, 
and knowledge to support patients, nurses, and other providers in their decision making in all roles and 
settings. ( http://www.nln.org/facultyprograms/facultyresources/informatics.htm) 
1. Use of health IT to augment/support the nursing care process includes concepts such as safety,

1. Use of health IT to augment/support the nursing care process includes concepts such as safety, 
care improvement, decision assistance/support, outcome analysis and data analysis. 
2. Communication includes EHR persona l hea lth records, standardized languages, and terminolog y. 
3. Issues including legal, ethical, social, security, advocacy, and public policy. 
4. Nursing involvement through teamwork/collaboration, covering nurses’ role in determining 
usability, workflow analysis, and systems selection/evaluation. 
1.5.2.1 NLN Health IT Tools 
The NLN IT component lists a skill set of tools they suggest will have to be utilized as indicated by nursing 
practice (Table 1.7). 
Since the rest of the guidelines are generic nursing recommendations, such as ethics and teamwork that 
are not unique to biomedical informatics curriculum, the included links will provide that additional content. 
1.5.3 Bachelor’s in Medical/Biomedical Informatics Curriculum

1.5.3 Bachelor’s in Medical/Biomedical Informatics Curriculum 
This section is structured around a 4-year bachelor’s degree specifically focused on educating Biomedical/ 
Medical Informatics professionals. 
The challenge of training professionals, from their first encounter within this field provides an unprec­
edented opportunity to shape the future of the discipline. There are only a handful of BS programs 
in this field and even fewer associates degrees. But the employment opportunities are stellar for new 
graduates, not only evidenced by Department of Labor, but due to the change in demographics, i.e. 
the U.S. Census Bureau projects one-fifth of the U.S. population will be over 65 by 2030, and with the 
expanded Affordable Care Act (ACA), this expanded healthcare demand will necessitate more trained 
professionals to handle the millions of new individuals with healthcare coverage. New wearable wireless

professionals to handle the millions of new individuals with healthcare coverage. New wearable wireless 
technologies, feeding data into EHRs, will also necessitate the need for more professionals in this field. 
The BS degree is structured into core areas that allow flexibility, so programs or students can develop 
additional expertise in areas of interest.

12 Biomedical Informatics 
Core medical/biomedical areas are as follows:
 1.  IT
 2.  Biological/medical
 3.  Medical informatics
 4. Ethics/management/economics 
1.5.3.1 Future Employment Prospects for BS Degrees in Medical/Biomedical Informatics 
 1.  The U.S. Bureau of Labor Statistics  has projected that the fastest-growing professions are in the  
computer and heathcare industries specifically in the medical records/informatics areas (http:// 
www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm). 
 a.	  They indicate in 2012, the last full-year statistics are available, that there were 186,300 indi­
viduals employed in this profession and projections call for 41,000 additional hires the next 
year. They project a 22% growth rate from 2102 to 2022.
 b.	  The  U.S. Department of Labor 2012–2022 has projected that for the next decade 2012–2022  
projections call, the medical records and health information technicians occupation will

projections call, the medical records and health information technicians occupation will  
grow 22%. http://www.bls.gov/ooh/healthcare/medical-records-and-health-information­
technicians (htm#tab-6). 
 2.  The projected doubling of the over 65 population in the next 2 decades one-fifth will be over 65 
by 2030 indicated by the U.S. Census Bureau. Baby boomers, in the next 20 years, will necessitate 
the need for medical informatics professionals to upgrade the tens of thousands of medical prac­
tices across the United States. Subfields of medical informatics, i.e., wireless medical devices, will 
necessitate the need for additional trained personnel to integrate data from these devices. 
 3. Forty percent of all medical costs are related to medical documentation, billing, and administra­
tive overhead, costs that will necessitate the need of reducing the overhead by automated medical 
records systems.

records systems. 
 4. The large population in the New York metropolitan area indicates the need for a large number 
of medical/biomedical informatics professionals. As per the 2012 U.S. census in the New York 
metropolitan area, tri-state area has 19.8 million people. It is the most populous metropolitan area  
in the United States defined by the Office of Management and Budget as the  New York-Northern 
New Jersey-Long Island, NY-NJ-PA Metropolitan Statistical Area . 
1.5.3.2  BS Medical/Biomedical Curriculum 
The Medical/Biomedical Informatics bachelor’s degree includes the traditional curriculum core courses:  
English I, II, and III (technical writing), and history/sociology/psychology, capstone core courses. The math  
courses are statistics, precalculus, calculus (business calculus is an alternative), several core computer and

courses are statistics, precalculus, calculus (business calculus is an alternative), several core computer and  
database courses. Management and ( medical) economics courses round out the first 64 credits with a few  
electives. Some students can choose a management track, taking additional accounting, business, and  
cost-analysis courses. Others choices include additional biology and chemistry courses for their electives. 
Bachelor’s degree 128 credits are broken down into these general categories: 
• 64 credits common core courses 
• 64 medical/biomedical informatics and information technology 
• The curriculum for a 2/year associates degree in Medical Informatics is provided in Table 1.8. 
1.6 Chapter Summaries 
The chapters in this book are designed to be covered in sequential order. Concepts build on preceding chap­
ters. Chapter 7 on medical sensors is the exception where Level IV provides four optional sections on A&P

ters. Chapter 7 on medical sensors is the exception where Level IV provides four optional sections on A&P  
basics. Some instructors add between 10 and 30 minutes of selected A&P lectures at the end of their lectures.  
The rationale is to create a basic core A&P knowledge base where students develop a balanced technological

Bachelor’s Curriculum in Medical Informatics/Biomedical Informatics (64) (optional courses depend on 
program and student interests) 
Core Area(s) 	 Required Electives Credits 
Information Technology Intro Information/Computer 3 
Technologya 
15 credits required Intro to Programming (object Advanced Programming 3 
15 credits recommended oriented Python, VB)a	 (C++, JAV A) 
(Recommended) 
(3 credits) 
Intro to Database Design I
a Advanced Database design 3 
II (3 credits) 
Database Administration 
III (3 credits) 
Intro Computer Security Wireless Networks Security 3 
(Recommend) (3 credits) 
Web Design (optional in first App Design for Mobile 3 
2 yearsa) Devices (recommend) 
Human Computer 
Interface (HCI) Design 
Biological–Medical Anatomy and Physiology I
a Biology I 4 
14 credits required Anatomy and Physiology I Chemistry I 4 
8 credits recommended 
Medical Terminologya 3 
Pharmacologya 3 
Ethics/Management/Economics Medical Ethics (optional in first 3

Ethics/Management/Economics Medical Ethics (optional in first 3 
2 yearsa) 
9 credits required 
6 credits recommended 
Economics (Medical)a Cost Analysis (3 credits) 3 
Intro Management Management in 3 
Healthcare environments 
(Bio)medical Informatics Medical Informatics I (survey of the Internship I: 75 hours 3 
field)a (2 credits) 
-9 credits required Medical Informatics II Advan: Internship II: 75 hours 3 
-6 credits recommended management, case studies (2 credits) 
Medical Informatics III EHR’s hands Internship III: 75 hours 3 
on exercises (2 credits) 
Totals (64 should be taken) 47 Credits At least 17 credits 
selected/35 
13 Introduction to Biomedical Informatics 
TABLE 1.8 Medical/Biomedical Informatics Curriculum 64 Credits 
a Courses taken at community colleges. 
and biological underpinning. The two chapters at the end of the book, written from the perspective of nurses

and biological underpinning. The two chapters at the end of the book, written from the perspective of nurses 
utilizing EHRs and a managers perspective implementing EHRs, can be added at any point in the semester. 
Some instructors believe that right after Chapter 3 on EHRs is the time to introduce the real world per­
spectives by professionals utilizing EHRs. Lastly, the appendices on application (app) development for EHRs 
either can be instructor led or provided as exercises for students to pursue for a final class project. All EHRs 
will eventually evolve to provide user friendly intuitive interfaces simplifying user input and providing long-
term trend analysis of medical conditions (Table 1.9). 
Most chapters include an illustration that summarizes the content of each chapter.

Chapter 
Summary Illustration Summarizing the Content of Most Chapters 
1. Introduction 
to Biomedical 
Informatics: 
This chapter 
frames the 
challenges 
addressed by 
Biomedical 
Informatics 
(BMI).
A discussion 
on BMI 
curricula 
introduces 
AMIA, NLN, 
and an
evolving BS 
program 
curriculum 
that was 
introduced in 
2007. 
Fields 
Clinical research informatics 
Biomedical InformaticsOrganixzaton Chaptercurricula(Textbook) summaries (Core competencies) 
Chapter Organization American Medical Informatics
(Diagrams) Association (AMIA)
Level I is comprised of core National League of Nurses
topics that a Biomedical (NLN) Informatics Curriculum
informaticist should master 
Level II contains applied Bachelors Program in Medical

concepts that support the Informatics in Northeastern
concepts in Level I University
 
(Continued ) 
14 
TABLE 1.9 Textbook Synopsis of Each Chapter
Biomedical Informatics

Chapter 
2. The U.S. 
legislation that Framework for implementing the U.S. Medicalhas spurred Records Infrastructure the explosion 
of electronic 
health records 
(EHR)
adoption. Health Insurance Portability and American Recovery and Affordable Care Act
Accountability Act (HIPAA) 1996 Reinvestment Act (2009) (2010) Obama Care 
Title I 
Health Information Title I. Quality, AffordableHealth Insurance Reform
Technology for Economic Healthcare for All Americans
and Clinical Health ActTitle II
Administrative Simplification (HITECH)
 
Security Privacy Subtitle A: Immediate
Improvements in Healthcare
Title III Subtitle C:
Certified EHR Coverage for all
Tax-Related Health Provisions
 Technology Americans
funding to
Provide
Secure—Protected Individuals
Title IV support the Meaningful use Families
Application and Enforcement
 Prevention Small Business Owners of Group Plan Requirements implementation
Standards of EHR’s 
Title V

Title V
Revenue Offsets
 
15 
TABLE 1.9 (Continued) Textbook Synopsis of Each Chapter

Chapter 
3. EHR are a 
collection of
data Electronic Health Records (EHR)
accumulated 
from various Architecture
 Lubliner 2015
Office of the Personal Datasources that Interoperability Standards ImplementationNational Coordinator Recordsdocument a 
(ONC) EHR Spec. (PDR)patient’s Health Meaningful Use
journey HL 7 RIM Models Continuity of Information
through the Exchanges -HL 7 -DICOM,
Care Recordhealthcare (HIE) -ISO -ICD10,
(CCR) -IEEE -SNOMED
system. 
Arden Syntax DSS -FHIR -LOINC Data Entry Forms HITECH Affordable
HIPAA  -CDA  -CPT Act Care Act 
-CCOW -HCPCS 
EHR-System Tools UMLS
Functional Models Security
Privacy Expert Systems
Query Consumer Clinical Decision Support
Directed Relationship
Based Mediated Hierarchy diag. Systems (CDSS) 
16 

Chapter 
Data 4. 
interoperability  
focuses on 
HL7, NCPDP (pharmacy), ISO, IEEE, IHE (International Health Exchange) HL7 standards
electronic 3: Mapping
 EHR-S
medical Tools
 Communication Protocols to facilitate interoperability of Electronic Health1:
Arden syntax
communication -UMLS
Information 
FHIR
and data sharing -UML-F
 CCOW
-OMG SysML CDAstandards. EHR, 	 2: Vocabularies/Codes ICD10 Virtual medicalOrganizations	 IEEE 1073medical devices, 	 ICD11
-AMA	 (14,000) Medical device LOINC Recordlaboratories -AMIA	 ICD10 communication (lab, nursingdata, imaging -HIMSS SNOMED CT ICD10 PCS U.S. and personal documentation)
studies, etc., 	 -RSNA (300,000 terms) CMU.S. (78,000) medical devices Vocabularies:
-ACC

-ACC
 (68,000)have to agree on 	 Procedural-ISO	 Disease andcommon	 codes Lexi-comp Common-Regenstrief SNODENT diagnosis and medi-spanprotocols to -HHS	 DICOM medical(dental)	 (imaging, CT, (drug referenceexchange data. -NLM	 terminologyand clinical-HL7	 MRI, XRAY )
CPT services provided	 support)HCPCS codes
for reimbursement AMA
-IEEE
Medicare-medicaid
-ANSI
-IHTSDO	 Health information exchanges (data interoperability EHR’s) Caveat: includes dominant interoperability
-EFMI	 standards, not inclusive of all specifications
-OMG Lubliner 2015 
17 

Chapter 
5. Privacy and Privacy and Security
Security:
HIPAA Title II 
describes 
HIPAA Title II Security primer	 Biometrics
security as the (Health Insurance Portability and Accountability Act 1996)
safeguards
that must be
DNA
Administrative
 Defense in depthin place to 	 (F5.com term is defense 13 COODIS Core STR Locl(Policies & procedures) in Breath) 
ensure with chromosomal positions
appropriate Privacy:	 Security: 
protection of That sets limits and conditions on the use The safeguards that must be in place to ensure
and disclosure of medical information appropriate protection of electronic Protected
electronic without patient authorization Health Information (ePHI) 
protected
health
Physical Technicalinformation (controls) (controls)
 
(ePHI). A Exceptions
 Lubliner 2013 
security
primer 
Public health Research Breach notification Encrypted PHI
 
introduces

security
primer 
 
1. Compromises a patient’s health; i.e., abasic security patient is unconscious (privacy rules waved) Penalties Retinal Scan Finger-Printtechniques.	 -Breaches:2. 	Public health is threatened
 
-Involving more than 500 individuals the security
3. Research (anonimized data)  rule require that they notify HHS immediately.1. With the permission of an IRB or -More than 500 individuals requires media be notified       Privacy board the patient’s privacy
-Encrypted PHI:rights can be waived. They are:
 
-Not required to provide breach notification because
4. Treatment, Payment, Healthcare operations the information is not considered “unsecured” Public-Private encryption 
18 

Chapter 
6. Telehealth– Telehealth 
Telemedicine Telemedicine (Delivery of services and diagnosis) is the practice 
of medicine or 
 M-health
analyzing Communications (Mobile Wireless Medical Tele-radiology CCRN-E Cost/Need
Tele-surgeryDevices And Software) and medical consults AACN cert.medical data 
remotely.
 © Lubliner 2013
mHealth -90% radiologists are inWaveLan M-Health
FDA Approved large remote groups -Monitor 10,000 babyrefers to IEEE 802.11n 600 Mbit/s First generation wireless da Vinci System -In 2013 the top 100 firms critically illmedical Boomers reach 65IEEE 802.11ac 6.93 Gbit/s medical devices 2013  million perf.1.5   have 5000 radiologists patients every daypractice using Wireless-Personal-Networks Second generation 2014 -Specialists provide expert remotelymobile Bluetooth4 24 Mbits/s iHealth, Fitbit, iWatch   opinions 24/day -Consultation
monitoring IrDA-UFIR  96 Mbits/s Telemental Affordable Care

WUSB 480 Mbits/s Implantable medical devices health Nurse Act focus ondevices. 
IrDA-GigalR  1024 Mbits/s Tele-education working in prevention
Home monitoring of patients tele-ICU
Teleradiology, 
telesurgery, Crisis response and devices: EKG, implantableand or eCCU -Reduce inpatientassist devices Some Apps deliver services: fall under telemedicinecertifications Electronic health costs
are also records -Reimbursement Qualifications: -Reduce cost of Doctors-on-demand app1.discussed. Mini clinics (will RN 5 years large facilities RingaDoc.com2. by Medicare   require remote consults) with critically outpatient ERSNOMED, ICD11, HL 7, DICOM 3. 3GDoctor.com England -Rural Areas ill patients 
19 

i
R
20
ohms10
volts
+u
Chapter 
7. Medical 
Sensors. This 
chapter
focuses on the 
exponential 
growth of
medical
sensors. It 
foundations of
chemistry, 
biology, 
physics, and 
electronics to
ensure the 
BMI
professionals 
are well 
grounded in 
their field. It 
also includes 
an anatomy
and
physiology 
primer. 
Medical sensors 
Electrical and chemical conduction basics Data Acquisition:
basic theory 
Medical Sensors and
Measurements
Blood pressure Body sensor
networks (BNSs)c Subatomic particles
Battery chemistry Inductive charging
Part I: Neurons and nervous system,
brain, spinal cord, muscles, heart, eye 
Part II: Cells, ATP , hearing, kidneys,
pancreas, liver, digestive system 
Part III: Lungs, immune system, strokes,
blood flow, prostate Part IV: Heart disease, cancer 
Data mining and big
data in healthcare 
Cods 
Secondary
core 
Primary
core 
– 
Magnetic field 
L 2 L 1

Cods 
Secondary
core 
Primary
core 
– 
L 2 L 1 
(ATP) Adenosine triphosphate 
Pulse oximetry
Beer’s Law
Absorbance (ad) = εcd 
Beer Lambert law 
Lambert-Bouguer Law 
I = Io e –(ad) 
Anatomy and Physiology Primer 
Current flow Valence electrons 
Action potential Electrical conduction
Heart 
Wireless medical
monitoring 
C i = n i
V 
20 Biomedical Informatics

Chapter 
8. Imaging: This 
chapter, first, 
discusses 
imaging devices 
and the complex 
physics and 
algorithms 
involved in 
analyzing this 
data; second, the 
standards used 
for transmitting 
and visualizing 
these images; 
and third, the 
system for 
storage and 
retrieval of
images picture 
archiving and 
communication 
system. 
Medical imaging
(DICOM) Digital communications and communications in medicine 
(framework supports communication, storage and handling of medical images)
Medical imaging hardware, physics and Picture archiving and retrieval system
algorithms (PACS) 
Radio pharmacology Image analysis
 
Principal component analysis
 
DICOM Standards
Object definitions
Data classes 
Data structures
 
Data dictionary
 
Message service
Presentation
Storage media and file
service
Media storage
 
Media formats
Gray scale standards 
Security and System Management
Web Access
Content mapping
Transformations
Handling

service
 
Web Access
Handling
Storing
Printing
Communications
21 

Chapter 
9. Ethics: This 
chapter
discusses the 	
Hippocratic oath
(original and revised) American 
Medical 
Association, 
the American 
Nurses 
and case 
studies 
relating to
medical ethics.
 
Medical Ethics
American Medical Association
(AMA) ethics groups 
American Nurses Association Ethical case
(ANA) ethics group studies 
10. Nursing The focus of this chapter is to explain the complexity of critical care nursing in the context of the data that are generated and the process of recording that data. 
Documentation Documenting patient care activities during emergency situations, which occur oft en in the critical care setting, is particularly challenging because many activities 
and the are occurring simultaneously. 
Electronic 
Health Records

Health Records 
11. Nursing In this chapter, the focus will be on what it takes to support a healthcare organization’s IT infrastructure and to understand the complexity of a heavily regulated,
Management	 highly technical, and safety conscious environment. 
22 

Chapter 
12. The future Future directions of Biomedical Informatics 
directions of
biomedical Predictive Analytics Future Scenarios
 
informatics
 
Five years: Scenario 1: 95%
Biomedical Predictive Analytics of all medical documentation
Intelligent
Lubliner 2014 data integrated and online 
Ten years: Scenario 2: All medical 
devices will automatically IntelligentPredictive update electronic health Cost factors: Predictive Intangible assistants Confidence External mandates records
weights costs Factors (PCF) 
Twenty five Scenario 3: EHR(2) the

Twenty five Scenario 3: EHR(2) the 
next evolution in useryears: Global interfaces and distributed Extracted Cost Political integration Subsidies healthcarePositiveHCACPS factorsfrom trends implementing (user surveys)CDC reports technologies Fifty years: Scenario 4: Distributed Penalties Negative healthcare:medical care150 year lifeCost of not will evolve beyond our spans. implementing Meaningful Confidence current location based 
hospital-physician centric technologies use levels One hundred system 
years: Ten steps
forward or 5 Scenario 5: eDoctor and Example 
steps back intelligent medical kiosks 
Appendix: An application development primer for those individuals who are interested in developing the next generation of user interfaces for Electronic Health Records on
Application mobile platforms the author refers to EHR2. 
Development 
for Mobile 
Devices and 
EHRs 
23 

for Mobile 
EHRs 
23 

24 Biomedical Informatics 
Glossary 
Bioinformatics, research focus, analyzes datasets for genomics, proteins etc. “The branch of informa­
tion science concerned with large databases of biochemical and pharmaceutical information” 
(World English Dictionary), it intersects with the field of computational biology. 
Biomedical engineering is defined as a field dealing with the application of engineering principles to 
medical practice. It also lies at the intersection of electrical engineering and the biological 
sciences. 
Biomedical informatics extrapolates meaning from diverse biological, medical, nursing, health, and 
clinical research sources and structures data via intuitive interfaces to enhance healthcare and 
delivery (Lubliner 2014). 
Clinical research informatics is the discovery and management of new knowledge relating to health 
and disease. It includes management of information related to clinical trials.

Consumer health informatics is the field “devoted to informatics from multiple consumer or patient 
views. These include patient-focused informatics, health literacy, and consumer education.” 
The focus is on information structures and processes that empower consumers to manage their 
own health; for example, health information literacy, consumer-friendly language, personal 
health records, and Internet-based strategies and resources. The shift in this view of informat­
ics analyzes consumers’ needs for information. 
Health informatics is “the interdisciplinary study of the design, development, adoption, and 
application of IT-based innovations in healthcare services delivery, management, and 
planning.” 
Informatics is “a field of study to apply IT to another field, from healthcare to journalism to biology to 
economics” (Indiana University).

economics” (Indiana University). 
Medical informatics (often used interchangeably with biomedical informatics, but the term biomedical 
is currently the preferred term used by the leading informatics body in this field, the AMIA) . 
It is “the science and art of modeling and recording real-world clinical concepts and events 
into computable data used to derive actionable information, based on expertise in medicine, 
information science, IT, and the scholarly study of issues that impact upon the productive use 
of information systems by clinical personnel” (S. Silverstein, MD). 
Nursing informatics is the “science and practice (that) integrates nursing and implementation of com­
munication and IT” (AMIA). 
Translational bioinformatics is the development, analytic methods to optimize the transformation of

Translational bioinformatics is the development, analytic methods to optimize the transformation of 
biomedical data, and genomic data, into proactive, predictive, preventive, and participatory 
health. 
1.A Appendix 
Curricula for existing medical informatics associates degree programs 
1: This is an information technology–centric 2-year medical informatics associates degree program. 
(IT–centric refers implies that it was created by the IT department with additional courses focusing on 
the medical informatics curriculum.) 
General Education Requirements 
Communication 
EN 101 Composition I 3 
EN 102 Composition II 3 
Mathematics Electives 
MA 108 College Algebra 3 
(Continued)

25 Introduction to Biomedical Informatics 
Science Electives
 
BS 103 Anatomy and Physiology I 4
 
BS 104 Anatomy and Physiology II 4
 
Technology Competency or Information Literacy
 
CIS 107 Information Technology 3
 
Fundamentals and Applications
 
CIS 125 Microcomputer Software I 3
 
Social Science EC 101 Economics I 3
 
PS 101 Introduction to Psychology 3
 
Humanities Elective Choose 3 credits from General 3
 
Education Humanities course list
 
Total general education credits 32
 
Major Requirements CIS 106 Linux Fundamentals 1
 
CIS 108 Programming Fundamentals 3
 
CIS 165 Fundamentals of C++ 4
 
Programming
 
CIS 180 Networking Essentials 3
 
CIS 202 Systems Analysis and Design 3
 
CIS 286 Network Security 3
 
Fundamentals
 
CIS 290 Database Fundamentals 3
 
CIS 294 CIS Internship or CIS 295 2
 
Capstone Project
 
HIT 111 Culture of Healthcare 3
 
HIT 112 Introduction to Medical & 1
 
Healthcare Terminology
 
HIT 212 Computer Applications in 3
 
Healthcare

Total major credits 29
 
Total degree credits 61
 
2: This is a health-centric associates degree program in medical informatics since the program evolved 
from a health curriculum with added information technology courses. 
Semester 1
 
WRT101 English Composition I 3
 
BIO109 Anatomy and Physiology I 4
 
MOA140 Medical Terminology 3
 
INF101 Introduction to Information Technology 3
 
INF … Programming Language Fundamentals 3
 
Total 16
 
Semester 2
 
WRT201 English Composition II 3
 
BIO209 Anatomy and Physiology II 4
 
MOA201 Diagnostic and Procedural Coding 4
 
INF … Advanced Programming Languages 3
 
Humanities Elective* 3
 
Total 17
 
26 Biomedical Informatics 
Semester 3
 
MOA141 Introduction to Medical Assistant 3
 
MOA218 Medical Economics 2
 
INF217 Database for Business Applications (note: 3
 
curriculum request to change name to Database for 
Applications)
 
MAT… Mathematics Elective** 3–4
 
WEX101 Dynamics of Health and Fitness 2
 
Total 16–17
 
Semester 4
 
MOA200 Pharmacology for Medical Office Assistants 2
 
INF218 Database Programming 3
 
INF219 Database Administration 3
 
BUS101 Introduction to Business 3
 
Social Science Elective*** 3
 
WEX… Wellness and Exercise Elective 1
 
Total 15
 
Total Degree Credits 64–65

Level I: Core Concepts ...................................................................................28
 
2.1 	 Introduction ........................................................................................28
 
2.2 	 HIPAA ..................................................................................................29
 
Title I: Health Insurance Reform • Title II: Privacy,
 
Applications: Implementing HIPAA Title II • Title III: Tax 
Simplification Rule • Title IV: Group Healthcare Guidelines and
 
Enforcement • Title V: Application and Enforcement of Group Health
 
Security, Standards, Administrative Simplification •  Level II 
Plans
 
Level I: Core Concepts (Continued) ............................................................38
 
2.3 	 American Recovery and Reinvestment Act of 2009 ......................38
 
Health Information Technology for Economic and Clinical Health Act

2.4 	 Affordable Care Act ............................................................................39
 
Meaningful Use
 
2.5 Summary .............................................................................................. 41
 
Questions .........................................................................................................42
 
Glossary ...........................................................................................................42
 
References ........................................................................................................43
 
2 
Framework for  
Implementing the  
U.S. Medical Records  
Infrastructure 
27

28 Biomedical Informatics 
2.1 Introduction
 
In the United States in the early 1960s, a number of public and private initiatives began the 
exploration of EHRs (see Section 3.2 on the history of EHRs in 1960 to 1996 that led up to the HIPAA 
of 1996). The Veterans Administration in 1971, the largest medical provider in the United States, 
started developing an EHR and rolled out a working system worldwide in 1987, originally called the 
Veterans Health Information Systems and Technology Architecture (VistA) (http://www.ehealth. 
va.gov/VistA.asp) and currently renamed HealthVet, the next generation of VistA. This chapter 
focuses on initiatives that spurred the development of the EHRs in the United States: HIPAA [3], the 
Affordable Care Act (ACA) [1] , and the stimulus bill. Government documents, many of which can be 
found at www.HHS.gov, are used to outline important provisions contained in these acts focusing

found at www.HHS.gov, are used to outline important provisions contained in these acts focusing 
on the evolution and implementation of EHRs. For a complete list of all provisions of HIPAA, ACA, 
and the stimulus bill, links are provided. 
The beginnings of a quantified approach to healthcare first began in 1996 with the HIPAA under 
President Clinton, Public Law 104–191. A number of incremental modifications in the ensuing decade 
were made culminating in the Final Rule in 2013 (see Figure 2.1). The evolution and adoption of 
EHRs continued with the American Reinvestment and Recovery Act(ARRA )[2] Feb.17,2009 [stimulus 
bill] with a Health IT funding component the HITECH ACT[4], 19.7 billion of which was earmarked 
to subsidize EHR implementation, and later with the ACA of 2010. These three major government 
initiatives spanning 1996 and 2010 laid the foundations for the evolution of the electronic medical

initiatives spanning 1996 and 2010 laid the foundations for the evolution of the electronic medical 
infrastructure in the United States whose goals were to enhance healthcare delivery and accessibility, 
reduce errors, eliminate duplicate diagnostic procedures, and create integrated research and clinical 
databases with patient confidentiality specified by HIPAA Title II, which brought healthcare efficien­
cies in par with other industries. The rationale was that unless the government subsidized the consid­
erable costs inherent in the transition, most physicians and hospitals would be unwilling or unable 
to convert to EHRs. Punitive measures were added so that e-prescriptions, issued by physicians, after 
2013 and Medicare and Medicaid reimbursement costs after 2015, would receive reduced compensa­
tion if they breached that deadline. 
HIPAA, a core component of the evolution of U.S. EHRs, was not created in a vacuum. The mod­

ern need for standard medical vocabularies was started in 1948 by the World Health Organization 
by creating the International Classification of Diseases (ICD) (see Chapter 4). The need for classify­
ing disease began much earlier at the dawn of written text, papyrus, where ancient Egyptians and 
Babylonians around 3300 BC began to quantify a system of medicine. Technology has evolved with the 
emergence of medical texts. In 1450, Johannes Gutenberg developed the first practical screw printing 
press, but these presses were not widely available till the early 1500s. Soon after in 1542, the first wide-
scale pharmaceutical text Antidotarium Florentine  was published by the Florence College of Medicine, 
quantifying medicines and treatments. 
EHRs became possible with the evolution of mainframes in the 1950s, personal computers in 1980s

EHRs became possible with the evolution of mainframes in the 1950s, personal computers in 1980s 
and the Internet in the 1990s. The emergence of HIPAA in 1996 logically followed the ability to con­
nect medical data worldwide. Since then, the growth has been exponential. The limiting factor was 
cost, and also political factors can’t be discounted, so the American Resources and Recovery Act in 
2009 with the HITECH Act included amendments providing resources to subsidize hospitals and 
physicians to defer the initial start-up costs (see Chapter 3). The next logical step was the ACA, that 
is, ObamaCare, which made healthcare universally accessible and affordable in the U.S. A caveat, 
universal dental care still lags behind. Only 50% of U.S. citizens have dental insurance, which is the 
next challenge to be addressed.

Framework for Implementing the U.S. Medical
Records Infrastructure
 
Health Insurance Portability and
Accountability Act (HIPAA) 1996 
American Recovery and
Reinvestment Act (2009) 
Affordable Care Act 
(2010) ObamaCare 
Title I 
Title II 
Health Insurance Reform Health Information 
Technology for Economic
and Clinical Health Act 
Title I. Quality, Affordable
Healthcare for All Americans 
Title III 
Title IV 
of Group Plan Requirements 
Tax Related Health Provisions 
Administrative Simplification 
Security Privacy 
(HITECH) 
Subtitle C: 
Provide 
funding to
support the
implementation
of EHR’s 
Certified EHR 
technology
Secure-protected
Meaningful use
Prevention 
Standards 
Subtitle A: Immediate 
improvements in healthcare
coverage for all
Americans 
Individuals 
Families 
Small business owners 
Title V
 
29 Framework for Implementing the U.S. Medical Records Infrastructure

Families 
Title V
 
29 Framework for Implementing the U.S. Medical Records Infrastructure 
FIGURE 2.1 Implementation dates of critical components to healthcare infrastructure. 
Three core U.S. healthcare initiatives (Figure 2.1): 
 1.  The HIPAA of 1996, under President Clinton (http://www.hhs.gov/ocr/privacy/hipaa/ 
administrative/) 
 2.  The $787 billion economic stimulus bill passed under President Obama on February 19, 2009, of  
which 19.7 billion was targeted at Health IT ( HITECH Act U.S. news, http://news.cnet.com/8301– 
13578_3–10161233–38.html) 
 3.  The ACA of 2010, passed under President Obama, often referred to as ObamaCare (http://www. 
hhs.gov/healthcare/facts/timeline/) 
2.2 HIPAA 
The HIPAA was enacted in 1996 and had several goals: portability of insurance when moving between 
jobs, security and privacy of personal medical data, setting guidelines and penalties for fraud and

jobs, security and privacy of personal medical data, setting guidelines and penalties for fraud and 
abuse of health information relating to unauthorized access to patient data, and creating a framework 
of standards that could ensure accurate communication and coding schemas so practitioners could 
reliably communicate. For example when describing heart attack, you might use angina or angina pec­
toris (temporary inadequate blood supply to the heart muscle), variant angina (caused by a spasm), or 
Prinzmetal’s angina (pain caused in clusters). Clear precise terms agreed upon by all are essential in 
medical diagnosis and treatment . Figure 2.2 summarizes the components of HIPAA and the first para­
graph of law 104–191 that clearly espouses its objectives.

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Simplification 
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Encouraging the
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and individual marke
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of me
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workers and their
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lose their jobs
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Guidelines fo
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Health Insurance Portability and Accountability Act (HIPAA)

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(Enacted in 1996: Intent to provide portable medical insurance coverage for individuals who change jobs)
30 
FIGURE 2.2 Health Insurance Portability and Accountability Act provisions. (From http://www.hhs.gov.healthcare/.) 

Title II 
Preventing Medical AdministrativeHealthcare Liability SimplificationFraud and Reform Abuse 
Electronic data SecurityPrivacyinterchange Security standards: general rules 
Administrative safeguards 
Technical safeguards 
Physical safeguardsTransactions Identifiers Code sets Organizational requirements 
Policies and procedures and
documentation requirements 
 
31 Framework for Implementing the U.S. Medical Records Infrastructure 
2.2.1 Title I: Health Insurance Reform 
Title I sets guidelines and expands access to medical coverage. There were a number of inequities 
that Title I addresses. First, health plans, specifically group plans, can’t deny access to coverage based 
on previous conditions, referred to as pre-existing conditions, and premiums of fellow plan participants 
would remain at similar levels. Second, HIPAA guarantees that when you move between jobs, a compa­

rable level of insurance will be available. Third, when moving from a group to an individual health plan, 
you also can’t be denied for a preexisting condition but premiums can rise: 
A. Increased portability (limiting the use of pre-existing conditions in group health plans) 
B. Special enrollment plans for dependents 
C. Health insurance that must be renewable in small (0–50) and large markets
 
(http://www.ssa.gov/policy/docs/ssb/v60n4/v60n4p18.pdf )
 
2.2.2 Title II: Privacy, Security, Standards, Administrative Simplification 
Privacy, Security, Fraud and Abuse, Medical Simplification, Transactions (see Chapter 5 for more 
details). 
Most of this discussion of HIPAA focuses on Title II since it specifically applies to EHRs. Administrative 
simplification specifies standards for information transactions, privacy guidelines and penalties for

simplification specifies standards for information transactions, privacy guidelines and penalties for 
unauthorized access, and security measures, such as electronic Protected Health Information (ePHI) 
guidelines to ensure patient confidentiality. A National Patient Identifier, a 10-digit identifier recom­
mendation, has yet to be implemented. Title II also outlines exceptions where anonymous medical 
data, where all identifying information is removed, can be used for public healthcare emergencies and 
sanctioned researches. 
Title II contains a number of components that fall into three categories (se e Figure 2.3): 
1. Healthcare fraud and abuse prevention 
2. Medical liability reform 
FIGURE 2.3 Title II, Health and Human Services (HHS).  (From http://www.hhs.gov/ocr/privacy/hipaa/ 
administrative/securityrule/nist80066.pdf.)

32 Biomedical Informatics
 3.  Administrative simplification
 a.	  Privacy
 b.	  Security 
 c.	  Electronic data exchange 
2.2.2.1 Fraud and Abuse Prevention 
This section of Title II was amended in 2000 and is enforced by the Health and Human Services (HHS) 
Office for Civil Rights (www.hhs.gov/ocr/office/news/2000/prprifl.doc). 
There are five components of this section:
 1.  Consumer  control 
 a. 	 Procedures to ensure patients have access to their medical records, to correct mistakes, and 
to advance consent for release of their information, except for public health emergencies, and 
documentation outlining their privacy rights.
 2.  Boundaries 
 a.	  Hospitals and healthcare organizations may not release or use data for nonhealth-related 
activities such as hiring and firing, promotions, or determining premiums for commercial  
products such as life insurance. Data should be used for patient medical care.

products such as life insurance. Data should be used for patient medical care. 
 b.	  Exceptions can be made, with proper authorization, for research with safeguards for remov­
ing patients’ identifying information.
 3.  Accountability 
 a. 	 There are outlined penalties if an individual’s privacy rights are violated; these include disclo­
sure by error, $100 per violation up to limit of $25,000/year; knowingly disclosing information, 
up to $50,000 and up to 1 year in prison; and finally, obtaining information fraudulently, up to 
$250,000 and up to 5 years in prison.
 4. Public responsibility 
 a. 	 There are guidelines to ensure access of medical data for public health emergencies such as 
infectious disease outbreaks; all efforts should be made to obscure individuals’ identity.
 5.  Security 
 a.	  Organizations must do everything possible to secure patient information and establish pro­
cedures and training or face penalties (see accountability for fines).

cedures and training or face penalties (see accountability for fines). 
2.2.2.2  Medical Liability Reform 
Medical liability refers to both the patient’s rights to be compensated for malpractice, i.e., medical injury  
during a procedure or under medical care, and the physician’s costs and responsibilities regarding medical  
liability insurance and possible penalties for nurses and doctors. HIPAA suggests guidelines, but specific  
regulations are currently being dealt with at the state level. Some of the issues are whether patients have  
unlimited rights to sue for pain and suffering contrasted with the cost of physicians to pay for insurance.  
Some specialty’ malpractice insurance may run between $100,000 and $200,000 per year, driving many  
doctors to switch from high-risk specialties. This is an evolving dilemma that will not be resolved soon. 
2.2.2.3 Title II Privacy Rule 
The HIPAA Privacy Rule intent is to safeguard individuals’ health information while traversing the

The HIPAA Privacy Rule intent is to safeguard individuals’ health information while traversing the 
myriad of systems that require access to these data. The scope of the privacy rule includes patient 
records referred to as electronic protected health information (ePHI) dealing with covered entities, i.e., 
healthcare organizations. The privacy rule tenets continue to be amended to address changes in tech­
nology and our understanding of the complexity of sharing medical data to ensure effective healthcare 
delivery.

33 Framework for Implementing the U.S. Medical Records Infrastructure 
Congress created a committee to advise the HHS to provide guidelines on health data and statistics 
to guide national policies; that is, the National Committee on Vital and Health Statistics (NCVHS) 
(http://www.ncvhs.hhs.gov/intro.htm). It originally was created in the 1960s to provide health statistics, 
disease classification, and other medical data standards but was significantly expanded in the 1990s to 
support HIPAA. Its charter was expanded to “form standards for the confidentiality of health informa­
tion required to assure the safety of the shared information.” 
HIPAA Privacy Rule (http://www.hhs.gov/ocr/privacy/hipaa/administrative/privacyrule/index.html). 
The HIPAA Privacy Rule establishes national standards to protect individuals’ medical 
records and other personal health information and applies to health plans, healthcare clear­

inghouses, and those healthcare providers that conduct certain healthcare transactions elec­
tronically. The Rule requires appropriate safeguards to protect the privacy of personal health 
information, and sets limits and conditions on the uses and disclosures that may be made of 
such information without patient authorization. The Rule also gives patients rights over their 
health information, including rights to examine and obtain a copy of their health records, and 
to request corrections. 
A subcommittee of NCVHS on privacy, confidentiality, and security report “Recommendations 
Regarding Sensitive Health Information” can be found at http://www.ncvhs.hhs.gov/101110lt.pdf . 
Figure 2.4 illustrates NCVHS guidelines on privacy for medical records containing genetic information, 
psychotherapy notes, and substance abuse treatments. 
2.2.2.4  HIPAA Security Rule

2.2.2.4  HIPAA Security Rule 
The HIPAA Security Rule focuses on ePHI. It is broken down into (1) administrative, (2) technical, and 
(3) physical components: 
The HIPAA Security Rule establishes national standards to protect individuals’ electronic  protected 
health information (ePHI) that is created, received, used, or maintained by a covered entity. The 
Security Rule requires appropriate administrative, physical and technical safeguards to ensure the 
confidentiality, integrity, and security of electronic protected health information. 
Level II Applications: Implementing HIPAA Title II (Sections 2.2.2.4.1 through 2.2.5) 
2.2.2.4.1 Administrative Safeguards 
The administrative safeguards involve management procedures to analyze an organization’s procedures  
to ensure patient data security as well as analyze potential risk, that is, risk analysis.

to ensure patient data security as well as analyze potential risk, that is, risk analysis. 
The Security Rule defines administrative safeguards as, “administrative actions, and policies and  
procedures, to manage the selection, development, implementation, and maintenance of security 
measures to protect electronic protected health information and to manage the conduct of the 
covered entity’s workforce in relation to the protection of that information.” 
(www.hhs.gov/ocr/privacy/hipaa/administrative/securityrule/index.html) 
2.2.2.4.1.1 Security Management Process
 1.  Risk analysis: The process of identifying potential security risks 
 a.	  Identifying potential security risks and vulnerabilities 
 i.	  How does ePHI flow throughout the organization? This includes ePHI that is created,  
received, maintained, or transmitted by the covered entity. 
 ii. 	 What are the less obvious sources of ePHI? Has the organization considered portable 
devices like PDAs?

34 Biomedical Informatics 
National Committee for Vital and Health Statistics (NCVHS)
Subcommittee on Privacy and Security
Privacy Guidelines
 
Substance abuse treatment
Genetic information Psychotherapy notes Disclosure records
Patient data may be provided,The Federal Genetic Under HIPAA Privacy These regulations prohibit the
without prior approval if usedInformation Non Rule, unlike the rest of the re-disclosure of information
for public health emergenciesDiscrimination Act of 2008 medical record, a healthcare that originated as substance
where identifying(GINA) prohibits employers provider may not disclose  abuse treatment records; the
information obscuredand certain insurers from psychotherapy notes for protections for these records
“requesting, requiring, or treatment, payment, or Rules were updated in 2013 to attach to the record and not
purchasing” genetic healthcare operations without protect PHI for 50 years after the custodian, as under

information an explicit authorization death FINAL RULE of 2013 HIPAA 
Goal (of the final rule) to update: 1. Prohibit the sale of PHI information
-HIPAA privacy and security rules (of 1996) 2. Expand patient rights to request electronic copies of health data
3. Modify rules to ensure school immunization and research-Health Information T echnology for Economic and 4. Incorporate HITECH act enforcement rules to HIPAAClinical Health (HITECH) Act (of 2010) 5. Rules preventing disclosure of genetic information Genetic
http://www.gpo.gov/fdsys/pkg/FR-2013-01-25/pdf/2013-01073/pdf Nondiscrimination Act (GINA) 
FIGURE 2.4 Privacy guidelines (sample) from the National Committee on Vital and Health Statistics source. (From http://www.ncvhs.hhs.gov/1 01110lt.pdf.)

iii. 	 What are the external sources of ePHI? For example, do vendors or consultants create, 
receive, maintain, or transmit ePHI? 
 iv. 	 What are the human, natural, and environmental threats to information systems that 
contain ePHI? 
 b. 	 Determining the probability of occurrence and magnitude of risks
 2.  Risk management 
 a .	  I s  e x e c u t i v e  l e a d e r s h i p  a n d / o r  m a n a g e m e n t  i n v o l v e d  i n  r i s k  m a n a g e m e n t  a n d  m i t i g a t i o n  
decisions? 
 b.	  Are security processes being communicated throughout the organization? 
 c. 	 Does the covered entity need to engage other resources to assist in risk management?
 3.	  Sanction policy 
Apply appropriate sanctions against workforce members who fail to comply with the security  
policies and procedures of the covered entity. 
 a. 	 Does the organization require employees to sign a statement of adherence to security policy

 a. 	 Does the organization require employees to sign a statement of adherence to security policy 
and procedures (e.g., as part of the employee handbook or confidentiality statement) as a pre­
requisite to employment? 
 b. 	 Does the statement of adherence to security policies and procedures state that the workforce 
member acknowledges that violations of security policies and procedures may lead to disci­
plinary action, for example, up to and including termination?
 4. Information system activity review 
Implement procedures to regularly review records of information system activity, such as audit 
logs, access reports, and security incident tracking reports. 
 a.	  What are the audit and activity review functions of the current information systems? 
 b.	  Are the information system functions adequately used and monitored to promote continual 
awareness of information system activity?

b.	  Are the information system functions adequately used and monitored to promote continual 
awareness of information system activity? 
 c.	  What logs or reports are generated by the information systems? 
 d.	  Is there a policy that establishes what reviews will be conducted? 
 e. 	 Is there a procedure that describes specifics of the reviews? 
2.2.2.4.1.2  Assigned Security Responsibility  The intent is to determine who in an organization is respon­
sible to monitor and guarantee that the employees comply with the security rules: 
Identify the security official who is responsible for the development and
 
implementation of the policies and procedures required by this subpart
 
(the Security Rule) for the entity.
 
 1. This requires all covered entities to designate a privacy official. 
 2. The security official and privacy official can be the same person, but necessarily applicable in all 
cases.

2. The security official and privacy official can be the same person, but necessarily applicable in all 
cases. 
 a. 	 Has the organization agreed upon, and clearly identified and documented, the responsibili­
ties of the security official? 
 b.	  How are the roles and responsibilities of the security official crafted to reflect the size, com­
plexity, and technical capabilities of the organization? 
 3. While one individual must be designated as having overall responsibility, other individuals in 
the covered entity may be assigned with specific security responsibilities (e.g., facility security or 
network security). 
35 Framework for Implementing the U.S. Medical Records Infrastructure

36 Biomedical Informatics 
2.2.2.4.1.3 Workforce Security  The organization must assign individuals who have access to ePHI. This 
will include the determination of the levels of access and which computer terminals and systems are to 
be used. This includes auxiliary devices such as flash drives that should contain encryption software and 
security access keys: 
Implement policies and procedures to ensure that all members of its workforce have appropriate access  
to electronic protected health information, as provided under the Information Access Management  
standard and to prevent those workforce members who do not have access under the Information  
Access Management standard from obtaining access to protected electronic health information. 
In workforce security, there are three subspecifications: 
 1.  Authorization and/or supervision 
 a.	  Implement procedures for the authorization and/or supervision of workforce members who

1.  Authorization and/or supervision 
 a.	  Implement procedures for the authorization and/or supervision of workforce members who 
work with electronic protected health information or in locations where it might be accessed. 
 i. 	 Are detailed job descriptions used to determine what level of access to ePHI the person 
holding the position should have? 
 ii. 	 Who has or should have the authority to determine who can access ePHI, e.g., supervisors 
or managers? 
 iii. 	 Are there similar existing processes used for paper records that could be used as an exam­
ple for the ePHI? 
 2.  Workforce clearance procedure 
 a. 	 Implement procedures to determine that the access of a workforce member to electronic pro­
tected health information is appropriate. 
 i. 	 Are there existing procedures for determining that the appropriate workforce members 
have access to the necessary information? 
 ii. 	 Are the procedures used consistently within the organization when determining access

 ii. 	 Are the procedures used consistently within the organization when determining access  
of related workforce job functions?
 3.  Termination procedures 
 a. 	 Implement procedures for terminating access to electronic protected health information 
when the employment of a workforce member ends or as required by determinations made as  
specified in paragraph (a3)(ii)(B) (the Workforce Clearance Procedure). 
(http://www.hhs.gov/ocr/privacy/hipaa/administrative/securityrule/adminsafeguards.pdf) 
 i. 	 Do the termination policies and procedures assign responsibility for removing informa­
tion system and/or physical access? 
 ii. 	 Do the policies and procedures include timely communication of termination actions to 
insure that the termination procedures are appropriately followed? 
2.2.2.4.2 Technical  Safeguards 
Access should only be made for individuals who have a need, to complete their job responsibilities, to 
access ePHI.

access ePHI. 
 1.  Isolating healthcare clearinghouse functions 
 a.	  If a healthcare clearinghouse is part of a larger organization, the clearinghouse must imple­
ment policies and procedures that protect the electronic protected health information. 
 i. 	 Does the larger organization perform healthcare clearinghouse functions? 
 ii. 	 If healthcare clearinghouse functions are performed, are policies and procedures imple­
mented to protect ePHI from the other functions of the larger organization? 
 iii. 	 Are additional technical safeguards needed to separate ePHI in information systems, 
used by the healthcare clearinghouse, to protect against unauthorized access by the larger 
organization?

37 Framework for Implementing the U.S. Medical Records Infrastructure
 2.  Access  authorization 
 a. 	 Implement policies and procedures for granting access to electronic protected health infor­
mation, for example, through access to a workstation, transaction, program, process, or other 
mechanism. 
 i. 	 How is authorization documented? How can it be used to grant access? 
 ii. 	 Are the policies and procedures for granting access consistent with applicable require­
ments of the privacy rule? 
 iii. 	 Have appropriate authorization and clearance procedures, as specified in workforce secu­
rity, been performed prior to granting access? 
 iv. 	 Are access rules specific to applications and business requirements? For example, do dif­
ferent workforce members require different levels of access based on job function? 
 v.	  Is there a technical process in place, such as creating unique user name and an authenti­
cation process, when granting access to a workforce member?

cation process, when granting access to a workforce member? 
 3.  Access establishment and modification 
The organization should create access procedures not only for individuals but for all downstream equip­
ment used to access electronic personal health information (ePHI). 
 1. Implement policies and procedures that, based upon the entity’s access authorization policies, 
establish, document, review, and modify a user’s right of access to a workstation, transaction, 
program, or process. 
 a.	  Are policies and procedures in place for establishing access and modifying access? 
 b. 	 Are system access policies and procedures documented and updated as necessary? 
 c. 	 Do members of management or other workforce members periodically review the list of per­
sons with access to ePHI to ensure they are valid and consistent with those authorized? 
2.2.3 Title III: Tax Simplification Rule 
Tax code changes to generate more revenue to pay for the increased costs of HIPAA implementation.

Tax code changes to generate more revenue to pay for the increased costs of HIPAA implementation. 
Title III discusses financial tax incentives that fall into three categories. Tax deductions for medical  
insurance, medical savings accounts that use pretax dollars, and long-term medical insurance guidelines. 
2.2.4 Title IV: Group Healthcare Guidelines and Enforcement 
Title IV provides more details regarding enforcement for group medical plans to prevent exclusion 
based on pre-existing conditions and continuation of coverage when moving between jobs. 
2.2.5 Title V: Application and Enforcement of Group Health Plans 
Title V includes provisions related to company-owned life insurance and treatment of individuals who lose  
U.S. citizenship for income tax purposes and repeals the financial institution rule to interest allocation rules. 
Company-Owned Life Insurance

Company-Owned Life Insurance 
Deductions are prohibited for interest on loans with respect to company-owned life insurance, includ­
ing company-owned endowment or annuity contracts.  
Treatment of Individuals Who Lose U.S. Citizenship 
Provisions were revised concerning expatriation to avoid taxes, including the following changes: 
(1)  applying the provisions to certain long-term residents, (2) permitting the Treasury Secretary to 
expand the 10-year taxation period to 15 years, (3) increasing the categories of income treated as U.S. 
source income, (4) crediting foreign taxes imposed on U.S. source income, and (5) requiring the filing 
of certain information by expatriates.

Health Information Technology for Economic and Clinical
Health Act (HITECH)
 
Division B: Health Information TechnologyDivision A: Health Information Technology (HIT) Medicare and Medicaid HIT 
Subtitle A:
 
Health Information Technology
 
Improving Healthcare Quality
 
Certified EHR technology
Secure and protected
 
Prevention
 
Standards
 
Enterprise integration
Health information technology policy and 
standards subcommittees
 
Create a national coordinator (ONC) 
Subtitle B: 
Standards Testing 
Provide Funding to support the implementation of EHR’s 
Subtitle D: 
Privacy and Security 
Subtitle A: 
Medicare Incentives 
Improving Healthcare Quality 
Financial incentives for medical professionals 
Financial incentives for hospitals
Medicaid Incentives 
Funding to implement EHR initiatives 
Amendments to Medicare 

Amending regulation
Long term healthcare changes 
  
38 Biomedical Informatics 
Level I: Core Concepts (Continued) 
2.3 American Recovery and Reinvestment Act of 2009
 
The American Reinvestment and Recovery Act (ARRA) passed by Congress in 2009 contained $782 
billion to jumpstart the economy. The ARRA provided $31 billion for healthcare initiatives, of which 
$19.7 billion was earmarked to facilitate the adoption of electronic medical records (EMRs) by the 
healthcare community. It includes the Health Information Technology for Economic and Clinical 
Health (HITECH) Act, which incorporated meaningful use (MU) specifications that became guidelines 
for reimbursement and categorization of the effectiveness of integration of EHRs into their processes 
(http://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS-111hr1enr.pdf ).

(http://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS-111hr1enr.pdf ). 
2.3.1 Health Information Technology for Economic and Clinical Health Act 
In 2009, the HITECH Act, part of the ARRA, was adopted and provided almost $20 billion in  funding 
to help hospitals and physicians make the transition to EHRs and provided $44,000 to $64,000 per 
physician to offset the cost of EHR implementation (Figure 2.5). Hospitals received millions per 
implementation. As part of that effort, MU standards levels 1 to 7 required medical practitioners to doc­
ument the effectiveness of their implementation efforts, and their reimbursement was conditional on 
these levels of compliance of these standards. Further regulations required all medical practitioners to 
implement electronic prescription technologies by 2012 and most hospital and physicians to apply EHRs 
by 2015. A number of healthcare providers such as dentists, optometrists, and mental health physicians

by 2015. A number of healthcare providers such as dentists, optometrists, and mental health physicians 
have more time to implement EHRs. Financial penalties, for example, 1%, 2%, and 3% of reimburse­
ments, would be withheld if these deadlines were not met. 
FIGURE 2.5 Health Information Technology for Economic and Clinical Health provisions.

39 Framework for Implementing the U.S. Medical Records Infrastructure 
2.4 Affordable Care Act 
The ACA was passed in March 2010 and upheld by the Supreme Court in June 2012, often referred to as 
ObamaCare (Table 2.1). 
The following are some key conditions: 
 1. Establish marketplace to compare healthcare plans (2014). 
 2. Acquire lower costs, depending on income, subsidized up to $88,000. 
 3.  Obtain access to Medicaid or the Children’s Health Insurance Program. 
 4. Preexisting conditions will be covered. 
 5.  Remove lifetime medical limits. 
TABLE 2.1 Affordable Care Act Provisions 
Ten Sections of the ACA 
Title I: Quality, Affordable Healthcare for All Americans Subtitle A—Immediate Improvements in Healthcare  
(http://www.hhs.gov/healthcare/rights/law/title/i-quality­ Coverage for All Americans 
affordable-healthcare.pdf) Individuals 
Families 
Subtitle B—Immediate Actions to Preserve and Expand 
Coverage 
Immediate access to insurance for uninsured

Families 
Coverage 
Immediate access to insurance for uninsured 
individuals with a preexisting condition 
Subtitle C—Quality Health Insurance Coverage for All  
Americans 
Health Insurance Market Reforms 
Preservation of right to maintain existing coverage 
Subtitle D—Available Coverage Choices for All Americans 
Establishment of Qualified Health Plans 
Consumer choice 
State flexibility in operation and enforcement of 
Exchanges and related requirements 
Federal program to assist establishment and operation 
of nonprofit, member-run health insurance issuers 
Subtitle E—Affordable Coverage Choices for All Americans 
Premium Tax Credits and Cost-Sharing Reductions 
Eligibility Determinations 
Subtitle F—Shared Responsibility for Healthcare 
Requirement to maintain minimum essential coverage 
Title II: The Role of Public Programs 
Title III: Improving the Quality and Efficiency of Healthcare

Title III: Improving the Quality and Efficiency of Healthcare 
Title IV: Prevention of Chronic Disease and Improving 
Public Health 
Title V: Healthcare Workforce 
Title VI: Transparency and Program Integrity 
Title VII: Improving Access to Innovative Medical Therapies 
Title VIII: Community Living Assistance Services and 
Supports Act (CLASS Act) 
Title IX:  Revenue Provisions 
Title X: Reauthorization of the Indian Healthcare  
Improvement Act 
Source: http://www.hhs.gov/healthcare/rights/law/.

6. Require coverage for dependents up to 26 years of age. 
 7.  Create uniform coverage standards. 
 8. Require coverage of preventive services and immunization. 
 9. Provide assistance for the uninsured. 
 a. Tax credits for individuals with 100% to 400% of the poverty line (up to $88,000) 
 b. Medicaid expansion for those individuals with 130% of the federal poverty line 
 10. Everyone is required to have healthcare coverage by 2014 or pay a small fee. 
 11. Employers with greater than 200 employees must enroll new hires. 
 12. $20 billion in funding to help hospitals and physicians make the transition to EHRs is needed and 
$44,000 to $64,000 is provided per physician to offset the cost of HER implementation. 
 13. MU standards levels 1 to 7 required medical practitioners to document the effectiveness of their 
implementation efforts. 
  (http://www.dpc.senate.gov/healthreformbill/healthbill52.pdf) 
2.4.1 Meaningful Use

2.4.1 Meaningful Use 
The term “meaningful use” was defined by the Centers for Medicare and Medicaid Services (CMS) as a 
series of standards and incentive programs used as criteria for physician reimbursement wherein phy­
sicians are funded between $44,000 and $64,000 and hospitals between $3,000,000 and $5,000,000 to  
offset the costs of implementing EHRs: “The goal of meaningful use was to promote the spread of EHRs 
to improve healthcare in the United States”  (www.healthit.gov). 
CMS specified four general benefits of implementing EHRs: 
 1. Complete and accurate information and history of their patients. Paper patient records were dis­
persed among many providers and tests were often duplicated unnecessarily. 
 2. Better access to information.
 3. Patient empowerment. 
 4. Patients are allowed access to all their medical records and can be part of the decision-making

3. Patient empowerment. 
 4. Patients are allowed access to all their medical records and can be part of the decision-making 
process. Personal data records allow individuals to maintain their own personal copy of their 
medical information. 
The Office of the National Coordinator (ONC) for Health Information Technology, part of the U.S. 
Department of HHS, created a nonprofit Certification Commission for Healthcare Information 
Technology (http://www.cchit.org/) to certify that organizations met meaningful standards (Table 2.2). 
 
Stage 1: Data Capture of Medical 
Information and Sharing among 
Multiple Providers 2011–2012 Stage 2: Advance Clinical Processes 2014 Stage 3: Improved Outcomes 2016 
Electronically capturing health 
information in a standardized format 
Using that information to track key 
clinical conditions 
Communicating that information for 
care coordination processes 
Initiating the reporting of clinical 
quality measures and public health 
information

Using information to engage patients 
and their families 
More rigorous health information 
exchange (HIE) 
Increased requirements for e-prescribing 
and incorporating lab results 
Electronic transmission of patient care 
summaries across multiple settings 
More patient-controlled data 
Improving quality, safety, and 
efficiency, leading to improved 
health outcomes 
Decision support for national 
high-priority conditions 
Patient access to self-management 
tools 
Access to comprehensive patient 
data through patient-centered HIE 
Improving population health 
Source: CMS.gov. 
40 Biomedical Informatics 
TABLE 2.2 Meaningful Use Timetable by the Centers for Medicare and Medicaid Services

TABLE 2.3 Objectives, of Which 19 Have to Be Satisfied to Receive Meaningful Use Funding 
 
14 Core Objectives for Physicians (All Required) 10 Menu Options (Comply with at Least 5) 
1. Use computerized physician order entry for physicians. 
2. I
mplement drug–drug and drug–allergy interaction 
checks.
 
3. Maintain an up-to-date problem list of current active 
diagnoses.
 
4. Keep an active medication list. 
5. Maintain an active medication allergy list. 
6. Record specified demographics on patients. 
7. Record and chart changes in specific vital signs. 
8. Document whether patients age 13 and older are 
smokers.
 
9. Report clinical quality measures. 
10. Implement one clinical decision support rule related to a 
high-priority hospital condition. 
11. Offer patients an electronic copy of their health 
information upon request. 
12. Give patients an electronic copy of their discharge 
instructions upon request. 
13. Have the capability to exchange key clinical information.

13. Have the capability to exchange key clinical information. 
14. Protect electronic health information. 
1. Implement drug formulary checks. 
2. Incorporate clinical lab test results into EHR as 
structured data.
 
3. Generate lists of patients by specific conditions to use for 
quality improvement, reduction of disparities, research, 
and outreach. 
4. Send patient reminders per patient preference for 
preventive follow-up care.
 
5. Provide patients with timely electronic access to their 
health information (including lab results, problem list, 
medication lists, and allergies) within 4 business days of 
the information being available. 
6. Use certified EHR technology to identify patient-specific 
education resources and provide those resources to the 
patient if possible. 
7. The physician who receives a patient from another 
setting of care or provider or believes an encounter is

setting of care or provider or believes an encounter is 
relevant should perform medication reconciliation.
 
8. The physician who transitions patients to another setting 
of care or refers patients should provide a summary of 
care record for each transition. 
9. Capability to submit electronic data to immunization 
registries or immunization information systems and 
submission to applicable law and practice.
 
10. Capability to submit electronic syndrome surveillance 
data to public health agencies and actual submission 
according to applicable law and practice. 
41 Framework for Implementing the U.S. Medical Records Infrastructure 
Meaningful Use Objectives (to Qualify for Incentive Reimbursement Program from ARRA) 
MU has two sets of standards: one for physicians and another for hospitals. Physicians have 24 
objectives, of which 19 have to be met to qualify for EHR reimbursement of implementation costs.

objectives, of which 19 have to be met to qualify for EHR reimbursement of implementation costs. 
Hospitals have 23 MU objectives, 18 of which have to be satisfied. These are further broken down 
into core objectives and a second set of 10 subobjectives from which you have to complete 50% 
(Table 2.3). 
2.5 Summary 
In 1985, the Veterans Administration implemented an EHRs system, under development for a decade. 
This was a rudimentary system by modern standards, but marked the beginning of the U.S. Government’s 
support and funding for this concept. With the emergence of the Internet, that is, the World Wide Web 
in the 1990s, the stage was set via HIPAA to set guidelines for the modern EHR infrastructure. This was 
not a single event; a series of modifications over the next decade culminating with the Final Rule of 2013 
set specific rational implementable standards for transactions between systems including privacy and

42 Biomedical Informatics 
security. In parallel, the ARRA, including the HITECH Act funding, directed $19.7 billion to subsidize 
this effort. Then in 2010, the ACA set guidelines to ensure all citizens had access. 
This is an ever-evolving endeavor but we have established a firm foundation on which to build. 
Note: With the Supreme Court Decisions the fate of the ACA appears to be secure: June 2012. National 
Federation of Independent Business V. Sebelius: Upholds Medicaid expansion and individual mandates. 
June 25, 2015, King et al. V. Burwell: Upholds health insurance subsidies. 
Questions 
Level I 
 1. What is HIPAA and what in general was it supposed to accomplish? 
 a. 	 What are the five components/titles of HIPAA? Briefly summarize their objectives (some 
information is in Level II sections of this chapter). 
 b.	  What led up to HIPAA prior to 1996 (research on the web)? 
 2. What is ARRA? Explain its objectives relative to EHRs. 
 a. 	 What is the HITECH Act?

2. What is ARRA? Explain its objectives relative to EHRs. 
 a. 	 What is the HITECH Act? 
 3. Explain the ACA. 
 a.	  List at least five key components that you believe are relevant to EHRs.  Why? 
 4. Explain the function of MU standards. Why was it created? 
 a.	  What are the differences between hospital and physician MU standards, and why are they not 
the same objectives? 
 b. 	 What are the penalties of not reaching MU standards (research on web)? 
 5.  How do HIPAA and NCVHS overlap in their objectives? 
Level II 
 6. Why is HIPAA Title II the most detailed of the five components of HIPAA? 
 a. 	 Explain the function of HIPAA Title II Privacy Rule in detail. 
 b. 	 Explain the function of HIPAA Title II Security Rule in detail. 
 7.  HIPAA describes detailed security management procedures to protect personal health informa­
tion (PHI). Explain these management guidelines and why they were implemented.
 a.	  Risk  analysis
 b.	  Risk  management

 b.	  Risk  management 
 c. 	 Sanctions: Be specific on the sanctions and penalties. The details can be found in Chapter 5.
 d.	  Technical  safeguards 
Glossary 
Affordable Care Act (ACA):  Passed in March 2010 and upheld by the Supreme Court in June 2012, 
which is often referred to as ObamaCare. 
American Reinvestment and Recovery Act (ARRA):  Passed by Congress in 2009, containing $782 bil­
lion to jump-start the economy and 20 billion targeted at promoting EHRs. 
Electronic health record (EHR)*:  A  c o ll e cti o n  o f  h e al th  da ta  fr o m  m ul ti p l e  s o ur c e s .  Thi s  i s  a  more  
expansive term  than electronic medical record and refers to all information of the health of the 
body. It is designed to share information among providers and includes all laboratory infor­
mation and specialist data (used almost exclusively by the Office of the National Coordinator

mation and specialist data (used almost exclusively by the Office of the National Coordinator 
[ONC] for health information).

43 Framework for Implementing the U.S. Medical Records Infrastructure 
Electronic medical record (EMR): Used for diagnosis and treatment, which refers to medical treatment 
and history and is a digital form of a medical chart and often refers to information gathered in 
a local practice (it is often used but electronic health record is the preferred term). 
Electronic protected health information (ePHI):  Guidelines to ensure patient confidentiality. 
Health Insurance Portability and Accountability Act (HIPAA) of 1996, Required HHS to develop 
standards for electronic health records (EHRs), data interchange, security, and unique EHR. 
HIPAA Privacy Rule: Establishes national standards to protect individuals’ medical records and other 
personal health information and applies to health plans, healthcare clearinghouses, and those 
healthcare providers that conduct certain healthcare transactions electronically.

healthcare providers that conduct certain healthcare transactions electronically. 
HIPAA Security Rule: Establishes national standards to protect individuals’ electronic protected health 
information that is created, received, used, or maintained by a covered entity. 
Health Information Technology for Economic and Clinical Health Act (HITECH):  In 2009, the 
HITECH Act, part of the ARRA, was adopted and provided almost $20 billion in funding to 
help ho
spitals and physicians make the transition to EHRs. 
Meaningful use:  Defined by the CMS as a series of standards and incentive programs used as criteria  
for physician reimbursement. 
References 
 1. Affordable Care Act, http://www.hhs.gov/healthcare/facts/timeline/, 2010. 
 2.  American Recovery and Reinvestment Act, http://www.treasury.gov/initiatives/recovery/Pages/ 
recovery-act.aspx, 2009.
 3.  HIPAA,  http://www.hhs.gov/ocr/privacy/hipaa/administrative/.

 3.  HIPAA,  http://www.hhs.gov/ocr/privacy/hipaa/administrative/. 
 4.  HITECH ACT, http://www.healthit.gov/policy-researchers-implementers/hitech-act, 2009. 
 5. Veterans Health Information Systems and Technology Architecture (VistA), http://www.ehealth. 
va.gov/VistA.asp, 1985.

Level I: Core Concepts ...................................................................................46
 
3.1 	 Introduction ........................................................................................46
 
3.2 	 History ..................................................................................................46
 
3.3 	 Electronic Health Records .................................................................49
 
EHR Taxonomy • EHR Architecture • EHR Adoption Statistics
 
3.4 	 Data .......................................................................................................59
 
EHR Data Entry
 
3.5 	 U.S. Initiatives .....................................................................................60
 
HIPAA • American Recovery and Reinvestment Act • Meaningful 
Use • E-Prescribing 
3.6 	 Health Information Exchanges ........................................................66
 
Three Types of Health Information Exchange

Level II: EHR Applications ............................................................................68
 
3.7 	 Navigating an Electronic Health Record ........................................68
 
Central Console • Patient List • Demographics • Navigator • Medication
 
Administration Record • Orders • Discharge Orders
 
Level III: Advanced Topics: Decision Support Systems, Expert Systems ...71
 
3.8 	 Clinical Decision Support System .................................................... 71
 
HL7 Decision Support Services • Pharmacy Decision Support Systems
 
3.9 	 Expert Systems ....................................................................................75
 
Inference Engine
 
3.10 Summary ..............................................................................................76

Questions .........................................................................................................76
 
Glossary ...........................................................................................................77
 
References ........................................................................................................79
 
3 
Electronic Health Records
 
45

46 Biomedical Informatics 
3.1 Introduction
 
Electronic health records (EHRs) began as an aggregate of discrete data accumulated from various 
sources which were integrated into a seamless narrative that documented a patient’s journey through 
the healthcare system. The newer generation of EHRs incorporate real-time dynamic data from mobile 
sensors, telehealth, external and implanted sensors. Prototype watches and medical sensors woven into 
clothing began to appear in 2013 and are becoming more mainstream and this data will begin to be incor­
porated into EHRs. System analysis techniques utilized in other engineering disciplines will add to the 
dynamic predictive analysis in medical records providing probabilities of potential acute conditions such 
as a stroke or heart attack and possible immune responses that may be affected by stress and pollution 
in the environmen t. The field of epigenomics will also benefit from the additional data p rovided from

in the environmen t. The field of epigenomics will also benefit from the additional data p rovided from 
dynamic medical data, where external factors can affect gene expression and regulation, i.e., the probabil­
ity of developing a specific cancer. Inheriting a trait from DNA is only one of many factors that determine 
susceptibility to developing serious diseases. We are on the cusp of a revolution that will bring healthcare 
parity with other engineering advances by creating a systems approach to healthcare (Figure 3.1). 
3.2 History 
In the 1960s when large mainframe computers began to proliferate, a number of EHR pilots appeared 
(Figure 3.2). Physician Lawrence Weed developed an EHR framework, the University of Vermont 
PROMISE project, a joint effort by Akron Children’s Hospital and International Business Machines 
Corporation (IBM) utilizing an IBM 305 tube-based mainframe with a 5 mb storage capacity.

Corporation (IBM) utilizing an IBM 305 tube-based mainframe with a 5 mb storage capacity. 
In the mid-1960s, the National Library of Medicine began providing an online indexing of biomedi­
cal literature originally called Medicus and later Medline. By the early 1970s, the Veterans Affairs (VA) 
began investing in an EHR system called VistaA. Ten years later, the system went public and was used 
at VA facilities worldwide. An open-source version of VistaA is available to hospitals; details can be 
found at www.WorldVistA.org.[9]. In the 1970s, the Regenstreif Institute [7], affiliated with the Indiana 
University School of Medicine, developed one of the first EHRs, but at this early stage, few physicians 
adopted the technology. With the two major technological advances, namely; the emergence of the PCs 
in 1981 and the web/Internet in 1990, Tim Berners-Lee created the first practical implementation of the

in 1981 and the web/Internet in 1990, Tim Berners-Lee created the first practical implementation of the 
web, at the Conseil Européen pour la Recherche Nucléaire (CERN) [1] at the super collider facility, which 
spurred the ability to share data ubiquitously, the scene was set for the emergence of EHRs. A number 
of commercial systems appeared in the mid-1990s such as Eclipsys, Clinitec, and others. In 1996, a 
turning point for the U.S. medical records efforts began with the Health Insurance Portability and 
Accountability Act (HIPAA). It was initially created to provide standards for submitting online medi­
cal claims, but later evolved incorporating the HIPAA Title II security framework and guidelines for a 
national EHR system. In 2009, the Health Information Technology for Economic and Clinical Health 
(HITECH) Act was adopted, part of the ARRA, which provided $19.7 billion in funding to help hospitals

(HITECH) Act was adopted, part of the ARRA, which provided $19.7 billion in funding to help hospitals 
and physicians make the transition to EHRs. The HITECH Act provided $44,000 to $64,000 per physi­
cian to offset the costs of EHR implementation for millions for hospitals for EHR implementation. As 
part of that effort, meaningful use standards levels 1 to 7 required medical practitioners to document the 
effectiveness of their implementation efforts, and their reimbursement was conditional on these levels 
of compliance of these standards. Further regulations required all medical practitioners to implement 
electronic prescription technologies by 2012 and most hospital and physicians to utilize EHRs by 2015. 
A number of healthcare providers, dentists, optometrists, and providers of mental health services have 
more time to implement EHRs. Financial penalties  of between 1%–3% of Medicare and Medicaid reim­
bursements would be withheld if these deadlines were not met.

Electronic Health Records (EHR) 
Lubliner 2015
Office of the Personal Data
Architecture 
Interoperability Standards National Coordinator Records Implementation
(ONC) EHR Spec. (PDR) 
Health Meaningful UseHL 7 RIM Models InformationContinuity of Exchanges -HL 7 -DICOMCare Record (HIE) -ISO -ICD10(CCR) -IEEE -SNOMED
-FHIR -LOINCArden Syntax DSS Data Entry Forms HITECH Affordable-CDA -CPT
EHR-System
HIPAA Act Care Act
Tools UMLSFunctional Models 
SecurityFunctions Patient Care RelationshipPrivacy Hierarchy Expert Systems
Diagram 
Clinical Decision SupportQuery ConsumerDirected Mediated Systems (CDSS) Based 
 
47 Electronic Health Records 
FIGURE  3.1 (See color insert.) Electronic health records.

Lubliner2015 
1947(8) 1961(2) 1965 1971 1976 1981 1987(8) 1990 1995 1996 2009 2010 
IBMPC model AffordableISO (1947) HIMSS National VistaA Release of Internet/ Several HIPAA, ARRA
5150, PCDOS Care Act(International (1961) Library of Veterans Veterans WWW Tim software Health stimulus
1.0, 256K (ACA)Standards formerly Medicine Administration Administration Berners-Lee companies Insurance bill and
RAM, first Obama care Organization) HMSS (NLM), index (VA) health health data www3. org release Portability HITECH
mass produced repository Act MEDICUS later data repository and web EHR ’s andICD (1948) personal
International 1962 called (Development browsers Clinitec, Accountability
Akron computer, HL7 Org.Classification MEDLINE initiated) Explorer and Eclypsis Act
 
Children ΄s Apple  created
of Diseases Navigator
Hospital SNOMED-CT preceded it but
maintained by 1976 emerge and (SNOP earlier limited 1988 AMIA
WHO (World EFMI

IBM version) European distribution AmericanHealth Patient IHTSDO’s 27 Federation of MedicalOrganization) Inform. international Medical Informatics
System Association
 members Informatics
 
administers
SNOMED-CT
 
48 
FIGURE  3.2 Timeline of electronic medical records. 

49 Electronic Health Records 
3.3 Electronic Health Records 
An EHR is a collection of health data from m ultiple sources. This is a more expansive term than an 
electronic medical record (EMR) and refers to all patient information acquired. It is designed to share 
information among medical providers and has the ability to track populations and potential spread of 
infectious diseases. It includes all laboratory information and specialist data. The EHR term is used 
almost exclusively by the Office of the National Coordinator (ONC) for Health Information. 
An EHR is an integrated medical view of a patient that accesses modules available in Integrated Health 
Information System (Figure 3.5). These modules may be located either in a central repository, hospital or 
C l o u d - b as e d,  o r  m o r e  lik e l y  in  a  n um b e r  o f  da ta b as es  g e o gra p hi call y  di s p e r s e d.  Thi s  fragm e n t e d  p a ti e n t

record in theory can be accessed by health information exchanges (HIEs), Section 3.3, which are government-
supported systems, at least one per state, that eventually will have the ability to convert EHR data from mul­
tiple vendors. In 2010, the ONC for Health Information awarded grants to 56 states and territories to support 
fir s t  r e gi o n al  an d  l a t e r  an  in t e gr a t e d  n a ti o n al  H IE  n e tw o r k.  G r an t s  r an g e d  fr o m  $ 6 0 0 , 0 0 0  f o r  Am e ri can 
Samoa to $28 million to Texas Health and Human Services (HHS) Commission. (A complete grant list is 
available at  http://www.healthit.gov/policy-researchers-implementers/state-healthinformation-exchange.) 
EHRs are a synthesis of static data acquired during medical visits and procedures integrated with 
more dynamic data from wireless and mobile medical devices. A new generation of mobile wearable

more dynamic data from wireless and mobile medical devices. A new generation of mobile wearable 
sensors that can track the stimuli and stresses in daily life connected into Smart phones and tablets 
will provide valuable insights into triggers that might create acute responses, providing a more com­
prehensive view of patients that were never available in printed medical records. In many engineering 
disciplines, we study forces and loads of systems under min/max conditions. Heart attacks and stroke 
prediction will benefit from real-time analysis of data. Drug absorption and effectiveness may also be 
dependent of dynamic metabolic effects during daily activities. 
EHRs will continue to evolve incorporating lifestyle choices, i.e., data that may add to a better picture 
of the overall human system. Data collected during personal encounters, work interactions, eating habits, 
environmental exposures commuting to work, sun exposure, etc., will add to a dynamic view of patient

environmental exposures commuting to work, sun exposure, etc., will add to a dynamic view of patient 
health. National Science Foundation–funded studies are currently under way to evaluate the effectiveness 
and preventive benefits of wireless medical devices. A national center for wireless health at University of 
California, Los Angeles (http://www.wirelesshealth.ucla.edu/) is a good source of current research, and in 
addition, a global nonprofit organization, the Wireless-Life Sciences Alliance, connects innovators, glob­
ally relevant companies, scientists, physicians, and policy makers (www.wirelesslifesciences.org). Better 
methods of visualizing medical data will also enable both healthcare professionals and individuals, utiliz­
ing personal data records, a better view of changes over time contributing to illness. 
A universal national patient ID has yet to be realized, but EHRs associated with a particular hospital/

A universal national patient ID has yet to be realized, but EHRs associated with a particular hospital/ 
medical software vendor assigns a tracking ID. Sometimes, it’s an algorithm based on Social Security, 
birth date, age, hospital system, or possibly it’s simply the next in sequence. Other key searchable fields 
are secondary identifiers such as Social Security, birth date, and age. 
3.3.1 EHR Taxonomy 
There are three general categories; EHRs, Continuity of Care Records (CCRs), and Personal Health 
Records (PHR). Each provides unique data relevant for different medical situations. The key to these 
EHRs is interoperability, the ability to share and exchange data. They incorporate features that ben­
efit individuals, healthcare organizations, and governmental agencies, such as the Centers for Disease 
Control and Prevention (CDC), to ensure the health of the population at large. The enactment of laws

Control and Prevention (CDC), to ensure the health of the population at large. The enactment of laws 
such as HIPAA in 1996 and funding initiatives of the American Recovery and Reinvestment Act (ARRA) 
in 2009 were designed to ensure these interoperability, privacy, and security objectives. 
The term EMR is used primarily for diagnosis and treatment. It refers to medical treatment and his­
tory and is a digital form of a medical chart and often refers to information gathered in a local practice.

50 Biomedical Informatics 
(EHR is the preferred and the more expansive term.) CCR refers to a subset of medical information 
focused on timely care of an individual either in an emergency situation or provided to another physi­
cian focusing on current health status, medications, and treatment. 
3.3.1.1 Personal Health Record 
A PHR is medical information in possession of an individual patient or a patient’s nonprofessional 
caregiver , such as a home aid. The format may be either paper documents, electronic media, or a 
combination. The sources of the information include patient-generated lists, copies of reports from 
physicians, hospitals and labs, legal documents such as living wills and healthcare proxy forms, 
and insurance statements. Organizations such as the American Health Information Management 
Association (AHIMA) encourage individuals to keep their own complete PHR, including any

Association (AHIMA) encourage individuals to keep their own complete PHR, including any 
information that a doctor may not have, such as exercise routines, dietary habits, herbal or nonpre­
scription medications, or results of home testing such as home blood pressure or sugar readings. 
Consumers can purchase PHRs software for their PC or in the Cloud. According to AHIMA, 42% 
of U.S. adults surveyed said they keep some form of a PHR. PHR is also available free of cost from 
several Internet sites (Figure 3.3). 
FIGURE  3.3  Provider dispute resolutions example provided by Blue Cross and Blue Shield contains conditions, 
medications, and in- and outpatient visits.

51 Electronic Health Records 
Definition: 
(HHS.gov)  “A PHR is an electronic record of an individual’s health information by which the individual  
controls access to the information and may have the ability to manage, track, and participate in his or 
her own healthcare.” 
http://www.hhs.gov/ocr/privacy/hipaa/understanding/special/healthit/phrs.pdf. 
PHR usually includes 
 1.  Longitudinal health history
 2.  Medical diagnoses
 3.  Medications
 4. Test  results 
 5. Location to keep family medical histories 
 6.  Emergency contact numbers 
 7. Keep track of appointments 
 8. Location to track other family members for whom they are responsible 
Benefits: 
 1. Manage their own health records 
 2. Control who has access to this information 
 3.  Able to monitor medical records and correct errors 
 4. Facilitate treatment for emergencies away from the healthcare providers

3.  Able to monitor medical records and correct errors 
 4. Facilitate treatment for emergencies away from the healthcare providers 
 5 .  D a t a  s h ar in g :  M o s t  p r o vi d e r  di s p u t e  r e s o l u ti o n s  ( P D Rs )  h a v e  an  o p ti o n  o f  a d din g  o r  d e l e tin g  
users’ access 
Types of PHRs: 
 1.  Provided by healthcare p rovider fall under HIP AA  Privacy Rule  (provided by  covered entities:  
known as protected health information [PHI]). The privacy rule  allows individuals to view and 
obtain a copy of their health information including  billing, medical records, claims, and other 
information used for treatment  decisions (Table 3.1). 
 a.	  Provided by healthcare plans or providers 
 b. 	 Usually a subset of their larger health record 
 c. 	 Read only, can’t update information 
 d. 	 Control of access, family members, etc. 
 e.	  Not always complete but users have the right to request information  from other providers to 
be added to this PHR

e.	  Not always complete but users have the right to request information  from other providers to 
be added to this PHR 
 f. 	 Disclosure requires users written consent except in the case where it is  used to provide medi­
cal services 
TABLE 3.1 HIPAA Privacy Rule Entities 
Healthcare Providers Health Plans Healthcare Clearinghouses 
Clinics Company health plans Billing services 
Chiropractors Health maintenance organizations Community health management 
Doctors Long-term care insurers Repricing companies 
Dentists Medical, dental, vision plans Value-added networks 
Nursing homes Medicare and Medicaid 
Pharmacies Medicare choice and supplement 
Psychologists Veterans’ health plans

2.  Third-party PHR software not covered under HIPAA 
 a.	  Third-party company, not a health plan, clearinghouse, or provider, is not  bound by HIPAA 
requirement. 
 b.	  A few third-party providers who say they are HIPAA compliant are  legally required to follow  
privacy rules. 
Covered entity (under HIPAA privacy rule) “refers to three specific groups, including health plans, health-
care clearinghouses, and healthcare providers that transmit health information electronically”  (http:// 
www.hrsa.gov/healthit/toolbox/HealthITAdoptiontoolbox/PrivacyandSecurity/entityhipaa.html). 
A sample PDR is provided by Blue Cross and Blue Shield (http://www.bcbs.com/healthcare-partners/ 
personal-health-records/consumer-personal-health-record.html). 
3.3.1.2 Continuity of Care Record 
The CCR is a core data set of the most relevant and timely facts about a patient’s healthcare . It is to be

The CCR is a core data set of the most relevant and timely facts about a patient’s healthcare . It is to be 
prepared by a practitioner at the conclusion of a healthcare encounter in order to enable the next prac­
titioner to readily access such information. It includes a summary of the patient’s health status (e.g., 
problems, medications, allergies) and basic information about insurance, advance directives, care docu­
mentation, and care plan recommendations. It also includes identifying information and the purpose 
of the CCR. The CCR may be prepared, displayed, and transmitted on paper or electronically, provided 
the information required by this standard specification is included. However, for maximum utility, the 
CCR should be prepared in a structured electronic format that is interchangeable among EHR systems. 
T o ensure interchangeability of electronic CCRs, this standard specifies that XML coding is required

T o ensure interchangeability of electronic CCRs, this standard specifies that XML coding is required  
when the CCR is created in a structured electronic format. XML coding provides flexibility that will 
allow users to prepare, transmit, and view the CCR in multiple ways, e.g., in a browser, as an element in 
an Health Level 7 (HL7) message or Clinical Document Architecture (CDA) compliant document,  in a  
secure email, as a PDF file, as an HTML file, or as a word processing document. It will further permit  
users to display the fields of the CCR in multiple formats. Equally important, it will allow the inter­
change of the CCR data between otherwise incompatible EHR systems. 
“The Continuity of Care Record (CCR) was developed in order to facilitate the transfer of health informa­
tion among healthcare providers when patients transition from one healthcare setting to the next” (http://

tion among healthcare providers when patients transition from one healthcare setting to the next” (http:// 
www.hrsa.gov/healthit/toolbox/HealthITAdoptiontoolbox/PersonalHealthRecords/aboutccr.html). 
CCR features 
 1. Clinical summary of a patient’s healthcare status (XML based)
 a.	  Advanced  directives
 b.	  Care  plan
 c.	  Care  documentation
 1.	  Vital signs
 2.	  Problems 
 3.	  Medications, immunizations, allergies
 4. 	 Procedures
 5.	  Family  history
 6.	  Medical  encounters 
52 Biomedical Informatics

53 Electronic Health Records 
d. Insurance information (payers)
 e. Identifying data 
f. Improve healthcare interoperability 
2. Used for transferring care between multiple healthcare providers 
Standards 
In 2007, American National Standard Institute (ANSI) (www.ansi.org) created a standard for 
Continuity of Care Documents using HL7 (www.HL7.org) (see Chapter 4). It utilizes the Clinical 
Architecture (CDA) and data defined by ASTM CCR and is compatible with the Integrating Healthcare 
Environment (IHE) designed to share information between systems. 
The HL7 Reference Information Model (RIM) is an object model that provides a visual representa­
tion of HL7 clinical data domains. It identifies the life cycle of message groups that are moved between 
domains of the model. The blocks for patient encounter, observation, procedure, etc., include fields that 
indicate relationships between  domains (Figure 3.4). 
3.3.2 EHR Architecture

3.3.2 EHR Architecture 
There are a number of U.S. and international guidelines for the EHR architectures. The goals are not simply 
the comprehensiveness of the patient information, the categories are clinical, ethical, legal, secure, and allow 
for data analysis, but conform to international standards; International Classification of Diseases (ICD10), 
D i g i t a l  I m a g i n g  a n d  C o m m u n i c a t i o n s  i n  M e d i c i n e  ( D I C O M ) ,  S y s t e m i z e d  N o m e n c l a t u r e  o f  M e d i c i n e 
Clinical Terms (SNOMED CT), etc., which allow for communication between multiple EHR vendors both 
nationally and internationally and HL7 for standard communications protocols (Chapter 4). 
The principal purpose of EHRs is the clinical care of patients. It’s a central repository of information from

The principal purpose of EHRs is the clinical care of patients. It’s a central repository of information from 
not only medical personnel but data from labs, medical scans, personal histories, etc., that can create a holistic 
view of the patient and can prevent duplicate unnecessary tests. Once all other practitioners have transitioned 
to EHRs such as dentists, optometrists, and mental healthcare workers, the interrelated complex medical 
factors contributing to a disease can be fully appreciated. Correlations can be missed by an incomplete medi­
cal record, an example of which is periodontal disease that has been shown to be a factor in heart disease, 
specifically inflammation in the gums and arteriosclerosis and its relationship to the inflammatory process 
in arteries. Intelligent software can correlate these diverse factors and can suggest treatments that might be 
missed. Finally, errors due to incomplete data and patients’ misidentification create thousands of patient

missed. Finally, errors due to incomplete data and patients’ misidentification create thousands of patient 
injuries a year that can be reduced using EHRs. The benefits far outweigh cost and additional labor entering 
patient data. 
The International Organization for Standardization (ISO) ( http://www.iso.org/iso/home.html ) is 
a federated group of organizational standards for organization management, environment, energy, 
food, and healthcare. The ISO standard 18308:2011 (EN) defines the architecture, services, and com­
munication standards for EHRs and their term “shared health records.” It also follows the Open 
Distributed Processing Model ISO/International Electrotechnical Commission (IEC) 10746–1. The 
IEC is a French nonprofit standards organization. Its definition summary states that ( https://www. 
iso.org/obp/ui/#iso:std:iso:18308:ed-1:v1:en) “one or more repositories, physically or virtually inte­

grated, of information in computer processable form, relevant to the wellness, health and healthcare 
of an individual, capable of being stored and communicated securely and of being accessible by mul­
tiple authorized users, represented according to a standardized or commonly agreed logical informa­
tion model. Its primary purpose is the support of life-long, effective, high quality and safe integrated 
healthcare.” 
The ISO standards do not simply discuss technical guidelines but include a broader definition of 
wellness and complimentary services, “alternative medicine.” This includes herbal remedies and other 
nonwestern medicine. 
Another organization that began in the United States in 1987 but quickly expanded to a global reach 
was HL7 (http://www.hl7.org/). The term HL7 came from the ISO seven-layer communication model for

54 Biomedical Informatics 
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55 Electronic Health Records 
Open System Interconnection. It’s an international organization for the interoperability of health informa­
tion technology (HIT). The organization includes thousands of medical practitioners and over 500 major 
healthcare companies who regularly meet to discuss HIT standards and ensure these standards are inte­
grated into their products. Their website is an excellent source of database and architectural models. A joint 
medical record specification is ISO/HL7 10781, a synthesis of the work of both these standards organizations. 
3.3.2.1 EHR Model 
The core of any EHR system is built around interoperability standards, i.e., a series of terms, data 
structures, and libraries all protected by a security layer. So the EHR model (Figure 3.5) begins with a 
privacy/security layer defined by HIPAA Title II. The next core layer are the libraries that incorporate 
international naming conventions such as ICD10 and DICOM that allow interoperability of EHRs, i.e.,

international naming conventions such as ICD10 and DICOM that allow interoperability of EHRs, i.e., 
to allow multiple vendors and systems to seamlessly communicate. 
The next core component is documentation by medical practitioners—inpatient hospital services such 
as doctors, nurses, and external providers specialists in medical practices and medications. An intelli­
gent layer of software, clinical decision support systems (CDSS), provides intelligence to help the medi­
cal practitioner. It can be as simple as workflow analysis, for example, steps that have to be completed 
during discharge of patients. Others involve medication tracking, alerts to ensure dosage, and allergies 
and drug interactions to provide patient safety. 
All these layers are connected, via a network, to internal and external EHR components such as radi­
ology, pharmacies, and laboratories. This complex system of interconnected medical records provide a

ology, pharmacies, and laboratories. This complex system of interconnected medical records provide a 
single point of care record, very different from the past where very few doctors had a complete integrated 
view of patient care. Since these systems may be part of different EHR systems, Health Information 
Exchanges (HIEs) are being developed, funded by the federal government, to convert data between 
multiple EHR vendors so systems and databases can exchange data (Figure 3.5). 
Network 
Network 
Core architecture (EHR) 
Task 3: Privacy/security
HIPAA title II: preventing fraud and abuse 
Task 2: Claims transactions and code set rules 
(SNOMED, ICD10, DICOM) 
Task 1: Data Interoperability 
HIPAATitle I: Healthcare Access and Portability 
Documentation 
system 
Clinical decision 
support system 
Patient 
tracking modules 
Closed loop
medication tracking 
External facilities 
Assisted living
facilities 
Tertiary care
Nursing
documentation 
Physicians
documentation

Nursing
External providers 
Medical practices 
External 
pharmacies
Privacy rule: It established regulations for the use and disclosure of
Protected Health Information (PHI)
Digital Signatures: Biometric Access devices 
EDI Healthcare Claims and Transactions set 837 
EDI Healthcare Claim Payment/Advice Transaction Set 835 
EDI Retail Pharmacy Claim transactions NCPDP
Telecommunications Standard version 5.1 
PharmaciesLaboratories Radiology 
FIGURE  3.5 Electronic health record architecture.

TABLE 3.2 Office of the National Coordinator for Health Information Technology Electronic Health Record  
Standards Final Rule 2014 
 
Security end-user devices. 
Adopted a new certification criterion that would require EHR technology to be able to support 
corrections and amendments to a patient record. 
A new certification criterion that enables secure messaging between a provider and a patient. 
Adopted a new certification criterion that permits a patient to securely view, download, and 
electronically transmit his or her health information, including the ability to track the use of these 
patient capabilities. 
Interoperability In many instances, certification criteria reference single vocabulary and context exchange standards for 
recording and representing clinical health information for use during electronic health information exchange. 
Adopted transport standards for the exchange of transitions of care/referral summaries as well as the

Adopted transport standards for the exchange of transitions of care/referral summaries as well as the 
transmission of patient summaries as part of the view, download, and transmit to a third-party 
certification criterion. 
The “transitions of care” certification criterion focused on receipt was revised to include the display of 
previously adopted summary care record standards, Continuity of Care Document/C32 and Continuity 
of Care Record, providing a form of backward compatibility. 
The test procedure for the transitions of care/referral certification criteria is expected to ascertain 
electronic health record (EHR) technology’s ability to engage in standard-based exchange with any 
other EHR technology that has also implemented the adopted transport standards. 
Data Adopted a new certification criterion that will enable providers to create a set of “patient summaries. ” In

Data Adopted a new certification criterion that will enable providers to create a set of “patient summaries. ” In 
Portability the event provider switches EHR technology, this capability will help prevent the need to manually 
reenter basic patient information into the new EHR. 
Safety and Adopted two new certification criteria related to patient safety—one that focuses on the application of 
Usability user-centered design to medication-related certification criteria and another that focuses on the quality 
management system used during the EHR technology design. 
Source: ONC Specification, http://www.healthit.gov/sites/default/files/pdf/ONC_FS_EHR_Stage_2_Final_082312.pdf. 
56 Biomedical Informatics 
3.3.2.2 EHR System Specifications 
EHRs are an integrated system of information sources that tie together patient information as they 
travel through the healthcare system. Diagnostic testing, medical specialists, medications, in- and

travel through the healthcare system. Diagnostic testing, medical specialists, medications, in- and 
outpatient services that span a lifetime are aggregated. The challenge is to present and visualize these 
data as a continuum rather than discrete events. A graph that tracks similar vital signs, for example, 
blood pressure, cholesterol, and glucose, over the years overlaid with medications can simplify diag­
noses. An integrated EHR specification linking diverse data resources is critical to provide an inte­
grated medical record. 
In 2014, the ONC for Health Information Technology (http://www.healthit.gov/newsroom/ 
about-onc) released the “ONC Fact Sheet: 2014 Edition Standards & Certification Criteria 
(S&CC) Final Rule” for standards for implementing EHRs. It is in conjunction with the Center 
for Medicare and Medicaid Services (CMS) incentive programs. The ONC-stated goals for this 
specification was to “promote patient safety and patient engagement; enhance EHR technology’s

specification was to “promote patient safety and patient engagement; enhance EHR technology’s 
interoperability, electronic HIE capacity, public health reporting, and security; enable clinical 
quality measure data capture, calculation, and electronic submission to CMS or States; and intro­
duce greater transparency and efficiency to the certification process” (https://www.federalregister. 
gov/ articles/2012/09/04/2012–20982/health-information-technology-standards-implementation­
specifications-and-certification-criteria-for). 
This 2014 ONC specification provides enhanced privacy–security, interoperability, and data interop­
erability between systems (Table 3.2). 
EHR Systems (EHR-S) Functional Model Release 2 (2014) “outlines important features and functions 
that should be contained in an EHR system. Through the creation of functional profiles, this model pro­
vides a standard description and common understanding of functions for healthcare settings. To date,

vides a standard description and common understanding of functions for healthcare settings. To date, 
Privacy and Adopted a certification criterion that focuses on the encryption of health information if it is stored on

Care Providers (functions) Patient Care 
Example child functions: 
Research and Public Health Administrative and Financial 
Example child functions:Example child functions: 
Trust Infrastructure 
Records Infrastructure 
 
57 Electronic Health Records 
FIGURE  3.6  Health Level 7 electronic health record system Functional Model standards. (http://www.hl7. 
org/documentcenter/public_temp_1A89AEE6–1C23-BA17–0CBBF529101474E6/calendarofevents/himss/2012/ 
Electronic%20Health%20Record%20System%20Functional%20Model%20R2.pdf.) 
HL7 has developed or is developing profiles for areas such as child health, emergency care, long-term 
care, behavioral health and vital statistic reporting” (HL7.org definition). 
A number of standards organizations, HL7, the ISO, and Healthcare Information Management 
Systems Society (HIMSS), in 2012 issued the “HL7 EHR System Functional Model and Standard (ISO/

Systems Society (HIMSS), in 2012 issued the “HL7 EHR System Functional Model and Standard (ISO/ 
HL7 10781), Release 2” specifications for EHR-S (Figure 3.6). Its goal was to create a standard frame­
work for EHR design (http://www.hl7.org/documentcenter/public_temp_1A89AEE6–1C23-BA17– 
0CBBF529101474E6/calendarofevents/himss/2012/Electronic%20 Health%20Record%20System%20 
Functional%20Model%20R2.pdf.). 
HL7’s primary focus are standards for communication of medical data between systems but they also 
provide modeling standards such as EHR-S and a decision support framework Arden. (See Chapter 4 
on interoperability.) Definition: HL7 refers to a set of international standards for transfer of clinical and 
administrative data between hospital information systems (www.HL7.org). 
3.3.3 EHR Adoption Statistics 
The growth rate of EHRs, as reported by the CDC in January 2014, was 78% of office physicians that had

The growth rate of EHRs, as reported by the CDC in January 2014, was 78% of office physicians that had 
incorporated some level of basic EHR systems (CDC data; Figure 3.7). That is dramatic growth from 2010 
when the number stood at 51%. The major cause of this acceleration in implementation was the passage 
of the ARRA’s (HITECH Act) in 2009 that allocated $19.7 billion to subsidize EHR costs and new added 
mandates that enacted penalties for Medicare and Medicaid reimbursement beginning in 2015 if bills 
and treatment records were not electronically submitted ( http://www.himss.org/News/NewsDetail . 
aspx?ItemNumber=27596). 
As of January 2015, there were approximately 600 EHR vendors. Larger vendors, in the hospital arena, 
accounted for 90% of the market. The top three, Epic, Meditech, and  Computer Programs and Systems’ 
Inpatient  (CPSI), hold just over 50% of the market. In the smaller market, physicians, and small prac­

tices, Epic is also the leader, but the rest of the market is more fragmented (Figure 3.8).

14.2% 
9.0% 
8.6% 
7.0%5.4% 
5.2% 
4.1% 
2.0% 
8.2% 
19.1% 
17.2% 
(a) 
11.6% 
20.3% 
8.0% 
6.9% 
5.5% 
2.7% 
2.6% 
2.5% 
2.4% 
2.2% 
35.3% 
Epic System Coporation
MEDITECH 
CPSI (Computer Programs and Systems)
Cemer Corporation
McKesson 
Healthland, Inc.
Siemens Medical Solutions USA 
Healthcare Management Systems
Allscripts
NextGen Healthcare 
Other 
Epic System Coporation 
eClinicalWorks 
GE Healthcare 
Practice Fusion 
Greenway Medical Technologies 
McKesson 
Athenahealth 
Vitera Healthcare Solutions 
Other 
(b) 
58 Biomedical Informatics 
80 
60 
40 
Any EHR system
Percent 
20 
18.2 17.3 17.3 
20.8 23.9 
29.2 
34.8 
42.0 
48.3 51.0 
57.0 
39.6 
33.9 
27.9 Basic system 
16.9 
10.5 11.8 
21.8 
48.1 
78.4 
71.8 
0 
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 
FIGURE 3.7  Electronic health record implementation statistics as of January 2014 source CDC.  Note: EHR is electronic

FIGURE 3.7  Electronic health record implementation statistics as of January 2014 source CDC.  Note: EHR is electronic  
health record. “Any EHR system” is a medical or health record system that is either all or partially electronic (excluding  
systems solely for billing). Data for 2001–2007 are from in-person National Ambulatory Medical Care Survey (NAMCS)  
interviews. Data for 2008–2010 are from combined files (in-person NAMCS and mail survey). Estimates for 2011–2013  
data are based on the mail survey only. Estimates for a basic system prior to 2006 could not be computed because  
some items were not collected in the survey. Data include nonfederal, office-based physicians and exclude radiologists,  
anesthesiologists, and pathologists. (From CDC/NCHS, National Ambulatory Medical Care Survey and National  
Ambulatory Medical Care Survey, Electronic Health Records Survey. https://www.google.com/url?sa=i&rct=j&q=&e

Ambulatory Medical Care Survey, Electronic Health Records Survey. https://www.google.com/url?sa=i&rct=j&q=&e 
src=s&source=images&cd=&cad=rja&uact=8&docid=-Wg5J-nGEhQ6nM&tbnid=ZL5cFGMGhYbfKM:&ved=0CA 
UQjRw&url=http%3A%2F%2Fwww.cdc.gov%2Fnchs%2Fdata%2Fdatabriefs%2Fdb143.htm&ei=RwaeU9iYNq7jsATU 
yYDYCw&bvm=bv.68911936,d.cWc&psig=AFQjCNErUDWAq0Ky5ZuQKfNXsFQCleaoeg&ust=1402951600266245.) 
FIGURE  3.8  Electronic medical record. (a) Hospitals and (b) smaller practices. (Adoption by Vendorhttp://www. 
policymed.com/2014/05/2014- electronic-health-records-market-share.html.)

59 Electronic Health Records 
3.4 Data 
The challenge is to efficiently populate EHRs and extract summary information tailored to different 
medical environments. The optimum goal is to minimize manual data input and to maximize automatic 
data feeds so practitioners can focus on patient care. Automated medical monitors, wireless medical 
devices, and data feeds from various sources such as labs, pharmacies, medical scans, and integrated 
medicated records through HIEs, will continue to increase over time. Phase I EHR mandate was to 
convert all medical data to an e-health format, Phase II is an ubiquitous exchange of data from multiple 
EHRs and integrated medical monitoring equipment and wireless sources, internal and implanted, this 
effort in underway. Phase III goal is to develop better user interfaces (see Appendix on APPs develop­
ment for EHRs) tailored for each medical environment; this effort has barely begun.

ment for EHRs) tailored for each medical environment; this effort has barely begun. 
Medical units previously utilized manual flow sheets (Figure 3.9), which have all the information 
nurses needed to capture in a concise format that was easy to enter and visually evaluate. The first gen­
eration EHRs requires nurses to navigate from screen to screen and sit in front of a computer console, 
which is not very efficient and reduces patient contact time. The next phases of EHR development will 
involve customizing apps on touch screen tablets to recreate these flow sheets with the added benefits 
that EHRs provide such as integrating data from labs and scans, displaying graphs and summaries over 
longer periods of time, sharing data instantly with multiple healthcare providers, and soon integrating 
clinical support systems that can provide diagnosis or at least prompt users of possible errors or concerns. 
3.4.1 EHR Data Entry

3.4.1 EHR Data Entry 
The challenge of entering medical data into an online system is developing intuitive user interfaces 
to provide quick, concise, accurate, and intuitive methods of data entry that will allow the caregiver 
to focus on patient care and reduce medication and documentation errors. EHRs, medical errors 
accounted for more deaths, approximately 100,000/year, than car accidents in 2001 ( http://www.medi­
calnewstoday.com/releases/11856.php). When possible, automated transfer of lab and vital signs should 
be integrated into data entry. The following is an actual data entry challenge in a hospital. A  nurse 
from a major medical center explained that during a routine patient care interaction, EHRs had just 
been introduced 4 months earlier into their hospital, the process of entering the data on a pint of blood

been introduced 4 months earlier into their hospital, the process of entering the data on a pint of blood 
was as follows. Even though bar code scanners are available at some hospitals, bar codes are available 
on most blood products, a bar code scanner link between the EHR was not available at this particular 
FIGURE  3.9 Manual flow sheets used in hospitals prior to electronic health records.

60 Biomedical Informatics 
hospital. Two nurses are typically required for this process, one to read the label and the other to check 
the patient ID and both sign and verify that the correct blood was administered. When this was manual, 
a paper form was filled out and sometimes an extra barcode sticker was attached and both nurses signed 
to ensure accuracy. In this case, this all had to be done while entering the data into an EHR computer 
console rolled to the bed. The codes were multiple 20 digit codes, where there is, of course, opportunities 
for errors. Rather than take a couple of minutes, it was exacerbated by the fact that the patient started 
having pain issues and a third nurse came in to enter the data to speed up the process. It took three 
times as long as the manual process. The purpose of this true story was that EHR data entry processes 
have to be constantly reevaluated and nurses involved in the feedback process to change procedures that

have to be constantly reevaluated and nurses involved in the feedback process to change procedures that 
don’t work efficiently. Sometimes, EHRs can be worse in terms of nursing processes, and installing an 
EHR without constant process improvement can be detrimental to patient care, patient satisfaction, and 
nursing morale. 
Entering data in EHRs can be from user input or from external sources. Human-Centered input data can 
be free-form, codes, drop-down lists, voice input, transcription, bar code scanners, or as yet-to-be-designed 
input devices. Automatic form entry can be from direct transmission from medical devices, bar code scan­
ners, pulled from databases, or from external record feeds through remote EHRs filtered through HIEs. 
When possible, the free-form data entry should be limited since generating summaries, graphs, and 
reporting data to external reporting agencies becomes more difficult. If you enter “a patient is experiencing

reporting data to external reporting agencies becomes more difficult. If you enter “a patient is experiencing 
right lower quadrant pain” and explain the symptoms, as opposed to a drop-down list for pain, the symp­
toms can be selected from the ICD10 where as you type in a field, it autocompletes the terms: The ICD10 
code for right lower quadrant pain is R10.31. Many EHR systems are including this autocomplete option. 
SNOMED is also used to define medical terms, diseases, microorganisms, etc. 
SNOMED CT, provides a granular, detailed, level description of conditions and the subsequent asso­
ciated symptoms versus using ICD10. The term “multiple granularities” (mg) refer to the level of detail; 
SNOMED has 20 levels versus ICD10 4. In contextual representations, SNOMED CT is stronger, pro­
vides more contextual details, than ICD10. 
Figures 3.10a and 3.10b represent some of the coding schemes and a relationship—hierarchy diagram

Figures 3.10a and 3.10b represent some of the coding schemes and a relationship—hierarchy diagram 
from SNOMED CT shows levels of description of a disease. 
Some new EHR systems allow you to define relationships and the complexity of a particular medi­
cal condition beyond just a simple code. After you enter the initial symptom-associated granularities 
such as right lower quadrant pain and other descriptive options, following the preceding text, entity– 
relationship diagram that illustrates increasing levels of detail available will appear with the associated 
codes. These autofill suggestions can be very sophisticated, are further described in Level II CDSS, and 
can guide you through terminologies and even check recommended medications and treatment. 
Other coding schemes for data entry are Logical Observation Identifiers Names and Codes (LOINC),

Other coding schemes for data entry are Logical Observation Identifiers Names and Codes (LOINC), 
which is a database and universal standard for identifying medical laboratory observations. It was 
developed in 1994 and is maintained by the Regenstrief Institute, a U.S. nonprofit medical research 
organization. LOINC was created in response to the demand for an electronic database for clinical care 
and management and is publicly available at no cost. 
It is endorsed by the American Clinical Laboratory Association and the College of American Pathologists. 
Since its inception, the database has been expanded to include not just medical and laboratory code names, 
but also nursing diagnoses, nursing interventions, outcomes classifications, and patient care data set. 
3.5 U.S. Initiatives 
In 1996, HIPAA and the ARRA in 2009 created the foundation for EHRs development in the United 
States. ARRA included financial incentives, $19.7 billion, to modernize the U.S. medical infrastructure,

States. ARRA included financial incentives, $19.7 billion, to modernize the U.S. medical infrastructure, 
a component of ARRA was the HITECH Act. One feature of HITECH was to define the guidelines 
to determine the effectiveness of the EHR implementation and reimbursement documentation. This 
was referred to as meaningful use, which was categorized by how EHRs and their implementation in a 
particular setting contribute to the quality, safety, efficiency of patients, and reduce health disparities.

(a) 
(b) 
Summary: Technology and Standards for HealthcareSNOMED CT
Messaging Standards Used for:
Clinical findings Body site	 HL7 Clinical data
X12N Financial data, HIPAA mandated transactions
DICOM ImagesSite findings Disease
NCPDP Standards for pharmacy business functions, HIPAA mandated transactions
IEEE	 Bedside instruments, medical infomation busDisorder by
Digestive Body region body region Terminology Standards
LOINC
Disorder of
digestive system Drugs NLM/FDA/VA collaboration on RxNorm, NDF-RT
Disorder of Billing CPT, ICD-9CM
endocrine system Clinical UMLS, SNOMED and others 
 
61 Electronic Health Records 
FIGURE  3.10 (a, b) Systematized Nomenclature of Medicine Clinical Terms entity–relationship diagram and various coding schemes from HHS.gov .

HIPAA
 
Health Insurance Portability and Accountability Act of 1996
 
Title I Title II	 Title III Title IV Title V 
Healthcare Preventing Medical	 Tax-related Groupaccess, healthcare Administrative	 Revenueliebility	 health health planportability, and fraud and simplification	 offsetsreform	 provision requirementsrenewability abuse 
Electronic data
 
interchange Privacy Security
 
Security standards: general rules 
Physical safeguardsTransactions Identifiers Code sets 
Organizational requirements 
Policies and procedures and 
Documentation requirements 
CBS_01527a 
 
62 Biomedical Informatics 
3.5.1 HIPAA 
The HIPAA of 1966 was comprised of two main components (Figure 3.11). 
1. Title I: Healthcare access, portability, and renewability. This protected individuals from losing 
their health insurance when they lose their jobs.

 2. Title II: Preventing healthcare fraud and abuse, administrative simplification, and medical liabil­
ity reform. It also included privacy rules, transactions and code sets rules, security rule, unique 
identifiers rule, and an enforcement rule. It provided guidelines for privacy and security and pro­
vides national standards for medical records and transactions. 
a. 	 The HIPAA Title II privacy rule regulates the disclosure and use PHI. It refers to any portion 
of the EHR and medical payments. Any violations can be reported to HHS, but it has a poor 
enforcement record. In 2013, the law was amended to restrict disclosure to 50 years after death 
called the omnibus rule. 
i. 	 Specifications for anonymizers, i.e. methods to remove patient identifiers from EHRs 
(Social Security number, names, etc.) to ensure patient confidentiality. Anonymizers are 
used when large medical data sets are shared to track outbreaks.

used when large medical data sets are shared to track outbreaks. 
b.	 The administrative simplification portion of Title II specifies documentation standards 
such as ICD and ICD10 for reimbursement of Medicare and Medicaid services. ICD10 is a 
comprehensive list developed by the World Health Organization of diseases, symptoms, etc. 
Examples of some of the categories are A00–B99 infectious and parasitic diseases, F00–F99 
mental and behavioral disorders, and I00–I99 diseases of the circulatory system. 
FIGURE  3.11 HIPAA standards created by the U.S. Government in 1996. (From HHS, http://www.hhs.gov/ocr/ 
privacy/hipaa/administrative/securityrule/nist80066.pdf.)

Information and Sharing among Stage 2: Advance Clinical 
Multiple Providers 2011–2012 Processes 2014 Stage 3: Improved Outcomes 2016 
Increased requirements for 
e-prescribing and incorporating lab 
results 
Electronic transmission of patient 
care summaries across multiple 
settings 
efficiency, leading to improved health 
outcomes 
tools 
Access to comprehensive patient data 
through patient-centered HIE

tools 
through patient-centered HIE 
63 Electronic Health Records 
3.5.2 American Recovery and Reinvestment Act 
The ARRA passed by Congress in 2009 contained $782 billion to jumpstart the economy. The ARRA 
provided $31 billion for healthcare initiatives of which $19.7 billion were earmarked to facilitate the adop­
tion of EMRs by the healthcare community. It includes the HITECH Act, which incorporated meaning­
ful use specifications that became guidelines for reimbursement and categorization of the effectiveness 
of integration of EHRs into their processes (http://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS­
111hr1enr.pdf). 
3.5.3 Meaningful Use 
The term “meaningful use” was defined by the CMS as a series of standards and incentive programs used 
as criteria for physician reimbursement for physicians that were to be funded between $44,000–$64,000

as criteria for physician reimbursement for physicians that were to be funded between $44,000–$64,000 
and for hospitals $3,000,000–$5,000,000 to offset the costs of implementing EHRs. “The goal of meaning­
ful use was to promote the spread of EHRs to improve healthcare in the United States” (www.healthit.gov). 
CMS specified three general benefits of implementing EHRs: (1) Complete and accurate information 
and history of their patients. Paper patient records were dispersed among many providers, and tests 
were often duplicated unnecessarily. (2) Better access to information. (3) Patient empowerment. Patients 
are allowed access to all their medical records and can be part of the decision-making process. Personal 
data records allow individuals to maintain their own person copy of their medical information. 
The ONC for Health Information Technology part of the U.S. Department of HHS created a nonprofit

The ONC for Health Information Technology part of the U.S. Department of HHS created a nonprofit 
Certification Commission for Healthcare Information Technology (http://www.cchit.org/) to certify 
that organizations met meaningful standards (Table 3.3). 
Meaningful use has two sets of standards, one for physicians another for hospitals. Physicians have 24 
objectives of which 19 have to be met to qualify for EHR reimbursement of implementation costs. Hospitals 
have 23 meaningful use objectives, 18 of which have to be satisfied. These are further broken down into 
core objectives and a second set of 10 subobjectives from which you have to complete 50% (Table 3.2). 
3.5.3.1 Meaningful Use Stage 2 Final Rule 
An important feature of meaningful use Stage 2 is for data interoperability that will enable the HIEs (see 
Section 3.6) ability to exchange data between EHRs (http://www.gpo.gov/fdsys/pkg/FR-2012 –09–04/

Section 3.6) ability to exchange data between EHRs (http://www.gpo.gov/fdsys/pkg/FR-2012 –09–04/ 
pdf/2012–21050.pdf) from differen t vendors. The meaningful use Stage 2 final rule specifies data sets 
and structured coded data to be transmitted between systems. 
TABLE 3.3 Meaningful Use Timetable by Center for Medicaid and Medicare Services (CMS.gov)

TABLE 3.4 CVX Vaccine Reference Tables 
64 Biomedical Informatics 
Some specific Stage 2 specifications are (see Chapter 4) 
 1. Procedures (SNOMED CT) 
 2. Laboratory test results (LOINC) 
 3. Medications and allergies (RxNorm) (normalized names for clinical drugs) 
 4. Encounter diagnosis (SNOMED CT or ICD10-Clinical Modification) 
 5.  Immunizations (CVX) (CDC vaccine codes) (Table 3.4) 
 6. Vital signs including height, weight, blood pressure, and smoking status (SNOMED CT) 
 7. Patient name and demographic information: preferred language (ISO 639–2 alpha-3), sex, race/ 
ethnicity (OMB Ethnicity), and date of birth 
 8. Functional status including activities of daily living, cognitive, and disability status 
 9.  Care plan field including goals and instructions 
 10. Discharge instructions (for hospitals) 
Sample of CDC vaccine codes (CVX): http://www2a.cdc.gov/vaccines/iis/iisstandards/vaccines. 
asp?rpt=vg.

asp?rpt=vg. 
Table 3.5 lists the meaningful use objectives for laid out in the ARRA of 2009 that will determine the 
level of reimbursement for EHR implementation. 
3.5.4 E-Prescribing 
Electronic prescribing (e-prescribing) refers to the electronic submission of prescriptions from a physi­
cian directly to a pharmacy. The goal was to reduce medication errors created by hand-writing ambi­
guities and improve patient care by integrating online error checking that evaluates drug interaction 
and allergies. It also enhances oversight by funding agencies to evaluate overprescribing of controlled 
substances and track treatment protocols. 
E-prescribing was mandated in the Medicare Modernization Act (MMA) of 2003. In 2005, MMA 
published standards under the Medicare Prescription Drug Benefit called Medicare part D. Medicare 
Vaccine Uncertain

Vaccine Uncertain 
Short Description CVX Code Vaccine Status Group Name Formulation CVX 
Adenovirus types 4 and 7 143 Active ADENO 82 
Adenovirus, type 4 54 Inactive ADENO 82 
Adenovirus, type 7 55 Inactive ADENO 82 
Adenovirus, unspecified formulation 82 Inactive ADENO 82 
Anthrax 24 Active ANTHRAX 
BCG 19 Active BCG 
Botulinum antitoxin 27 Active 
Cholera 26 Inactive Cholera 26 
CMVIG 29 Active IG 14 
Dengue fever 56 Never active 
Diphtheria antitoxin 12 Active 
DT (pediatric) 28 Active DTAP 107 
DTaP 20 Active DTAP 107 
DTaP , 5 pertussis antigens 106 Active DTAP 107 
DTaP , unspecified formulation 107 Inactive DTAP 107 
DTaP , IPV , Hib, HepB 146 Pending DTAP 107

Reinvestment Act)
 
Use computerized physician order entry for physicians. 
Implement drug–drug and drug–allergy interaction checks. 
Maintain an up-to-date problem list of current active 
diagnoses. 
Keep an active medication list. 
Maintain an active medication allergy list. 
Record specified demographics on patients. 
Record and chart changes in specific vital signs. 
Document whether patients age 13 and older are smokers. 
Report clinical quality measures. 
Implement one clinical decision support rule related to a 
Offer patients an electronic copy of their health information 
upon request. 
Give patients an electronic copy of their discharge 
Have the capability to exchange key clinical information. 
Protect electronic health Information. 
Implement drug formulary checks.

Implement drug formulary checks. 
Incorporate clinical lab-test results into electronic health 
record (EHR) as structured data. 
Generate list of patients by specific conditions to use for 
Send patient reminders per patient preference for 
preventive follow-up care. 
Provide patients with timely electronic access to their health 
information (including lab results, problem list, 
Use certified EHR technology to identify patient specific 
The physician who receives a patient from another setting of 
care or provider or believes an encounter is relevant 
should perform medication reconciliation.

should perform medication reconciliation. 
The physicians who transition their patients to another 
setting of care or refer their patients should provide a 
summary of care record for each transition. 
Capability to submit electronic data to immunization 
applicable law and practice. 
Capability to submit electronic syndrome surveillance data 
to public health agencies and actual submission according 
to applicable law and practice. 
65 Electronic Health Records 
TABLE 3.5 Meaningful Use, 24 Objectives, of which 19 Have to Be Satisfied, to Receive Meaningful Use Funding 
Meaningful Use Objectives (to Qualify for Incentive Reimbursement Program from the American Recovery and 
part D ( http://www.medicare.gov/part-d /) is a program to subsidize prescription drugs under the 
Medicare program enacted in 2006. The initial plan covered the first $2970 cost of prescriptions. Then,

Medicare program enacted in 2006. The initial plan covered the first $2970 cost of prescriptions. Then, 
the donut hole kicked in where coverage resumed after exceeding $4750. So, for this $2000 gap, patients 
received no coverage. The affordable healthcare plan, ObamaCare, eliminated this donut hole  gap in 
prescription drug coverage. 
The CMS (www.cms.gov) mandated that all physicians convert to e-prescribing by January 1, 
2013, and register before that date with CMS. There are reimbursement penalties increasing every 
year initially 1% then 2% year then finally 3%. There are hardship exemptions that can be applied 
for and which can be found at http://www.ama-assn.org/resources/doc/hit/avoid-erx-penalty-tip. 
pdf (Figure 3.12).

66 Biomedical Informatics 
Patient 
Demographics/
Prescription 
Patient 
Inquiry 
Pharmacy
benefit 
manager 
Eligibility,
Formulary,
Medication history 
Prescription
data 
fill status 
Medication 
History fill status 
Prescriber 
Pharmacy 
Transaction 
hub 
1. 
2. 
Maintains 
Master-Patient 
Index 
Maintains Index 
of Enrolled 
Pharmacies 
FIGURE  3.12 E-prescribing defined by the Center for Medicare and Medicaid Services. 
3.6 Health Information Exchanges 
The term “health information exchange” (HIE) refers to the sharing of information among multiple providers 
and organizations that have different EHR systems (Figure 3.13). There are 56 funded HIEs, link to all state 
and territory HIEs (http://statehieresources.org/state-plans/). In 2011, $548 million from the ARRA created 
the State Health Information Exchange Cooperative Agreement Program to promote and fund HIEs across

the State Health Information Exchange Cooperative Agreement Program to promote and fund HIEs across 
the U.S. healthcare system. The grants ranged from $600 thousand to American Samoa to $28 Million to Texas 
HHS. Its goal was to create interoperability of all medical records. The goal of HIEs is to provide transparency 
among EHR providers, where a medical record is created in a particular hospital/physician’s office using an 
EHR such as Cerner, and that medical data are accessible from another hospital utilizing another EHR, for 
example, EPIC. All EHR/medical records are required by HIPAA to be designed around data storage standards 
such as HL7, DICOM, SNOMED, and ICD9–10. Unfortunately, there is enough variation in internal data struc­
tures that require an HIE to ensure smooth communication between systems built by different vendors. 
An added benefit was the ability to gather patient demographics data and potential outbreaks and

An added benefit was the ability to gather patient demographics data and potential outbreaks and 
report them to the CDC. The goal of the CDC is to protect public health and safety. One of the key 
meaningful use objectives is to “submit electronic syndrome surveillance data to public health agencies. ” 
The ONC for Health Information Technology has set guidelines to (1) standardize the structure of the 
data with formats such as HL7 , www.hl7 .org; (2) standard medical vocabularies such as SNOMED and 
ICD10, www.cdc.gov/nchc/icd/icd10.htm; (3) standard application programming interface (API); and 
(4) security and encryption as outlined by the National Institute of Standards and Technology (NIST) 
security architecture (www.nist.gov/healthcare/security/hiesecurity.cfm). The Nationwide Health and 
Information Network (NHIN) from the ONC details those standards in the document  NIST Interagency

Information Network (NHIN) from the ONC details those standards in the document  NIST Interagency 
Report 7497 “Security Architecture Design Process for Health Information Exchanges” by Kenneth Lin 
and Daniel Steinberg, September 2010 (http://csrc.nist.gov/publications/nistir/ir7497/nistir-7497.pdf). 
3.6.1 Three Types of Health Information Exchange 
1. Directed exchange—ability to send and receive secure information electronically between care 
providers to support coordinated care 
a.	 Directed, often called point-to-point, uses a secure messaging protocol called Direct 
Project services  offered by the ONC’s state HIE program (http://www.healthit.gov/ 
providers-professionals/state-health-information-exchange), one of the meaningful use

Physician Nurse 
Hospital 
Medical lab 
Health Information 
exchangePharmacy	 (HIE) HL 7, DICOM, 
SNOMED, ICD 9–10, 
CERNER, EPIC, 
VistaA, etc. 
Hospital 
Lubliner 2013 
MRI-CAT
 
Scans
 
67 Electronic Health Records 
FIGURE  3.13 Health information exchange. 
certification requirements. It will allow medical providers to share patient records utiliz­
ing a process as simple as e-mail but securely encoded. 
 2.  Query-based exchange—ability for providers to find, search, and/or request information on a 
patient from other providers, often used for unplanned care (http://www.healthit.gov/sites/ 
default/files/query_based_exchange_final.pdf) 
 a.  Key challenge is converting medical records between data formats allowing queries. 
 b.	  Defined by five rights: right information, right person, right format, right channel, and right 
time. 
 3.  Consumer-mediated exchange—ability for patients to aggregate, get personal copies, and control

time. 
 3.  Consumer-mediated exchange—ability for patients to aggregate, get personal copies, and control 
the use of their health information among providers. 
 a. Allows patients to correct wrong or missing information and correct billing errors. 
 b.	  Allows them to track their own health information, which can be stored in personal data  
records. 
A regional health information organization brings together medical organizations in a particular  
region, which includes public health organization and certified laboratories; it is often used to assist the 
development of HIEs. The goals are similar to HIEs; it is a group of companies, hospitals, or organiza­
tions that have developed a system to provide a seamless exchange of health information. 
NHIN also called an eHealth Exchange developed by the U.S. ONC for Health Information 
Technology is a series of specifications to securely exchange health data. The goal of the ONC is to tie

Technology is a series of specifications to securely exchange health data. The goal of the ONC is to tie 
together HIEs to create a nationwide network. Some of the organizations that are currently part of the 
NHIN are (1) Social Security Administration, (2) VA, (3) CDC, (4) CMS, and (5) Department of Defense. 
http://www.healthit.gov/sites/default/files/pdf/fact-sheets/nationwide-health-information-network­
exchange.pdf.

68 Biomedical Informatics 
Level II: EHR Applications 
3.7 Navigating an Electronic Health Record
 
This section illustrates components of typical examples EHRs and the common sections/tabs that are 
typically available. They include a central navigation console, patient lists, orders, lab/medications, and 
a discharge screen that usually acts as a checklist by multiple care providers to ensure all medications 
and signatures have been completed. 
3.7.1 Central Console 
All EHRs have a central navigation console (Figure 3.14) . It provides you with access to a subset of the 
EHR database i.e., display a patient’s medications in a Medication Administration Record (MAR). A list 
of your patients appears when you log on that are automatically categorized into folders based on their 
needs. If a new medication request is made, i.e., a patient has requested additional pain medication, the

needs. If a new medication request is made, i.e., a patient has requested additional pain medication, the 
nurse will check a priority field, and those requests, when you log on, will be placed in your urgent/pri­
ority folder. If a patient is scheduled for discharge and requires your signature, electronic, that request 
also will be filtered into a separate folder. The potential for efficiency is impressive and potentially trans­
formational in improving healthcare and reducing errors, but the process of customizing your inbox 
environment takes time and requires a good support staff. That support component is often under­
funded in most healthcare systems. Three to six months after an EHR system is implemented is the time 
to reevaluate the processes and effectiveness of its daily use. Morale can also be enhanced significantly 
if it is treated as an evolutionary process. 
3.7.2 Patient List

3.7.2 Patient List 
Starting from a central navigation screen, you begin by selecting a patient list that has been assigned to 
one of the medical providers, physician, nurse, etc. (Figure 3.15). Next, select a specific patient, and his 
or her history, medication, diagnosis, and treatment can be reviewed. 
3.7 .3 Demographics 
 1. Name, age, allergies, date of birth, sex, attending, discharge date. 
 2. Drill down: Many of these items can be selected for further details. 
 a. 	 Click on, for example, allergies. A detailed list appears and then right click on a specific 
allergy to add more information. They are usually listed from most severe at top. 
3.7.4 Navigator 
 1. Navigator bar: Select features of the patient records. 
 2. Results: Usually the first option is a general summary of patient information. 
 3. Diagnosis: Will usually show diagnosis and problems for the patient.

3. Diagnosis: Will usually show diagnosis and problems for the patient. 
 4. Notes: Used to document patient encounters. There is usually an option to included other scanned 
forms into this patient record. 
 5. Forms: Will be any charted information (Figure 3.16). 
3.7 .5  Medication Administration Record 
Orders: Medication Administration Record (MAR) place, view, modify, cancel, or work with any type  
of orders (Figure 3.17 a and b) 
 1.  Drug references: Usually used by pharmacist and clinicians 
 2. ICU summary: Available for patient treatment just in the ICU

Step 1 Central information console	 Step 3 Orders
Patient List Orders Rounds DischargeDisplay 
Need your attention Add Document Medication bycategories Hx Reconciliation
Messages INBOX Orders (Patient History:  Admission Process)
(3)	 (Sign, Review results, place orders)
Patient Order Originator Date Status
 Priority Orders	 Document AdmissionMedication by(current	 in planJon Doe  Insulin Mary  Smith 9/1/13 Pending	 TransferWork	 hospital list (outcomes forMary  Doe  Plasma Bill Natel 9/2/13 Pending	 (across all visits) Items	 visit) interventions) Discharge 
Orders (3) Filters (display subset orders) Customizedview 
Categories (Orders) -All Orders
Bold contain orders -Active orders (24 hrs)Step 2 Patient view -Completed orders 
Summary Screen- Vital Signs New Orders Order (profile)Patient Care (X selected in categories displays item) 
Outstanding Orders Therapies
Vital signsIV Solutions
Immunization Medications
Laboratory Medications Intake and output 
 
69 Electronic Health Records

69 Electronic Health Records 
FIGURE  3.14 Navigation in an electronic health record, central console inbox, patient view, and medication orders.

70 Biomedical Informatics 
Patient List (active) When a Nurse/Doctor/Specialist logs on the patients assigned to them are Displayed 
Name Room Bed Age (years) Sex MRN Length of Stay Admitting Phy Note 
John Doe 
Jane Doe 
0601 
0602 
A 
A 
80 
65 
M 
F 
0123456789 
1234567890 
10 Days 
12 Days 
Arthur 
Arthur 
Physician 
Physician 
John Smith 
Jane Smith 
0603 
0604 
B 
A 
42 
81 
M 
F 
2345678901 
3456789012 
05 Days 
02 Days 
Ross 
Arthur 
Physician 
Physician 
John Rand 
Jane Rand 
Bill Doe 
0605 
0606 
0607 
B 
A 
B 
77 
48 
73 
M 
F 
M 
4567890123 
5678901234 
6789012345 
12 Days 
10 Days 
05 Days 
Kiel 
Arthur 
Ross 
Physician 
Physician 
Physician 
Alice Doe 
Bill Rand 
0608 
0609 
A 
B 
60 
70 
F 
M 
7890123456 
8901234567 
15 Days 
03 Days 
Arthur 
Patel 
Physician 
Physician 
FIGURE  3.15 Patient list associated with a healthcare provider. 
(a) (b) 
FIGURE  3.16 (See color insert.) (a, b) Navigator on left; patient status view on right. 
(a) (b)

(a) (b) 
(a) (b) 
FIGURE  3.17  (See color insert.) (a, b) Medication Administration Record (MAR) delivery timetable, MAR drug  
summary table. (From http://www.pearsonhighered.com/realehprep/learn-about/what-is.html.) 
3.7 .6 Orders 
Inpatient summary: screen for therapeutic results: Vitals after medications are administered (Figure 3.18). 
3.7.7 Discharge Orders 
Discharge: Allows you to manage the process of documenting and planning the patient discharge pro­
cess (Figure 3.19). There are usually workflow tabs to select if each of the required steps have been com­
pleted, and once all steps are done, the physician electronically signs the discharge.

71 Electronic Health Records 
FIGURE 3.18 Patient orders from physicians are summarized. 
FIGURE  3.19  Patient discharge checklist. (From https://store.cerner.com/.) 
Level III: Advanced Topics: Decision 
Support Systems, Expert Systems 
3.8 Clinical Decision Support System
 
A CDSS is a software that assists healthcare professionals in making diagnosis, treatment decisions, and 
workflow decisions. A number of synonyms have been used for CDSS such as knowledge management, 
artificial intelligence (AI)-neural networks, inference engines, and diagnosis support system. The adop­
tion of CDSS is sketchy in clinical diagnoses since there is concern about incorrect or medical recom­
mendations based on incomplete information. Does the knowledge base take into account all the factors, 
such as patient history, genetics, symptoms, and even geographical data, which might contribute to root

such as patient history, genetics, symptoms, and even geographical data, which might contribute to root 
causes of illness? As EHRs proliferate and a larger more inclusive database evolves, research will evaluate 
symptoms and treatments and produce reliable probabilities to aid healthcare workers. It’s only a matter 
of time till they become more widely accepted based on larger studies of patient outcomes.

Medical Logic Modules (MLM) Categories
(slots) (examples taken from HL 7 Arden Syntax manual 2.10 May 2014) 
Maintenance Library Knowledge Resources 
SYNTAX: 
Arden Syntax Version: 
arden: version 2.9; version: 1.00; 
Tile describes what the MLM does: 
title: Hepatitis B Surface Antigen in
      Pregnant Women; 
Authoring institution, up to 80 characters in length
institution: columbia university;
author: John M. Smith, Jr.;
 specialist : Jane doe, Ph.D.;
 date: 2014-01-02; 
Validation codes
 
production—approved for use in the clinical system,
research—approved for use in a research study,
testing—for debugging (should be the initial value)
expired—out of data, no longer in clinical use.
validation: testing; 
Library: Knowledge Base 
Purpose: Why its being used 
purpose: Screen for newborns who are
at risk for developing hepatitis B;
Explanation: 
explanation: This women has a positive
hepatitis B surface antigen titer within
the past year. Therefore her newborn is at risk for

developing hepatities B.;
Keywords: (used for searching through modules)
keywords: hepatitis B; pregnancy;
Citations: (support, refute)
citations 
1. SUPPORT Steiner RW. Interpreting the
fractional excretion of sodium. AmJ 
Med 1984; 77:699-702.
Links: (other cases or resources) 
URL_LINK’NLM Web Page’ ,
“http://www.nlm.nih.gov/”; 
Knowledge Category: 
Type: 
type: data driven;
Priority (order evoked)
         priority: 90;
Logic (true, false)
Urgency (importance of Action)
         urgency: 70;
Data Value 
if latest potas > 5.0 then
conclude true; 
endif; 
Time Function Operator 
if time of latest potas is
     within past 3 days 
Then conclude true; 
endif; 
 
72 Biomedical Informatics 
Meaningful use guidelines mandate that at least one clinical decision support system component,

endif; 
 
Meaningful use guidelines mandate that at least one clinical decision support system component, 
diagnostic test ordering, be integrated in their EHR system. Prescription and billing systems also are 
required to submit electronically their reimbursement requests and many systems currently include 
CDSS to ensure all components required for Medicare and Medicaid are completed before submission. 
3.8.1 HL7 Decision Support Services 
HL7 “is a not-for-profit, ANSI-accredited standards developing organization dedicated to providing a 
comprehensive framework and related standards for the exchange, integration, sharing, and retrieval of 
electronic health information that supports clinical practice and the management, delivery and evalu­
ation of health services” (www.hl7.org). A Decision Support Service inputs patient data and provides 
specific assessment and recommendations on diagnosis and treatment to aid medical personnel based

specific assessment and recommendations on diagnosis and treatment to aid medical personnel based 
on an evolving knowledge base. 
3.8.1.1 Arden Syntax for Medical Logic Modules 
The Arden syntax for medical logic systems, from HL7, encodes procedural medical knowledge. Its 
function is to help clinicians make better decisions based on prior patient treatment knowledge. The 
health databases, in HL7, consist of medical logic modules (MLMs), each containing knowledge for a 
single decision (Figure 3.20). 
Features the MLM provides (wiki.hl7.org/images/a/aa/Arden_Syntax_2.10_draft_2014–03–18.docx) 
are as follows: 
1. MLM, contains sufficient knowledge to make a single decision.
 2. Contraindication alerts.
 3. Management suggestions.
 4. Data interpretations.
 5. Diagnosis scores. 
3.8.1.2 Fuzzy Data Sets 
Fuzzy sets allow you to define data sets or classes with unsharp boundaries to calculate degrees of truth

Fuzzy sets allow you to define data sets or classes with unsharp boundaries to calculate degrees of truth 
or if they fall if values fall in borderline range. Examples such as small or large, cold or warm, normal 
and elevated, enlarged and symmetric, diabetic and hypoxic are inherently a set, or class, with unsharp 
boundaries. An example with a sharp/crisp data set with clear boundaries between concepts are normal 
and pathological. 
FIGURE  3.20 Medical logic modules coding syntax.

73 Electronic Health Records 
Fuzzy number 
The data type fuzzy number is dedicated to fuzzy sets over the reals. A fuzzy number partitions the 
reals into a finite number of (possibly unbounded) intervals, on each of which the fuzzy set is linear and 
continuous. 
Formally, a fuzzy set u: R → [0, 1] can be stored into a variable of the type fuzzy number, if the fol­
lowing condition is met: There are a1 < a2 < … < ak with k >= 1, such that u is linear on each open interval 
(a1; a2), …, (ak-1; ak), u is constant on (-∞; a1) and (ak; +∞), and for each x in R, u(x) coincides either with 
the left limit or the right limit of u at x. If u is continuous, we then define 
Fuzzy set u = fuzzy set (a 1, t1), (a2, t2),…, (ak, tk),
 
where ti = u(ai) for i = 1, …, k and u(x) is called the characteristic function of the fuzzy set.
 
In MLMs discontinuity points, data are undefined or unknown in those regions, which means that

In MLMs discontinuity points, data are undefined or unknown in those regions, which means that 
approaching 2 from the left side, the membership value is 0, while approaching 2 from the right side, the 
membership value is 1. An example is 
Two to three = fuzzy set (2, truth value 0), (2, truth value 1), (2, truth value 1), (3, truth value 1), 
(3, truth value 0) 
Membership 
1 
1 2 3 4 5 6 7 8 x 
Example of MLM-coded logic 
logic: 
if last_pulse_rate is greater than 60 and
 low_dose_beta_use then
 
if angina_frequency is greater than 4 then
 
let msg be
 “Increased dose of beta blockers may be ” || 
“needed to control angina .”;
 conclude true; 
else 
if premature_beat_frequency is greater than 5 then 
let msg be 
“Increased dose of beta blockers may ” || 
“be needed to control PVC’s.”;
 conclude true;
 endif; 
endif;
 endif;
 conclude false;
 ;;
 
action:
 write msg;; 
end:

74 Biomedical Informatics 
3.8.2 Pharmacy Decision Support Systems
 
In the pharmacy, CDSSs are in widespread use and are usually integrated with e-prescription systems. 
They check drug interactions, contraindications, allergies, and dosage levels and report possible side 
effects and are linked in e-prescribing systems. They also cross-check guidelines and recommenda­
tions. Federal regulations for prescribing medications and controlled substances can be found under 
the U.S. Food and Drug Administration under Title 21, which is revised every year (http://www.fda.gov/ 
Drugs/default.htm). Title 21 is a more inclusive series of guidelines that includes, besides drugs, medi­
cal devices, medical scanners, and cosmetics. These drug indexes can be linked to pharmacy CDSSs, 
for example, to check for prescribing controlled substances 21 CFR 1306.04. These controlled substance 
guidelines are broken down into five categories; schedule 1, has a high potential for abuse, down to

guidelines are broken down into five categories; schedule 1, has a high potential for abuse, down to 
schedule 5, which has a low abuse potential. All these drugs are automatically reported back to the Drug 
Enforcement Administration (DEA) and these reports have resulted in investigation for overprescrib­
ing. The DEA also has a pharmacist manual that will be linked by the CDSS when certain substances 
are prescribed for quick reference (Table 3.6). 
Research studies on pharmacy CDSSs have confirmed the effectiveness and reduction of medication 
errors when linked in EHRs. On the U.S. National Library of Medicine website (http://www.ncbi.nlm. 
nih.gov/pubmed), a large number of studies validate the safety benefits of pharmacy CDSSs. In 2012, a 
study funded by the U.S. Agency for Healthcare Research and Quality on the effectiveness of medication 
manag emen t inf o rmatio n technology b y M cKibbo n K.A. et al. ti tled “The effectiv eness o f in tegrated

manag emen t inf o rmatio n technology b y M cKibbo n K.A. et al. ti tled “The effectiv eness o f in tegrated 
Health Information Technologies across the phases of medication management: a systematic review 
of randomized controlled trials http://www.ncbi.nlm.nih.gov/pubmed/21852412.” The results indicated 
an improvement in the process of care of 50% of the institutions studied. Clinical data on medical out­
comes were not available. Since the Affordable Care Act will be in common use by 2015, more clinical 
studies will be available in the near future. 
TABLE 3.6 Clinical Decision Support Systems 
Clinical Decision Support Systems (CDSS) (Representative List of Vendors) 
Name
 
Agfa HealthCare (Belgium)
 
Athenahealth, Inc. (United States)
 
Allscripts Healthcare Solutions, Inc.
 
Carestream Health, Inc. (United States)
 
Cerner Corporation (United States)
 
Epic (United States)
 
GE Healthcare (United Kingdom)
 
McKesson Corporation (United States)

NextGen Healthcare Information System, LLC (United 
States) 
Novarad Corporation (United States) 
Philips Healthcare (Netherlands) 
Siemens Healthcare (Germany) 
Zynx Health (United States) 
CDSS Primary Software Product 
The Archimedes Model 
Elsevier Clinical Decision Support 
The Isabel system 
PKC (which stands for problem–knowledge coupling) 
Micromedex point-of-care clinical decision support suite 
Wolters Kluwer Health 
Link
 
http://www.agfahealthcare.com/he/global/en/internet/main/
 
http://www.allscripts.com/
 
http://www.carestream.com/
 
http://www.cerner.com/
 
http://www.epic.com/
 
http://www.gehealthcare.co.uk/
 
http://www.mckesson.com/
 
https://www.nextgen.com/
 
http://www.novarad.net/
 
http://www.medical.philips.com/
 
http://www.healthcare.siemens.com/

http://www.zynxhealth.com/
 
http://archimedesmodel.com/archimedes-model/
 
http://www.clinicaldecisionsupport.com/
 
http://www.isabelhealthcare.com/home/default
 
http://www.pkc.com/
 
http://micromedex.com/
 
http://www.wolterskluwerhealth.com/pages/welcome.aspx/

Expert Systems Lubliner 2012 Inference engine Select closest match 
Probabilities 
correlation to existing data 
0 
Query Engine Knowledge
Age Symptom 1 62% base Sex Symptom 1 75% rules and History Symptom 1 data N 
Provide additional data on magnesium
Feedback of experts and potassium levels to validate
system versus clinical diagnosis 
data Mg++ K+ 
 
75 Electronic Health Records 
3.9 Expert Systems 
“Expert Systems are computerized applications that combine computer hardware, software and special­
ized information to imitate expert human reasoning and advice.” [5] The core components of expert sys­
tems are a knowledge base composed of rules and facts and an inference engine supplied with data from a 
user that selects the appropriate rules based on the data and calculates probabilities that the rules apply to a 
particular situation. An additional component is feedback from clinical data that cross-checks the validity

particular situation. An additional component is feedback from clinical data that cross-checks the validity 
of the rule/diagnosis that then adds to the refinement of the expert system knowledge base (Figure 3.20). 
Once a basis framework has been selected, the inference engine asks a series of targeted questions 
proposed by the expert system to refine matches to the existing knowledge base. A list of probabilities 
are then generated, i.e., an example of a system used for determining heart arrhythmias states to the 
medical professional that 62% of arrhythmias are due to hypokalemia, a low potassium level, and 75% 
due to hypomagnesaemia, low magnesium, that might be making the patient more prone to arrhyth­
mias. The system asks the individual to enter potassium and magnesium results from blood test to vali­
date or refute the hypothesis. This type of feedback mechanism provides more accurate diagnosis where

date or refute the hypothesis. This type of feedback mechanism provides more accurate diagnosis where 
additional data increases the probability of an accurate diagnosis. This is an example of a rule-based 
expert system (Figure 3.21). 
3.9.1 Inference Engine 
Inference engines determine which rules match those of the supplied data and match those with the 
highest probabilities. There are forward-chaining inference (FCI) engines that analyze the facts to some 
conclusion or disease. These systems are used to predict outcomes, an example of an FCI systems is 
EMYCIN, written in lisp, was used to identify bacteria-causing infections, which was developed at 
Stanford University [2]. It provided a 69% success rate, which was higher than practitioners at the time. 
A backward-chaining inference engine is from hypothesis to the facts used primarily for diagnosis; an 
example is the knowledge engineering environment.

example is the knowledge engineering environment. 
Other paradigms for medical expert systems are Case-Based Reasoning (CBR), cognitive systems, 
and crowd-based expert systems. The CBR utilizes a library, an evolving library of cases where matches 
are made to the current case, rather than utilizing a standard rule-based engine; this is similar to the 
process of how doctors make a diagnosis. The process involves these three steps; retrieve similar cases, 
FIGURE  3.21 Expert system architecture.

76 Biomedical Informatics 
reuse the case to solve similar problems, revise and modify the case, and finally, retain the new case 
with updates for the case library (4 Rs). 
Cognitive systems [3] are a series of AI paradigms with “the ability to engage in abstract thought that 
goes beyond immediate perceptions and actions.” Originally, comprehensive AI systems attempted to 
model human consciousness but, due to their lack of success, were modified for a more narrow expertise 
in specific domains of knowledge. An example is chess programs that are the equal of the best master 
level chess players. Cognitive systems utilize structured representations and probabilistic models to sup­
port problem solving utilizing concepts from psychology, logic, and linguistics. 
Crowd sourced, wisdom of the crowds, provides a new method to extract large amounts of relevant 
data from the web on the assumption that large data sets may be more accurate than limited clinical data

data from the web on the assumption that large data sets may be more accurate than limited clinical data 
from the web. An example is IBM’s “Watson” [4] famous for beating experts on the Jeopardy game show, 
based on a crowd-sourcing paradigm. So far, this approach has yet to be validated in the medical arena. 
This crowd-based approach has showed some success on social networking sites, where specific diseases 
are targeted and individuals supply anecdotal data. 
3.10 Summary 
Computer databases have been the foundation of computer systems since the dawn of technology in 
the 1950s. Aggregating medical data, dispersed among numerous databases and stored into standard 
nomenclatures that can be accessed and shared in a secure environment, is the goal of EHRs. There 
are a number of reasons why online medical data lagged behind, such as data privacy, changing mind-
sets of practitioners, cost, technology, will of government agencies to set standards and financing. The

sets of practitioners, cost, technology, will of government agencies to set standards and financing. The 
innumerable advantages of data sharing to prevent duplicate tests, mining data to determine the best 
outcomes of drugs and procedures, tracking excellence or lack thereof in particular medical institu­
tions, preventing disease outbreaks in the early stages, and implantable or wearable medical devices that 
can detect life-threatening conditions before they become acute. We are in the early stages of creating 
a seamless data sharing network similar to ubiquitous cell phones, which can communicate and share 
information seamlessly. The real short-term challenge is to create better user interfaces and minimize 
tedious data entry . W e are on an exciting roller coaster of change with wearable medical devices and 
clothes with embedded medical devices that will change medicine by providing proactive rather than 
reactive medicine. 
Questions 
Level I

Questions 
Level I 
 1. What are the different types of EHR? 
 a.  Explain three unique features of each type of record. 
 b.  What benefits do you see in maintaining these records? 
 2. What sources/organizations provide standards for EHR development? 
 a.  What key areas do EHRs need to address? 
 b.  Explain key components of these core EHR components. 
 3. When entering EHR data, what standard nomenclatures are used to ensure all parties understand 
the clear meaning of the information entered? 
 a. Explain what an entity–relationship diagram is. 
 b.  What is a CDSS? 
 c.  What role does an entity–relationship diagram play in a CDSS? 
 4. Explain, in general, what HIPAA is 
 a. Explain what Tile I and Tile II of HIPAA provides. 
 5.  What is the ARRA?

6. Explain the role of meaningful use criteria in EHR implementation 
 a. 	 Explain the general (meaningful use) features of Stage 1, 2, and 3. 
 b. 	 What are the top three deliverable features (meaningful use) of Stage 2? 
 c. 	 Explain your reasoning. 
 7. What is the purpose of HIEs? 
 a.	  Name the three types of HIEs. 
Level II 
 8. As you navigate an EHR explain the levels of subrecords such as MAR and discharge orders and 
how you perceive a typical interaction might take place, i.e., what sequence of data entry you 
would follow. 
 a. 	 Draw a diagram of how you think a data entry session might progress. 
 b. 	 Explain your reasoning with details. 
Level III 
 9. What is the purpose of a CDSS? 
 a. 	 Explain how the HL7 Arden syntax is used in the development of a CDSS. 
 b. 	 Using the embedded MLM, use the specific format terms provided in Figure 3.20 and write 
a simple CDSS code interaction to define a patient with some authoring, patient informa­

tion, citations, a priority level, and if then, block(s) to suggest treatment option based on 
a patient with moderate blood pressure (systolic/diastolic) 90/130 and high blood pressure 
above 100/150. 
 c. 	 For extra credit, write a working program as a web page using HTML and some scripting 
language (JavaScript, PHP, etc.) and provide the working link to the teacher (this can be done 
in a group if more complex diagnostic choices are added). 
 10. What is a fuzzy data set used in a CDSS? 
 a. 	 Explain what a discontinuity in that data set is. 
 b. 	 Give a specific example different from the textbook example defining the truth values. 
 c. 	 Extra credit: Using the link to Arden HL7 syntax manual, find the section on fuzzy sets and 
use another discontinuity example, nonrectangular, from that manual and explain in detail 
what that would mean in a real-world CDSS example.

 d.	  Link  wiki.hl7.org/images/a/aa/Arden_Syntax_2.10_draft_2014–03–18.docx. 
 11. What is an expert system? 
 a.	  What is an inference engine? 
 b.	  How do an expert system and CDSS differ? Give details. 
 c. 	 Extra credit: Research an expert system, developed after 2010, for a specific medical disease or 
condition. Provide some level of details. 
Glossary 
A  clinical decision support system is software that assists healthcare professionals in making diagnoses,  
treatment decisions, and workflow decisions. 
Continuity of Care Record  is designed as a subset of information focused on timely care of an indi­
vidual either in an emergency situation or provided to another physician focusing on current 
health status, medications, and treatment.

health status, medications, and treatment. 
Cognitive systems are a series of artificial intelligence paradigms with “the ability to engage in abstract 
thought that goes beyond immediate perceptions and actions.” 
Electronic health record * is a collection of health data from multiple sources. This is a more expansive 
term, versus electronic medical record, and refers to all information of the health of the body. 
77 Electronic Health Records

78 Biomedical Informatics 
It is designed to share information among providers and includes all laboratory information 
and specialist data (used almost exclusively by the Office of the National Coordinator for 
Health Information Technology). 
Electronic medical record  is used for diagnosis and treatment, refers to medical treatment and history, 
and is a digital form of a medical chart and often refers to information gathered in a local prac­
tice. (It is often used but electronic health record is the preferred term.) 
Expert systems are computerized applications that combine computer hardware, software, and special­
ized information to imitate expert human reasoning and advice. 
Health information exchange  is the ability to share/exchange medical information across different 
medical records systems ( http://www.healthit.gov/HIE). 
Healthcare Information and Management Systems Society is a global nonprofit organization focused 
on health information technology.

on health information technology. 
Health Level 7 International (HL7)  is a standards organization that provides a framework for medi­
cal data exchange and sharing and standards that software organizations use to ensure data 
interoperability. It’s a nonprofit organization with members that represent a large percent­
age of all electronic health records development organizations. HL7 is an American National 
Standards Institute accredited standard for healthcare. The level 7 refers to the ISO seventh 
level, the highest achievement of software integration and usability of the ISO seven-layer 
models. 
Health Insurance Portability and Accountability Act  o f  1 9 9 6  r e q u i r e d  t h a t  r e q u i r e d  H e a l t h  a n d 
Human Services develop standards for electronic health records (EHR), data interchange, 
security, and unique EHR identifies for records.

security, and unique EHR identifies for records. 
Inference engines  determine which rules match those of the supplied data and match those with the 
highest probabilities. 
International Statistical Classification of Diseases and Related Health Problems (ICD9–10) is a com­
prehensive list by the World Health Organization of diseases, symptoms, etc. Example of some 
of the categories is A00-B99 Infectious and Parasitic Diseases, F00-F99 Mental and Behavioral 
Disorders, I00-I99 Diseases of the Circulatory System. 
International Classification of Diseases and Related Health Problems (ICD10)  is created by the 
World Health Organization. It provides a list of codes, symptoms, diseases, and social 
issues related to disease. It has over 14,000 codes to ensure that medical documents clearly 
refer to similar medical conditions to later be cross-referenced to track epidemics and 
treatment.

treatment. 
Medical logic modules  contain knowledge for a single medical diagnosis decision. 
The Office of the National Coordinator (ONC)  for Health Information Technology is at the forefront 
of the administration’s health information technology efforts and is a resource to the entire 
health system to support the adoption of health information technology and the promotion 
of nationwide health information exchange to improve healthcare. ONC is organizationally 
located within the Office of the Secretary for the U.S. Department of Health and Human 
Services. 
Personal health record  is a personal copy of a patient’s health information so the patient can track, 
maintain, and make informed medical decisions. All doctors are required to provide this 
information upon request. It’s a subset of the electronic health record and usually contains

information upon request. It’s a subset of the electronic health record and usually contains 
personal information, medical tests, diagnoses, medications, allergies, and family history. 
Pharmacy clinical decision support systems  are in widespread use and are usually integrated with 
e-prescription systems. They check drug interactions, contraindications, allergies, dosage 
levels, and report possible side effects and are linked in e-prescribing systems. 
Nationwide Health Information Network also called eHealth Exchange developed by the U.S. Office of 
the National Coordinator (ONC) for Health Information Technology is a series of specifications

79 Electronic Health Records 
to securely exchange health data. The goal of the ONC is to tie together health information 
exchanges to create a nationwide network. 
Regional Health Information Organization , often used interchangeably with a health information 
exchange, is a group of companies, hospitals, or organizations that have developed a system to 
seamless exchange of health information. 
HL7 Reference Information Model  is an object model that provides a pictorial representation of HL7 
clinical data domains. It identifies the life cycle of message groups that are moved between 
domains of the model. 
 1. Berners-Lee, T. (1991). Conseil Européen pour la Recherche Nucleaire, and now the European 
Particle Physics Laboratory, http://www.livinginternet.com/w/wi_lee.htm 
 2. Englebardt, S.P. and Nelson, R. (July 14, 2015). The role of expert systems in nursing and medicine.

2. Englebardt, S.P. and Nelson, R. (July 14, 2015). The role of expert systems in nursing and medicine.  
Anti Essays. From the World Wide Web, http://www.antiessays.com/free-essays/185731.htmlp. P. 137. 
 3. Heckerman, D. and Shortliffe, E. (1992). From certainty factors to belief networks. 	 Artificial 
Intelligence in Medicine  4(1), 35–52. doi:10.1016/0933–3657(92)90036-O. http://research.microsoft.  
com/en-us/um/people/heckerman/HS91aim.pdf. 
 4. Mahn, T. (2010). Wireless medical technologies: Navigating government regulation in the new  
medical age, http://www.fr.com/files/uploads/attachments/FinalRegulatoryWhitePaperWireless  
MedicalTechnologies.pdf 
 5. Langley, P. (2012). The cognitive systems paradigm, CogSys.org 
 6. Morris, G., Silberman, S., and Covich-Bordenick, J. (2011). Report on health information exchange: 
The Changing Landscape. Washington, DC. http://www.cfrhio.org/images/2_2011_Report_on_ 
Health_Information_Exchange_-_Sustainability_Report.pdf

Health_Information_Exchange_-_Sustainability_Report.pdf 
 7. Regenstreif Institute: Indiania School of Medicine.  https://www.regenstrief.org/ 
 8. Why these doctors love their RHIO. Medical Economics, http://www.memag.com/memag/article/ 
articleDetail.jsp?id=182803 
 9. Veterans Administration. (1987). http://www.WorldVistA.org.

Level I: Core Concepts ...................................................................................82
 
4.1 	 Introduction ........................................................................................82
 
4.2 	 Interoperability ...................................................................................82
 
Interoperability: Communications • Medical Classification Systems: 
Medical Vocabularies • Interoperability: Mapping Tools • Medical 
Databases
 
Level II: Application and Theory: Messaging HL7 with Embedded 
SNOMED ........................................................................................... 108
 
4.3 	 Introduction ...................................................................................... 108
 
HL7 Message Architecture • HL7 Message Structure • HL7 Codes in 
Tables • HL7 with Embedded SNOMED CT 
4.4 ICD10 ...................................................................................................112

Level III: Advanced Topics: Mapping Tools ...............................................114
 
4.5 	 Unified Medical Language System ..................................................114
 
UMLS Metathesaurus • UMLS Semantic Network • Lexical Tools 
(Dictionary) 
4.6 	 RxNav ..................................................................................................116
 
4.7 Summary .............................................................................................116
 
Questions ........................................................................................................117
 
Glossary ..........................................................................................................118
 
References .......................................................................................................119
 
4 
Data Interoperability
 
81

82 Biomedical Informatics 
4.1 Introduction
 
The term interoperability implies ubiquitous communication and a clear, precise language where the 
meanings of terms and ideas leave no room for doubt or interpretation. We, as human beings, have 
yet to accomplish this task successfully in our communications. Mathematics is the closest we have 
come to precisely describe some aspects of the universe, but this too is imprecise till we understand the 
entire complexity of space-time, dark energy, and dark matter that comprises approximately 90% of our 
universe, but we still have few clues on its composition. How can we describe the universe precisely if 
we are unsure of its underlying composition? A grand unified field theory that unites strong and weak 
interactions of particles and electromagnetic and gravitational forces into a single series of formulas 
even eluded Einstein. Medical science is evolving, so too is our schema for describing it.

even eluded Einstein. Medical science is evolving, so too is our schema for describing it. 
The medical community, industry, and government have jointly developed a series of standards, namely, 
the International Statistical Classification of Diseases and Health Related Problems (ICD10), Systematized 
Nomenclature of Medicine (SNOMED, medical terminologies), Digital Imaging and Communications in 
Medicine (DICOM, images), Health Level 7 (HL7, communications), National Council for Prescription 
Drug Programs (NCPDP, pharmacy communications), and Institute of Electrical and Electronics 
Engineers (IEEE, electronics), but we rely on an individual’s perception to enter those data. Is their diag­
nosis correct, are their tests conclusive, or is there an unknown disease that we approximate with one that 
fits it best? We can define precise terms but the underlying medical science is evolving; so too is interoper­

ability. These standards are incorporated into electronic health records (EHRs), data definitions of diseases 
and medications, medical transmission protocols, etc. There are currently 600 EHR vendors as of 2014 
(http://www.emrandhipaa.com/emr-and-hipaa/2012/04/11/over-600-ehr-vendors/). Imagine if there were 
600 languages spoken, a tower of Babel of medical terminology. Under the best of circumstances, there 
would be some ambiguity. This chapter will describe the current state of the art, as of 2015, in generating 
medical standards for communicating information and links to the standards organization so you can 
keep abreast of the latest evolution of the science, with the caveat that this is a work in progress. 
Here is the definition of interoperability by the Healthcare Information and Management Systems 
Society (HIMSS):

Society (HIMSS): 
Interoperability means the ability of health information systems to work together within and across 
organizational boundaries in order to advance the effective delivery of healthcare for  individuals 
and communities. 
http://www.himss.org/files/HIMSSorg/content/files/AUXILIOHIMSSInteroperability 
Defined.pdf. 
4.2 Interoperability 
The term interoperability refers to the seamless exchange of information and consistent language and 
meaning. It implies both communications standards such as HL7 and medical vocabularies such as 
the SNOMED and ICD10 and ICD11 that will be released in 2017, so all facets of the healthcare system 
can exchange data with comparable meaning intact (Figure 4.1). Interoperable development tools that 
create the cross terminology mapping between concepts, such as the Unified Medical Language System 
(UMLS), simplify the development process.

(UMLS), simplify the development process. 
The term interoperability can be broken down into three general categories: 
1. Communications refer to the message structure of information transmitted between systems. HL7, 
a communications standards organization, defines its charter as “dedicated to provide a compre­
hensive framework and related standards for the exchange, integration, sharing and retrieval of

HL7 standards
EHR-S
Arden Syntax
FHIR
CCOW
CDA
Virtual medical
Record
Vocabularies:
Common
medical
terminology 
HL7, NCPDP (pharmacy), ISO, IEEE, IHE (International Health Exchange)
1: Communication protocols to facilitate interoperability of electronic health
3: Mapping
tools
-UMLS
-AMA 
SNODENT
(dental) 
ICD10
CMU.S
(68,000)
Disease and
diagnosis 
ICD10
PCS U.S
(78,000)
Procedural
Codes
LOINC
(lab, nursing
documentation) 
DICOM
(imaging, CT,
MRI, xray)
CPT services provided HCPCS codes
and medi-span
-AMIA
-Regenstrief
for reimbursement AMA medicare-medicaid 
Lexi-comp
(Drug reference
and clinical
support) 
IEEE 1073
medical device
-HHS
-NLM
-HL7
-IEEE
-OMG
-ANSI
-UML-F
-OMG SysML
Organizations 
2: Vocabularies/codes 
Lubliner 2015 
ICD11
communication
and personal
medical devices
-HIMSS
-RSNA
-ACC
-ISO
SNOMED CT
(300,000 terms) 
ICD10
(14,000) 
-IHTSDO Health information exchanges (data interoperability EHRs') Caveat: includes dominant interoperability

ICD10
(14,000) 
-EFMI standards, not inclusive of all specifications
 
83 Data Interoperability 
FIGURE 4 .1 Interoperability: communication, terminology, and mapping standards.

MSH always start Electronic Pharmacy Order type (ex nonprescription)Field with a message health order and then end of order delimiter separators header record type ID code 11111 
MSH |^~&| CERNER | Pharmacy | 1234567 | 12345678901234 | 11111 |
 
PID | –| HL7 |–| 00001234 | Smith ^ John || RXO | 0101-10-112 | Tylenol 100 mg | 
Message Patient Field	 Pharmacy Medication order # and Patient ID	 name andstandardseparator order text explanation 
HL7 ID number 
Lubiner 2015 
MSH: Message header Required field
NTE: Is a note or comment Optional and repeatable
PID: Patient identification Required 
PID1: Patient demographics Optional
RXO Phamacy order Optional 
PV1 Patient visit	 Required 
ORC Common order Optional 
|^~& Are component, field separators Required 
  
84 Biomedical Informatics 
electronic health information that supports clinical practice and the management, delivery and 
evaluation of health services” (www.HL7.org).

evaluation of health services” (www.HL7.org). 
a.	 The additional medical communications standards are International Organization for 
Standardization (ISO), Technical Committee (TC) 215 and IEEE 1073.
 2. Vocabularies refer to a set of generally accepted naming standards for disease, symptoms, proce­
dures, epidemiology, etc., to facilitate accurate communications between medical practitioners 
worldwide. SNOMED Clinical Terms (SNOMED CT) is administered by the International Health 
Terminology Standards Development Organisation (IHTSDO), which, owned and governed 
by 27 international members, is “the most comprehensive clinical vocabulary available, in any 
language, with a concept oriented structure that meets the criteria for a well-formed, machine-
readable terminology. HL7 and SNOMED organizations signed an agreement, renewed every two

readable terminology. HL7 and SNOMED organizations signed an agreement, renewed every two 
years,” to “drive harmonization between HL7, SNOMED and the HL7 Reference Information 
Model (RIM)” (http://www.ihtsdo.org). (Reference Information Model [RIM] is an object model 
that displays the HL7 domains as a pictorial representation.) 
a. 	 There are some additional vocabularies: ICD10, DICOM (imaging), Logical Observation 
Identifiers Names and Codes (LOINC, nursing), and Lexicomp (pharma).
 3.	 Mapping tools are used to link different medical vocabularies and concepts. It is used by medical 
informatics developers to generate categories of terms and their relationships. The relationships 
between terms are usually parent–child that form a broader category to a narrower one or one with 
more granularities. Terms are also grouped into broad categories/classifications. Semantic categories 
assist in extracting context and meaning. The UMLS contains approximately five million  concepts–

assist in extracting context and meaning. The UMLS contains approximately five million  concepts– 
names and one million concepts–relationships between names and terms. The U.S. National Library 
of Medicine (NLM, UMLS), the largest medical library, uses UMLS to link to PubMed, which has 
publications of 23 million journals and reference articles. The UMLS defines its charter “to promote 
the creation of more effective and interoperable biomedical information systems and services, includ­
ing electronic health records” (http://www.nlm.nih.gov/databases/umls.html). 
4.2.1 Interoperability: Communications 
This section will focus on electronic medical communications standards between EHRs, medical devices, 
laboratory data, and imaging studies, which have to agree on common protocols to exchange data . The 
message header and content fields, specified by communication protocols such as HL7 (Figure 4.2),

message header and content fields, specified by communication protocols such as HL7 (Figure 4.2), 
FIGURE 4 .2  Health Level 7 (HL7) sample pharmacy, HL7 communications message  between systems.

HL 7 ISO IEEE Organization/
Standards 
Communications 
(Messaging) 
1. TC 215
    (Medical records) IEE 1073 HHS (Health and
Human Services) 
1. EHRs 
2. CCOW (Context
management) 
3. CDA (Clinical
Document Arch.) 
4. Arden 
(a)
(b)
(c)
(d)
(e) 
(f ) 
Data structure 
Messaging
Privacy and security
Health cards 
Devices 
(g) Business requirements
for electronic health 
records 
Pharmacy and
medicine business 
Interoperability of
personal medical
devices 
1. Health 
informatics: point
of care (POC) 
2. Personal health 
devices: Tele-
Health 
NCPDP (National
Council for Prescription) 
HIMSS (Healthcare Infor.
Management Systems
Society) 
IHTDSO (Intern. Health
Terminology Standards
Development Org) 
Syntax (CDSS) 
5. Virtual medical
 Records 
6. FHIR (Fast Health
Interoperable
Resources) 
3. ISO 12052
    DICOM (Medical
    imaging) 
2. ISO/HL7
27931 :2009
    (Medical comm. 
    protocols) 
3. 
4. 
POC devices 
cell phones
integration 
Personal health 
devices: blood

2. ISO/HL7
3. 
4. 
devices: blood 
pressure 
IHE (Integrating the
Healthcare Enterprise) 
RSNA (Radiological
Society of North America) 
NLM National Library Med. 
 
85 Data Interoperability 
ensure that both sending and receiving systems maintain the precise meaning of information. This exam­
ple shows a typical HL7 message structure with some of the fields identifying the EHR vendor CERNER 
and the type of message such as pharmacy order (RXO) and patient identification (PID) [00001234 Smith 
John] and medication order [0101-10-112 Tylenol]. 
4.2.1.1 HL7 
HL7 s
tarted in 1987 (www.HL7.org ). Its charter is to define communication protocols for the seam­
less exchange of electronic health information. HL7 is an open standard, i.e., free and publicly avail­
able (e.g., in the pharmacy industry, the NCPDP is used to ensure communications interoperability

able (e.g., in the pharmacy industry, the NCPDP is used to ensure communications interoperability 
between pharmacy orders [NCPDP.org ]). It’s a nonprofit organization whose members include most 
of the  healthcare vendors worldwide. The standards categories that are maintained by HL7 are listed 
in Table 4.1. The original name aptly borrowed the concept from the ISO seven-layer communications 
standards (Figure 4.3). Layer 7, the highest level, is the application communications exchange protocols, 
as opposed to the other ISO lower hardware communications specifications such as layer 1, physical 
connections between computers; layer 2, data link frames for packaging messages with error checking; 
and layer 3, network that focuses on addressing issues such as IPV6 and routing packets to their correct 
destinations. 
HL7 standards nomenclatures : HL7, a nonprofit organization that started in 1987 and is comprised of

HL7 standards nomenclatures : HL7, a nonprofit organization that started in 1987 and is comprised of 
corporate and medical professionals, sets primarily a communications standard for messaging clinical 
data between systems, but it provides other functional standards for EHRs, decision support systems 
(DSS), etc. (www.HL7 .org). 
This link is the HL7 Master Index of all standards, versions, and documentations ( http://www.hl7. 
org/implement/standards/product_matrix.cfm?ref=nav):
 1. EHR-S Functional Model (FM), Release 2, 2014: “Outlines important features and functions that 
should be contained in an EHR system. Through the creation of functional profiles, this model pro­
vides a standard description and common understanding of functions for healthcare settings. To 
date, HL7 has developed or is developing profiles for areas such as child health, emergency care, 
long term care, behavioral health and vital statistic reporting” (HL7.org definition).

OSI 7 Layer Mo
del 
Application 
Transport 
Internet
NetworkAccess 
a Core standards categories (http://www.hl7.org/implement/standards/product_matrix.cfm?ref=nav). 
8.	 User U l 
p a7. Message format, human machine interfaces p Application header 
e e 
7. Application 
6. Presentation 
y6. Convert into 0’s, 1’s, and encryption Presentation 
header5. Permission and authentication r r 
s Session header 5. SessionT Transport header:r sequencing error CK 4. Transport a 
Network4. Complete end to end error checking transport n TCP 3. Networkheaders3. Network addressing p Packet 2. Data2. Flow control o1. Bits, physical hardware r Frame 1. Physical 
t 
 
86 Biomedical Informatics
TABLE 4.1 HL7 Communications Standards Categories 
HL7a 
1. Primary Structure and semantics of clinical documents to communicate between healthcare providers 
standards (used Point of use CCOW 
most often) Messaging for data exchange 
Specification based on RIM V3

Specification based on RIM V3 
Document markup standard based on structure product labeling specification that is attached 
to any medicine 
Continuity of care fosters interoperability of data by physicians 
2. Foundational Arden syntax for procedural clinical knowledge to share health knowledge databases 
standards DSS that recommends possible treatments; its AI software with embedded rules (see DSS in 
Chapter 3) 
Control data for the contents of each data field 
Service-oriented architecture 
3. Clinical and Messaging standards 
administrative Claims and reimbursements 
domains Genomics 
Drug stability reporting 
4. EHR profiles Child health profiles 
Clinical research profiles 
Behavioral Health Functional Profile 
5. Implementation ANSI orders and observations 
guides Clinical oncology 
Questionnaire assessment 
6. Rules and Arden syntax reference V1.6 
references GELLO version 3

references GELLO version 3 
DSS release 1 
7. Education and Books and guides 
awareness Data access rules/consent 
Quality reporting documents 
FIGURE 4 .3 (See color insert.) ISO seven-layer model. 
2. Context Management Specification ( CCOW): “CCOW is a standard for allowing independent sys­
tems to synchronize context  on a single workstation, providing a seamless interface for the user 
of that workstation (e.g., ensuring consistent user authentication, display of the same patient, 
display of the same order, etc.). In theory, FHIR resources could be used as an alternative CCOW 
implementation technology; however, the business case for doing this is not clear. CCOW profiles

87 Data Interoperability 
include V2 mappings. These mappings can be used to help identify the equivalent FHIR data 
elemen ts when establishing CCOW linkages in FHIR-based systems” (HL7.org definition).
 3.	  Clinical Document Architecture  (CDA):  “The HL7 Version 3 Clinical Document Architecture 
(CDA®) is a document markup standard that specifies the structure and semantics of ‘clinical docu­
ments’ for the purpose of exchange between healthcare providers and patients. It defines a clinical 
document as having the following six characteristics: 1) persistence, 2) stewardship, 3) potential 
for authentication, 4) context, 5) wholeness, and 6) human readability. A CDA can contain any 
type of clinical content—typical CDA documents would be a Discharge Summary, Imaging Report, 
Admission and Physical, Pathology Report  and more. The most popular use is for inter-enterprise 
information exchange, such as is envisioned for a U.S. Health Information Exchange (HIE)” (HL7.

information exchange, such as is envisioned for a U.S. Health Information Exchange (HIE)” (HL7. 
org definition).
 4. 	 Arden syntax  (2.9):  This “is a language for defining decision support rules. These rules make   reference  
to data elements that are used as part of the decision-making process. However, the  specification  
does not define how these data elements are identified. FHIR element and  extension identifiers  
would provide one mechanism for identifying the relevant data elements” (HL7.org definition).
 a.	  GELLO: GELLO is “part of the HL7 Version 3 Normative Edition and is a standard query 
and expression language  that provides a framework for manipulation of clinical data for 
deci sion support  in healthcare. The GELLO language can be used to build queries to extract 
and manipulate data from medical records and construct decision criteria by building expres­
sions to correlate particular data properties and values. These properties and values can then

sions to correlate particular data properties and values. These properties and values can then 
be used in decision-support knowledge bases that are designed to provide alerts and remind­
ers, guidelines, or other decision rules.”
 5.	  Virtual Medical Records : “The Virtual Medical Record is a draft specification under  development 
by HL7 that also  serves the decision support space . It defines a logical medical record that  decision 
support rules can be constructed against. At present, this model is a custom model created 
s pecifically for VMR. However, the Decision Support work group is evaluating the possibility of  
using FHIR as a structure for future versions of the specification.”
 6.	  Fast Healthcare Interoperability Resources  (FHIR): This “is a next generation standards framework 
created by HL7. FHIR combines the best features of HL7’s Version 2, Version 3, and CDA
® product

® product  
lines while leveraging the latest web standards and applying a tight focus on implementability. 
FHIR solutions are built from a set of modular components called ‘Resources.’ These resources 
can easily be assembled into working systems that solve real world clinical and administrative  
problems at a fraction of the price of existing alternatives. FHIR is suitable for use in a wide variety 
of contexts – mobile phone apps, Cloud communications, EHR-based data sharing, server commu­
nication in large institutional healthcare providers, and much more” (hl7.org/fhir). 
4.2.1.1.1 Reference Information Model 
The HL7 RIM is an information model for healthcare development. It’s a graphical representation of HL7 
clinical data and describes the life cycle of messages moving through an EHR. It constitutes a series of

clinical data and describes the life cycle of messages moving through an EHR. It constitutes a series of  
classes composed of entities, roles, participants, relationships, and actions. It is derived based on the 
Unified Modeling Language (UML). (An entity–relationship [ER] diagram is a visual [graphic] tool that 
represents the entities and the relationships between them in a database.) 
An information model is a way of representing relationships, rules, and constraints for a  particular domain,  
for instance, its healthcare delivery. It provides an organized structure of information and  knowledge. In  
data modeling, an information model refers to the properties and operations performed on those entities;  
in this instance, an entity is a patient or service performed.  It provides a formal way of  describing a domain,  
healthcare, mapped to a specific implementation of EHR software. Languages to  implement informational

healthcare, mapped to a specific implementation of EHR software. Languages to  implement informational  
models are ER graphic notations, Integrated Definition Language, UML, etc. (Section 4.5). 
This RIM was introduced to insure consistent and best practices in software development and software  
engineering in the EHR design process . Some of the classifications in the RIM are as follows: An act is

88 Biomedical Informatics 
any procedure, medication, etc. Acts are related through an act relationship. Entities are persons, orga­
nizations, places, devices, etc. The RIM has four main classes: (1) entity, (2) role, (3) participation, (4) act 
(some definitions include two more main classes: role relationship and act relationship). For example, 
subclasses of act are observations and procedures. 
Entity Role Participant Relationship Action 
Green Yellow Blue Pink Red 
Represents an Represents Defines a Represents acts, Central block 
entity playing the role of a participant relationships to and represents
a role participant show how they are an action 
The following are the general concepts when creating an ER class diagram: 
• An entity is something you want to describe or track, for example, any patient or service. 
• A class describes an entity that includes its attributes and behavior, for example, patient treatment.

• A class describes an entity that includes its attributes and behavior, for example, patient treatment. 
• An object is one instance of a class with unique data, for example, John Smith. 
• A property is a descriptor of a class or entity, for example, age and last name. 
• A method is a function executed by a class, for example, add a new patient to the EHR. 
• An association is a relationship between two or more classes. 
The following are examples of identifiers used in a RIM: DEF, a definition of an act;  INT, an intention 
to perform an act;  RQO, a request or order for a service; CNF , confirmation by an order; and EVN, 
an event that happens. A more complete description can be found at https://www.hl7.org/document­
center/public_temp_B669E2A2-1C23-BA17-0C7A999023268366/calendarofevents/himss/2011/HL7%20 
Reference%20Information%20Model.pdf. 
The RIM diagram is color coded based on the entity, role, act relationship key provided earlier 
(Figure 4.4). 
RIM Model Expanded

RIM Model Expanded 
Example: 
An ACT (Class) can be defined
many ways: CODE (CD),
TITLECode(TS), ClassCode(CS) 
An ACTRealationship further
defines the properties of that
class ContextControlCodes 
More details are provided by
Account i.e., billing
BalanceAmount 
Under DIET 
Dietcarbohydratequality (PQ) 
A high-resolution link to RIM can be found in the website http://www.healthintersections.com.au/ 
wp-content/uploads/2011/05/RIM.png.

89 Data Interoperability 
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Standards Description
ISO TC 215 
(a) Working Group 1 
(b
) Working Group 2 
(c) Working Group 4 
(d ) Working Group 5 
(e) Working Group 6 
( f ) Working Group 7 
( g) Working Group 8 
ISO 631 
ISO 3166 
ISO 4217 
ISO 9000/9001 
(a) ISO 9126 
(b) ISO 9451 
(c) ISO 9592 
ISO 12052 
ISO 14000 
ISO 22000 
ISO/HL7 27931:2009 
(a) 27809: 2007 
(b) 27799: 2008 
(c) 21549–7:2007 
(d) 21549–5: 2007 
(e) 21730: 2007 
ISO 31000 
ISO 50001 
Technical Committee on Health Informatics 
(a) Data structure 
(b) Messaging 
(c) Privacy and security 
(d ) Health cards 
(e) Pharmacy and medicine business 
( f ) Devices 
( g) Business requirements for electronic health records 
Language codes 
Country codes 
Currency codes 
Quality management 
(a) Software engineering (functionality, reliability, usability, 
efficiency, maintainability, portability) 
(b) Information technology 
(c) Computer graphics 
DICOM medical imaging (see Chapter 8) 
Environmental management 
Food safety management

Food safety management 
Data exchange standards HL7 
(a
) Health informatics: patient safety 
(b
) Health informatics: information security 
(c) Patient healthcard data: medication 
(d) Patient healthcard data: identification cards 
(e) Use of wireless communication in healthcare setting 
Risk management 
Energy management 
Note: Subset of all ISO categories (http://www.iso.org/iso/home.html). 
Italics are medical standards. 
90 Biomedical Informatics 
4.2.1.2 ISO 
The International Organization for Standardization (ISO) is a standards organization from 130 countries 
established in 1947. “The mission of ISO is to promote the development of standardization and related 
activities in the world with a view to facilitating the international exchange of goods and services, and

activities in the world with a view to facilitating the international exchange of goods and services, and 
to developing cooperation in the spheres of intellectual, scientific, technological and economic activity” 
(http://www.iso.org/iso/home.html). 
Th e  O p e n  S y s t e m s  I n t e r c o n n e c t i o n  ( O S I )  p r o j e c t ,  a t  I S O ,  i s  t h e  s o u r c e  o f  t h e  s e v e n - l a y e r 
communications model, a theoretical 30-year-old standard mainly used in classes, describes 
networking standards, where layer 1 is the simplest (physical) hardware level, for moving binary data 
across networks–wires. Layer 7 is the highest layer, which is the application layer, such as SFTP, for 
secure file transfers. The Transmission Control Protocol/Internet Protocol, which is an actual series of 
protocols, is used and is equivalent to the OSI levels 3 and 4. To gain more insight, refer to the paper 
by Hettick [2].

by Hettick [2]. 
ISO is an international organization that covers standards ranging from quality management, ISO 
9000, to food safety, ISO 22000 (Table 4.2) . This table lays out a representative list of the ISO standards 
categories and subcategories. The two categories that specifically relate to medical records are ISO TC 
215, which specifies communications standards for the seven categories (messaging, privacy, medical 
devices, etc.), and ISO/HL7 27931:2009, which coordinates interoperability standards between the most 
used medical communications protocols ISO and HL7. 
TABLE 4.2  ISO Standards: Some Representative Examples of ISO Standards

91 Data Interoperability 
4.2.1.2.1 ISO TC 215 on Health Informatics 
The ISO TC 215 was set up to focus on EHR communications standards. The HL7 organization works 
closely with the ISO to coordinate efforts. 
Coordination between communications standards organizations ensures standards are  interoperable 
across organizations and borders. In 2008, the Joint International (Initiative) Council, which includes 
the European Standards Organization (CEN) TC 251 (www.cen.edu), HL7, ISO group TC 215 (http:// 
www.iso.org/iso/iso_technical_committee?commid=54960), IHTSDO (www.IHTSDO.org), and  
Clinical Data Interchange Standards Consortium (www.CDISC.org) which all regularly meet to ensure 
coordination between communications standards. 
ISO TC 215 on Health Informatics Categories 
 1.  Messaging and communications
 a.  Architecture
 b.  Device  interfaces
  i.  Clinical messaging
  ii. Device communication
 c.  Methodology 
 d.  DICOM objects (medical imaging)

a.  Architecture
 d.  DICOM objects (medical imaging) 
 2. Health records and modeling 
 a. Transmitting and receiving medical records
 b.  Country identifier 
 c.  Modeling a and b 
 3.  Health concept representation
 a.  Clinical  terminologies 
 b. Concept mapping between diverse EHR systems
 4. Security
 a.  Secure communications
 i.  Confidentiality
 ii. Security  management 
 b.  Public key infrastructure 
 c.  Archiving and backup 
Table 4.3 lists the nine ISO TC 215 EHR working groups. Various organizations are working on similar 
EHR standards, such as HL7, and they coordinate their effort to ensure interoperability. 
4.2.1.3 IEEE 11073 Health Device Communications Standards 
The IEEE Standards Association (SA) develops standards for the interoperability electronic of devices 
(http://standards.ieee.org/). An area of IEEE standards focuses on health IT standards referred to as

(http://standards.ieee.org/). An area of IEEE standards focuses on health IT standards referred to as  
TABLE 4.3  ISO TC 215 Working Groups for EHR Communications 
WG 1 Data structures 
WG 2 Messaging and communications 
WG 3 Health concept representation 
WG 4 Privacy and security 
WG 5 Health cards 
WG 6 Pharmacy and medicine 
WG 7 Devices 
WG 8 Business requirement for EHRs 
WG 9 Standards Development Organization harmonized workgroup for devices

92 Biomedical Informatics 
TABLE 4.4 IEEE 1073 Medical Device Communications Standardsa 
Standard (Last 4 
Digits, Y ear Enacted) Description Link 
Layer (ISO 
Communications Model) 
11073–00101–2008 Health informatics, POC 
medical device 
http://standards.ieee.org/findstds/ 
standard/11073–00101–2008. 
html 
Lower layers 
1073–00103–2012 Health informatics, personal 
health device 
communication for personal 
telehealth devices 
html 
Layers 3 and 4 
1073–10404–2010 Health informatics, personal 
communication (cell 
phones, PCs), pulse oximeter 
html 
1073–10407–2008 Health informatics, personal 
health device, blood pressure 
monitor 
standard/11073–10407–2008. 
html 
Lower layers

monitor 
html 
a These standards statuses are all active as of 2014 (examples) (http://standards.ieee.org/findstds/standard/healthcare_it.html). 
11073 Medical Device Communications Standards, i.e., interoperability of personal medical devices. 
These standards evolve over time (check the IEEE site for the latest active version). They fall into several 
categories: (1) health informatics, point of care (POC); (2) personal health devices, telehealth; (3) POC 
devices, cell phone integration; and (4) personal health devices, blood pressure (Table 4.4). 
4.2.1.4 Integrating the Healthcare Enterprise 
Integrating the Healthcare Enterprise (IHE) ( http://ihe.net/) is a nonprofit organization created by the 
U.S. Healthcare Industry  and the Radiology Group of North America and supported by the HIMSS. It

U.S. Healthcare Industry  and the Radiology Group of North America and supported by the HIMSS. It 
originally focused on the interoperability of health and IT systems and DICOM, which is the standard 
for medical imaging storage such as CT, MRI, and PET scans, and later expanded to incorporate the 
LOINC used to identify medical laboratory observations. IHE, HL7, and LOINC are standards used 
to transmit data between external systems. In order to accurately specify a disease, it’s necessary to 
describe the proper domain: imaging, pharmacy, etc. 
The IHE mission is “to bring together information technology stakeholders and healthcare profession­
als to implement standards for communicating patient information efficiently throughout  healthcare 
facilities, large and small” (http://ihe.net). 
The Healthcare Industry regularly holds seminars to ensure that medical devices and systems are

The Healthcare Industry regularly holds seminars to ensure that medical devices and systems are 
interoperable, i.e., able to seamlessly share data. The current standards incorporated into the IHE stan­
dards are given in Table 4.5: 
An example of IHE laboratory data sharing message is illustrated as follows. They include 
Laboratory Code Set Distribution (LCSD) for testing and observation codes. For example, LAB-51 
code set, based on HL7, such as MFN.M10, includes standard batteries of tests used in standard clini­
cal environments. 
A message might look like this: a battery of tests requested in the emergency room (department) 
MFN^M10/[OM5]/MSH|^~\&|OF|LabSystem|OP||20050205094510||MFN^M08|2106|2.5|||NLD|MFI| 
OMA|OF_OMA_NL_20050205|REP||| ER| 
with the codes 
OM1–2 producer’s service/test/observation ID 
OM1–4 specimen required 
OM1–5 producer ID/OM5, battery of tests 
OM1–18 nature of service/test/observation

Categories Description Link 
Anatomic Anatomic pathology laboratory data and imaging 
pathology systems. 
Cardiology Sharing information in cardiology clinical domain. 
The test includes cath labs, echocardiography, 
ECG, stress tests, and implantable cardiac devices. 
Dental Secure exchange of dental images. 
Eye care Eye evaluations, cataract surgery. 
IT Working group started by the HIMSS specifying an 
infrastructure IT integration framework for implement systems 
to support EHRs and communications. 
Laboratory Specific laboratory test codes supported by HL7 
such as the LCSD. 
Patient care Patient care across providers, document sharing, 
coordination order processing. 
Patient care Integrating patient care devices into electronic 
devices medical records. 
Pharmacy Codes for transmitting pharmacy data; PRE 
pharmacy prescriptions, DIS pharmacy 
dispensing, HMW hospital medication workflow, 
PADA pharmacy advice. 
Radiology Nuclear medicine images. Mammography

Radiology Nuclear medicine images. Mammography 
Radiation (MAMMO), XDS1 (cross image document 
oncology sharing etc.). 
http://ihe.net/Anatomic_Pathology/ 
http://ihe.net/Cardiology/ 
h
ttp://ihe.net/Dental/ 
http://ihe.net/Eye_Care/ 
http://ihe.net/IT_Infrastructure/ 
The It infrastructure White Paper 
http://www.ihe.net/Technical_Framework/upload/ 
IHE_ITI_White-Paper_Enabling-doc-sharing­
through-IHE-Profiles_Rev1-0_2012–01–24.pdf 
http://ihe.net/Laboratory/ 
http://ihe.net/Patient_Care_Coordination/ 
http://ihe.net/Patient_Care_Devices/ 
http://ihe.net/Pharmacy/ 
http://ihe.net/Radiology/ 
http://ihe.net/Radiation_Oncology/ 
 
93 Data Interoperability 
TABLE 4.5 IHE Standards Categoriesa 
a Improve information sharing. 
The IHE utilizes healthcare and industry participation to improve communications and interoperability

The IHE utilizes healthcare and industry participation to improve communications and interoperability 
between systems. They work with the HL7, DICOM, NCPDP (pharmacy), and other standards organiza­
tions to improve EHR communications. The IHE has a four-step development methodology: (1) Experts 
define use cases for data sharing. (2) They optimize the process creating standards. (3) They work with 
EHR companies to implement these standards. (4) They evaluate the effectivity of these protocols under 
IHE supervision (Figure 4.5). 
ITI Labortory profiles profiles 
Blood Care providers Clinical Laboratories
 
Security specimen (care settings, Management Automation
 Laboratory Code Set Distribution (LCSD)collection ambutatory providers) Laboratory Testing Workflow (LTW)ATNA rooms LCSD: sharing lab tests code set Laboratory Point of Care Testing (LPOCT)CT Sharing Laboratory Reports (XD-LAB)

Patient LTW: tests performed in hospital lab Inter Laboratory Workflow (ILW) administration LPOCT: point of care testing
 
PAM
 Audit Trail and Node Authentication SecurityLDA: 
PDQ LBL: specimen containers robotized distribution laboratory (ATNA) for protecting patient confidentiality
automation Patient Administration Management (PAM)
ILW: to share accurate patient demographic dataDocument lab to lab LAW: Cross Enterprise Document Sharing (XDS)sharing workflow laboratory
analytical standards for sharing medical documentsXDS XD-LAB: CDA Lab report workflow across the enterprise 
XDM 2011 
XDR 
FIGURE 4 .5 Integrating the Healthcare Enterprise laboratory data sharing guidelines. (From http://wiki.ihe.net / 
index.php?title=Laboratory.)

NCPDP prescription Message Header 
Sender ID 
Segment 
Identifier 
Segment 
Identification Version 
 Batch 
No. 
Ref. Number Group Indicator 
Explanation of NCPDP Message Header Fields 
Batch Header Record 
 NCPDP Data 
 Dictionary 
Name 
Field 
Number Definition of Field Format 
Valid 
Values Copybook 
Starting  
Position 
Ending 
Position 
Sender ID* 880-K1 Identification number 
assigned to the 
sender of the data by 
the processor of the 
data. 
X(24) NCPKFLAT 1 24 
Segment 
Identifier* 
701 Unique record type 
 required on Batch 
X(02) 00 =File 
Header 
NCPKFLAT 25 26 
Standard. 
Segment 
Identification* 
111-AM Identifies the segment 
in the request record. 
 This field is only 
populated on records 
with Segment 
Identifier G1. 
X(02) Spaces NCPKFLAT 27 28 
Version*
1 N/A Represents the current 
version of VIPs 
X(01) A NCPKFLAT 29 29 
NCPDP software 
that is being used. 
Batch Number* 806-5C Number assigned by 
processor. Matches 
trailer record

trailer record 
9(07) NCPKFLAT 30 36 
Reference 
Number* 
880-KS  Number assigned by 
 provider to each 
 transaction record. 
X(10) Spaces NCPKFLAT 37 46 
This number is  
unique to each set of  
 flat file records that 
 represent a single 
 claim. This field is 
only populated on  
records with Segment  
 Group 
Indicator*
1 
N/A  This field is used to 
 indicate a group of 
related segments. 
These segments 
together represent 
 the equivalent of 
1 claim per line. 
 This field is only 
Identification ‘07’ 
X(01) N NCPKFLAT 47 47 
(claim segment). 
94 Biomedical Informatics 
TABLE 4.6 NCPDP Pharmacy Transmission Header, to Standardize Communications

Finding site 
classification systems. 
Interoperability 2: Vocabularies/Codes 
SNOMED CT 
concept 
Is a Is a Is a 
Body structure Clinical finding Organism 
Is a Is a Is a 
Pneumonia 
Is a 
Lung structure Finding site Infective 
pneumonia 
Is a 
Bacterial Causative agent Bacteria 
pneumonia 
 
95 Data Interoperability 
4.2.1.5 NCPDP (Pharmacies) 
The NCPDP has created templates for pharmacy telecommunications regarding what should be shared 
between pharmacies and payers (http://www.ncpdp.org/pdf/200903HIPAA_Implementation_v2.pdf). 
The Health Insurance Portability and Accountability Act (HIPAA), document 5010, through the 
Department of Health and Human Services has certified pharmaceutical transaction version D.0, effec­
tive January 2012, which coincides with the mandates that physicians should use e-prescriptions, i.e., all 
scripts should be sent electronically to pharmacies to reduce errors (Table 4.6).

scripts should be sent electronically to pharmacies to reduce errors (Table 4.6). 
The HIPAA of 1996 specified that a single standard be used to submit pharmacy claims in NCPDP for­
mat (http://www.cms.gov/Medicare/Billing/ElectronicBillingEDITrans/downloads/NCPDPflatfile.pdf ). 
4.2.2 Medical Classification Systems: Medical Vocabularies 
In order for two medical practitioners to accurate communicate, they have to agree on similar terms to 
describe a disease, procedure, or patient observation. Even with that level of synchronization, slight varia­
tions in wording may obscure meaning. Medical vocabularies/classification systems incorporate thesauri 
referred to as metathesauri, similar to those available in Microsoft Word, which take those potential word­
ing variations and replace it with a universally accepted term. In addition, the commonly used classifica­
tion systems, such as SNOMED and ICD10, collaborate to produce cross system equivalencies.

tion systems, such as SNOMED and ICD10, collaborate to produce cross system equivalencies. 
Another important aspect to document is the context of the condition. These can be provided by 
attribute relationship hierarchy diagrams (see Figure 4.6) . If a bacterium is found, what is the site of 
the infection and what is the specific strain? No single code may reflect this information. So the docu­
mentation system may provide a series of targeted questions; SNOMED CT has that feature to provide 
a graphical display of the context: 
SNOMED context → Body structure → Lung → Bacterial pneumonia → Bacteria 
New medical relationships between causative agents can be constructed with the UMLS tools 
(Section 4.5), which provide not only cause–effect relationships but linkages between different medical 
FIGURE 4 .6 Systematized Nomenclature of Medicine attribute relationship hierarchy. International Health

FIGURE 4 .6 Systematized Nomenclature of Medicine attribute relationship hierarchy. International Health 
Terminology Standards Development Organisation SNOMED CT User Guide. (From http://ihtsdo.org/fileadmin / 
user_upload/doc/download/doc_UserGuide_Current-en-US_INT_20130731.pdf.)

SNOMED CT
(IHTSDO)
Largest 300,000+
concepts
SNOMED entity
Relationship
SNOWDENT
(Dentistry)
DICOM (Imaging) 
ICD
World Health
Organization (WHO)
 
ICD10 (11 arrives in 2015)
ICD Clinical
Modification (CM) US
ICD10 Procedural Coding
System (PCS) US.
LOINC Logical
Observation Identifier
Names and Codes
 
RELMA Regenstrief
Mapping Assistant
 
CPT
Current procedural
terminalogy codes
Coding medical
procedures identifying
services provided used
for billing for insurance
companies AMA
HCPCS
codes used by Medicare
and Medicaid
 
Lexi-Comp and
Medi-Span
NDC
The National Drug Code
 
RxNorm
(Names Clinical Drugs)
Links Drug Databases
 
National Drag File (NDF)
Medispan (previous name
Lexicomp)
 
MicroMedex
 
Gold Standard
First Data Bank (FDB)
formerly NDDF
 
National Drug Code (NDC)
RxNav
Linkages between
RxNorm and NDC
 
96 Biomedical Informatics

97 Data Interoperability 
4.2.2.1 SNOMED CT 
The SNOMED CT is the most comprehensive international medical classification available as of 2013; 
it had 300,000 medical codes to support medical documentations. It began in 1965 as Systematized 
Nomenclature of Pathology, which evolved beyond just pathology into SNOMED Reference Terminology 
( R T ) .  I n  1 9 9 9  S N O M E D  R T  m a i n t a i n e d  b y  t h e  C o l l e g e  o f  A m e r i c a n  P a t h o l o g i s t s  m e r g e d  w i t h  t h e 
United Kingdom’s Clinical Terms Version 3, formerly known as Read Codes, to create SNOMED CT. 
The current version is now administered by the IHTSDO, a multinational effort. These codes map to 
other classification systems such as ICD10, HL7, LOINC, DICOM, and ANSI and are available in numer­
ous languages. 
SNOMED Data Architecture 
1. Concept identifier, a unique medical code 
2. Hierarchies from general to specific 
3. Human readable terms → concepts with synonyms

3. Human readable terms → concepts with synonyms 
a. 1 million English terms linked to foreign language descriptions
 b. 300,00+ concepts 
4. Relationships, link concepts
 a. Relationship, link concept to a more general concept 
b. Type of relationship that has causative agents, viral pneumonia → virus → lung 
c. 1+ million relationships 
SNOMED CT codes are affected by the context. For example, the breast cancer codes indicate potential 
sources: either from a family history , a cancer in remission, or a new diagnosis. Each code indicates 
the context in which it is described. These contexts have different SNOMED codes. Similar to context 
modifiers, axis modifiers are modifiers that can change the meaning or type of a procedure or clinical 
finding. An example of a modifier is (needle) biopsy for a procedure. Other types of biopsy modifier 
codes specify alternate biopsy techniques (Table 4.7).

codes specify alternate biopsy techniques (Table 4.7). 
SNOMED CT creates hierarchies between medical concepts to illustrate attribute relationships where 
causative agents relate to physical structures, symptoms, and diseases (see Figure 4.6). 
4.2.2.1.1 International Health Terminology Standards Development Organization 
The IHTSDO is a nonprofit organization in Denmark. It owns SNOMED CT ( http://www.ihtsdo.org/). 
The following is the IHTDSO charter: 
The IHTSDO seeks to improve the health of humankind by fostering the development and use of suit­
able standardized clinical terminologies, notably SNOMED CT, in order to support safe, accurate, and 
TABLE 4.7 SNOMED CT ER Attributes 
Attribute Values  	 Example 
Clinical finding | 404684003	 Seizure disorder had definitional manifestation, seizure finding 
Hypertensive disorder | systemic arterial disorder 
Has definitional manifestation, finding of increased blood pressure 
Clinical finding | 404684003 Family history of stroke

Clinical finding | 404684003 Family history of stroke 
Event | 272379006 Associated finding cerebrovascular accident (disorder) 
Procedure | 71388002 
Anatomical or acquired body structure | 442083009 Procedure on colon, procedure site colon structure 
Substance | 105590001 Protein measurement procedure 
Observable entity | 363787002 Component | protein (substance) 
Cell structure | 4421005 
Organism | 410607006

98 Biomedical Informatics 
effective exchange of clinical and related health information. The focus is on enabling the implementa­
tion of semantically accurate health records that are interoperable. Support to association members and 
licensees is provided on a global basis allowing the pooling of resources to achieve shared benefits. 
4.2.2.1.2 Systematized Nomenclature of Dentistry 
A U.S. government mandate for universal EHR implementation by 2015 will require that all of a patient’s 
medical and dental records  b e  a v a i l a b l e  i n  a n  e l e c t r o n i c  f o r m a t if the provider is a participant in a 
Medicare or Medicaid incentive program . Eventually, the EHR mandate may be extended to all provid­
ers (https://www.aaoinfo.org/news/2014/01/electronic-health-records-implementation-aao-representa­
tives-ensure-orthodontic). 
Dentists and orthodontists who either have a small number of patients or have no Medicare and

Dentists and orthodontists who either have a small number of patients or have no Medicare and 
Medicaid patients are currently not affected by the reimbursement penalties for not submitting bills in 
electronic format. These rules are evolving but as of 2014, no dental requirement for EHR or electronic 
dental record (EDR) has been specified. 
The American Dental Association (ADA) has been working, since 2007, on the Systematized 
Nomenclature of Dentistry (SNODENT) to standardize terminology in the dental field, similar to 
SNOMED  (http://www.ada.org/en/member-center/member-benefits/practice-resources/dental- informatics/ 
snodent). 
1. Provides standardized terms for describing dental disease 
2. Captures clinical detail and patient characteristics 
3. Permits analysis of patient care services and outcomes 
4. Is to be interoperable with EHRs and EDRs 
5. Updates added in 2014 
a. 	 Eliminated the “Not Otherwise Specified” (NOS) designation.

a. 	 Eliminated the “Not Otherwise Specified” (NOS) designation. 
b.	 Identified “frequently used terms” and added terms from the ADA health history form. 
c. 	 The ADA has also developed a new numeric codes. 
d.	 Assigned concepts to hierarchies. 
e.	 Reviewed descriptions that were assigned to the concepts. 
f.	 Reviewed synonyms for the concepts. 
g. 	 Developed a crosswalk from SNODENT to ICD9 and ICD Clinical Modification (CM) ver­
sion 10 (ICD10 CM). 
4.2.2.2 ICD10 and ICD11 in 2015 
ICD10 version 10, schema circa 2013, which has 14,000+ codes and subcategories, is a medical classifi­
cation list of diseases, symptoms, diagnoses, health management, and epidemiologies created by the 
World Health Organization (WHO). The WHO constitution mandates “the production of international 
classifications on health so that there is a consensual, meaningful and useful framework which gov­

ernments, providers and consumers can use as a common language.” An internationally agreed-upon 
standard aids in the interpretation and comparison of medical data (see Section 4.4 for more details). 
This list can be expanded by using subcodes related to other disease categories. The online browser is 
available in 43 languages ( http://apps.who.int/classifications/icd10/browse/2010/en). For example, most 
countries use International Classification of Diseases (ICD) to report mortality rates, i.e., maternal mor­
tality rates per 100,000 live births (Figure 4.7), which is an indicator of general health conditions in that 
region. SNOMED CT and UMLS integrate ICD10 libraries to ensure compatibility. 
4.2.2.2.1 ICD11 
ICD11 is currently under development, based on user inputs and needs, and the first version will be

ICD11 is currently under development, based on user inputs and needs, and the first version will be 
available in 2017 (http://www.who.int/classifications/icd/revision/icd11faq/en/index.html).

TABLE 4.8 ICD10 CM U.S. Coding System Example 
Second Three Seventh Character 
Classification First Three Characters (1,2,3) Characters (4,5,6) (Example D or G) 
External causes • V00-X58, accidents • 79.0, 79.1 A fracture • D subsequent encounter for 
of morbidity • V10-V19, pedal cyclist designated as closed fracture with routine healing 
injured in transport accident • 82.0 open fractures • G subsequent encounter for 
• 	 V20-V29, motorcycle rider fracture with delayed healing 
injured in transport accident 
Example, 	 V20 82.0 D 
seven-digit code 
99 Data Interoperability 
3 
10 
30 
100 
300 
1000 
FIGURE 4 .7 International Statistical Classification of Diseases and Health Related Problems report: infant mor­
tality rates per 100,000 as of 2010. (Maternal mortality: Fact sheet N°348. World Health Organization.) 
The following are the new features of ICD11 (WHO): 
1. ICD11 revision process allows for collaborative web-based editing that is open to all interested

1. ICD11 revision process allows for collaborative web-based editing that is open to all interested 
parties. To assure quality, it will be peer reviewed for accuracy and relevance. 
2. It will be free to download online for personal use (and in print form for a fee). 
3. It will be available in multiple languages. 
4. Definitions, signs and symptoms, and other contents related to diseases will be defined in a struc­
tured way so it can be recorded more accurately. 
5. It is compatible with electronic health applications and information systems. 
4.2.2.2.2 U.S. ICD Clinical Modification 
ICD10 CM is maintained by the Centers for Medicare and Medicaid Services (CMS) and is a U.S. 
n a ti o n al  c o d e  th a t  p r o vi d e s  m o r e  d e tail  th an  th e  WH O ’ s  I C D 1 0 ,  wi th  6 8 , 0 0 0  c o d e s .  I t  p r o vi d e s 
a disease and diagnosis code set that lists the causes for hospital or medical interventions. The

a disease and diagnosis code set that lists the causes for hospital or medical interventions. The 
codes are in the form of 3–7 digits, wherein the seventh digit provides detail not available in ICD10 
(Table 4.8): 
• 	 ICD10 CM: U.S. National Code provides more detail with 68,000 codes. 
• 	 ICD10 PCS (ICD10 Procedural Coding System): U.S. (exclusively) procedural code has 76,000 
codes.

1. Medical and surgical (Section O) 9. Other procedures 
31 body systems (med-surg.) 
Central nervous Subcutaneous tissue 
and fascia 
Peripheral nervous Muscles 
Heart and great vessels Tendons 
Upper arteries Bursae and ligaments 
Lower arteries Head and facial bones 
Upper veins Upper bones 
Lower veins Lower bones 
Lymphatic and hemic Upper joints 
Eye Lower joints 
Ear, nose, sinus Urinary 
Respiratory Female reproductive 
Mouth and throat Male reproductive 
Gastrointestinal (body system D) Anatomical regions, 
Body part Approach Device Qualifier general 
F large intestine O open Z no device X diagnostic 
Hepatobiliary and pancreas Anatomical regions, 
upper extremities 
Endocrine Anatomical regions, 
lower extremities 
Skin and breast 
2. Obstetrics 10. Chiropractic 
3. Placement 11. Imaging 
4. Administration 12. Nuclear medicine 
5. Measurement and monitoring 13. Radiation oncology 
6. Extracorporeal assistance and performance 14.  Physical rehabilitation and

6. Extracorporeal assistance and performance 14.  Physical rehabilitation and 
diagnostic audiology 
7. Extracorporeal therapies 15. Mental health 
8. Osteopathic 16. Substance abuse treatment 
a http://www.cms.gov/Medicare/Coding/ICD10/Downloads/pcs-slides-2013.pdf. 
100 Biomedical Informatics 
4.2.2.2.3 U.S. ICD10 Procedure Coding System 
The U.S. PCS is maintained by the Center for Medicaid and Medicare Services (CMS) which provides a 
procedure classification system with 78,000 codes that is not included in ICD10 CM (http://www.cms. 
gov/Medicare/Coding/ICD10/Downloads/pcs-slides-2013.pdf) (Table 4.9). 
It provides
 1. Standardized terminologies 
2. Multiaxial definitions in which each character has the same meaning within and across sections 
3. No diagnostic information; that is, the information is in ICD10 CM 
4. Terms not classified that are used for new devices and substances

4. Terms not classified that are used for new devices and substances 
5. Definitions for all substantially different procedures 
6. Codes in the form of seven digits, that is, in letters A–Z and numbers 0–9 
(Letters O and I excluded so as not to be confused with numbers 0 and 1) 
TABLE 4.9 ICD10 PCS Terms and Coding Example 
ICD10 PCS System Structure (16 Sections)a

101 Data Interoperability 
4.2.2.3 LOINC 
LOINC is a coding scheme used in laboratories for clinical observations  and in nursing for diagnosis, 
interventions, outcomes, and patient care  that facilitates interoperability of clinical observations 
between EHR systems ( http://loinc.org /). It creates different codes for each test, measurement, 
or observation that has a clinically different meaning. As of 1999, LOINC has been recommended 
for transmitting laboratory and clinical observations in HL7 messages. A free license is available at 
http:loinc.org/terms-of-use . 
The LOINC codes distinguish a given observation (test ordered/reported, survey question, clinical 
document) across six dimensions called “parts”:
 1. Component
 2. Property
 3. Time
 4. System (specimen)
 5. Scale 
6. Method (manual count) 
LOINC provides the question and SNOMED CT provides the answers. LOINIC provides nursing observa­

5. Scale 
tions that lead to the final classification provided in the SNOMED or ICD10 code. It also provides a more 
detailed series of events that lead to the eventual diagnosis creating a trail of clues that can be reviewed later. 
The following are examples from observations/discrete measurements/collections from a lab test: 
1. Lab tests such as glucose in urine (mg/dl) and complete blood count 
2. Measurements of a patient, for example, weight and height 
3. Questions on a form: can you move your arm/range 
4. Clinical measurements such as temperature 
5. Documents, that is, intake or discharge summary 
The OBX-4 slot, in a HL7 message, allows two sets of triplets: one for your local concept and the other for 
the concept from the vocabulary standard (LN indicates a LOINC coding system). 
4.2.2.3.1 Regenstrief LOINC Mapping Assistant

4.2.2.3.1 Regenstrief LOINC Mapping Assistant 
The Regenstrief LOINC Mapping Assistant (RELMA) is a search tool for the LOINC clinical database 
(http://search.loinc.org). It provides utilities to map codes between LOINC and other clinical libraries. It 
provides a ranked list of terms. 
To search for specific LOINC codes, go to http://search.loinc.org 
Example: If you entered HEMOTOCRIT at the aforementioned search site: Search Results: 
LOINC LongName 
4544 3 Hematocrit (volume fraction) of blood by automated count 
20670 8 Hematocrit (volume fraction) of blood 
31100 1 Hematocrit (volume fraction) of blood by impedance 
4.2.2.4 RxNorm 
RxNorm provides standardized names for clinical drugs by referencing a number of pharmaceutical 
libraries produced by the NLM (http://www.nlm.nih.gov/research/umls/rxnorm/). It is similar to the

libraries produced by the NLM (http://www.nlm.nih.gov/research/umls/rxnorm/). It is similar to the 
Metathesaurus in the UMLS that references numerous drug-naming conventions and creates an agreed-
upon naming convention (Table 4.10). 
4.2.2.5 NDC 
The National Drug Code (NDC) is maintained by the Food and Drug Administration (FDA) and was 
mandated by the U.S. Federal Government in 1972 by the Drug Listing Act. It requires the FDA “list

102 Biomedical Informatics 
TABLE 4.10 Drug Databases That Are Referenced by RxNorm 
RxNorm Clinical Drug Library (Repository Linking Numerous Pharmaceutical Databases Listed) 
Database Description Link 
National Drug File Provides standard nomenclatures for drugs 
for the Department of Veterans Affairs 
http://www.va.gov/vdl/documents/ 
Clinical/Pharm-National_Drug_File_ 
(NDF)/psn_4_tm_r0206.pdf 
Medi-Span (previous 
name Lexicomp) 
Drug reference guide that provides 
prescription drug information and 
adverse effects to medical professionals 
http://www.medispan.com/ 
Micromedex Provide reference information on 
symptoms and treatments of diseases 
http://www.micromedex.com/ 
Multum Provides consumer drug information and 
side effects and provides a drug insert 
in prescriptions (sources CDC and 
WHO) 
http://www.drugs.com/mtm/ 
Gold Standard Drug reference and patient information 
and alternative therapies 
http://www.goldstandard.com/product/ 
drug-reference-patient-education/

drug-reference-patient-education/ 
First Data Bank (FDB), 
formerly NDDF 
Drug information designed to integrate 
with EHRs 
http://www.fdbhealth.com/ 
fdb-medknowledge/ 
NDC FDA list of drugs that include the 
manufacturer and packaging codes 
http://www.accessdata.fda.gov/scripts/ 
cder/ndc/default.cfm 
of all drugs manufactured, prepared, propagated, compounded, or processed by it for commercial dis­
tribution. All drug products are identified and reported using a unique, three-segment number, called 
the National Drug Code (NDC), which serves as a universal product identifier for drugs” (http://www. 
fda.gov/Drugs/InformationOnDrugs/ucm142438.htm). The NDC is a 10-segment code for all drugs 
(Figure 4.8). 
4.2.2.6 RxNorm versus NDC 
The NDC numbers are more complex to read than RxNorm, which creates a standardized name from

The NDC numbers are more complex to read than RxNorm, which creates a standardized name from 
multiple databases, i.e., a thesaurus of names referencing the same data. NDC contains the manufac­
turer labeler, product code, and packing information in a 10–11-digit code (manufacturer’s name), which 
is essential as part of the required labeling on medicine containers. Two manufacturers will have dif­
ferent codes for the same medication. Also, packaging information for the same medication creates 
additional code variation. 
When EHRs reference a medication, the RxNorm value provides a standard reference term with no 
duplicate entries that may be available with the NDC numbers. But RxNorm, after generating a generic 
reference term with them, contains linkages to the multiple NDC codes (Figure 4.9). 
RxNorm: acetaminophen 500 MG oral tablet 
The National Institutes of Health (NIH) states the following:

The National Institutes of Health (NIH) states the following: 
RxNorm’s standard names for clinical drugs and drug delivery devices are connected to the varying 
names of drugs present in many different controlled vocabularies within the Unified Medical Language 
System (UMLS) Metathesaurus, including those in commercially available drug information sources. 
These connections are intended to facilitate interoperability among the computerized systems that record 
or process data dealing with clinical drugs. 
4.2.2.7 Current Procedural Terminology Codes 
Current Procedural Terminology (CPT) codes are used for coding medical procedures and identify­
ing services provided that are used for billing by insurance companies. It is a U.S. code created by 
the American Medical Association. (In contrast, ICD10 codes focus on the diagnosis of diseases)

Local code Local name Code system LOINC code LOINC name Code system 
4 statement num 
OBX l 4 l NJ l 0123 ^ABC ^HSP_A ^26453-2 ^ Erythrocytes [#volume] ^LN l 3.95/ML l l l l F I
OBX l 5Nl J l llll F I 
(a) 
Row # Row # 
US Version SI Version Lonic Long common name Description of change 1.1 1.1 
1443 1457 38390-1 Cryptococcus neoformans Ag (presence) in Deprecated term. LOINC 38390-1 replaced with 31788-3,
Cerebral spinal fluid Cryptococcus sp Ag (presence) in cerebral spinal fluid 
742 745 40844-3 Immunoglobulin light Deprecated term. LOINC 40844-3 replaced with 48378-4,
chains.kappa.free/immunoglobulin light Immunogolobulin light chains.kappa.free/immunoglobulin
chains.lambda (mass rstio) in serum light chains.lambda.free (mass ratio) in serum 
1846 1860 48577-1 HFE gene p.G845A (presence) in blood or Deprecated term. LOINC 48577-1 replaced with 21695-2,
tissue by molecular genetics method HFE gene p.C282y (presence) in blood or tissue by
molecular genetics method

molecular genetics method 
1444 1458 5119-3 Cryptococcus neoformans Ag (titer) in Deprecated term. LOINC 5119-3 replaced with 9820-2,
serum by latex agglutination Cryptococcus sp Ag (titer) in serum by Latex 
agglutination 
1801 1815 9785-7 Microscopic observation (identifier) in Deprecated term. LOINC 9785-7 replaced with 10704-5,
stool by ova and parasite preparation Ova and parasites identified in stool by light microscopy 
(b) 
Entity that
labels the drug Product code Packaging information
National drug code (Bayer) (aspirin) (50 tablets) 
NDC 0123 1742 02
(c) 
 
103 Data Interoperability 
FIGURE 4 .8 (a) Logical Observation Identifiers Names and Codes (LOINC) code imbedded in a Health Level 
7 message. (From https://loinc.org/get-started/02.html .) (b) LOINC codes. (From http://loinc.org/usage/obs /

7 message. (From https://loinc.org/get-started/02.html .) (b) LOINC codes. (From http://loinc.org/usage/obs / 
introduction-to-the-mappers-guide-for-the-top-2000-plus-loinc-laboratory-observations.pdf.) (c) Food and Drug 
Administration National Drug Code, 10–11-digit, three-segment code for drugs. 
NDC code 
000043-0245-92 
RxNorm 
acetaminophen 
000603-3881-02 
068788-3883-*3 
Explanation 
Acetaminophen 325 mg/
oxycodone hydrochloride
7.5 mg oral tablet
(percocet) 
Acetaminophen 500 mg/
hydrocodone bitartrate 5
mg oral tablet
(hydrocodone)
Acetaminophen 750 mg/
hydrocodone bitartrate 7.5
(hydrocodone) 
FIGURE 4 .9 RxNorm linkages to the numerous National Drug Code product codes.

104 Biomedical Informatics 
provided (http://www.ama-assn.org/ama/pub/physician-resources/solutions-managing-your-prac­
tice/coding-billing-insurance/cpt.page). 
Single and “pseudo” single bill 
data for CPT code 78492 
CY 2011 final 
rule data 
CY 2012 proposed 
rule data 
CY 2012 final 
rule data 
Median line item CCR 0.1708 0.1350 0.1272 
Median line item charge 3,858.75 4,051.70 4,051.70 
Median line item cost ($) 649.85 539.07 492.02 
Median packaged cost ($) 391.06 327.69 273.43 
Hospitals reporting 48 60 64 
Single bills 3,910 8,617 9,727 
Total frequency 5,922 10,531 11,912 
In the table three significant observations are noted for CPT code 78492, which is the myocardial PET 
imaging service ( https://www.federalregister.gov/articles/2011/11/30/2011–28612/medicare-andmedicaid­
programs-hospital-outpatient-prospective-payment-ambulatory-surgical-center): 
• 	 A bill from a doctor will have CPT codes.

• 	 A bill from a doctor will have CPT codes. 
• 	 If you use Medicare, you will receive Healthcare Common Procedure Coding System (HCPCS) 
codes. 
• 	 Codes with letters and numbers most likely will be ICD9–ICD10 codes. 
The CPT codes are broken down into three categories: 
1. Category I is for vaccines: 
a. Updates released twice a year (in January and July). 
b. Emergency releases, to respond to crises, which can be made available any time 
2. Category 2 is for performance measurement, the purpose of which is to minimize the administra­
tive burden on physicians and other healthcare professionals, hospitals, and entities seeking to 
measure the quality of patient care. 
3. Category III is for
 a. Services
 b. Procedures
 c. Emerging technologies 
4.2.2.7 .1 Healthcare Common Procedure Coding System Codes 
HCPCS codes are the billing codes used by Medicare and monitored by CMS. They are based on the

HCPCS codes are the billing codes used by Medicare and monitored by CMS. They are based on the 
CPT codes. 
CY 2011 
HCPCS code 
CY 2012 
HCPCS code CY 2012 long descriptor 
Final CY 2012 
status indicator 
Final CY 
2012 APC 
C9280 J9179 Injection, eribulin mesylate, 0.1 mg G 1426 
C9281 J2507 Injection, pegloticase, 1 mg G 9281 
C9282 J0712 Injection, ceftarolin fosamil, 10 mg G 9282 
C9729 0275T Percutancous laminotomy/laminectomy 
(intralaminar approach) for decompression of 
neural elements. (with or without ligamentous 
resection, discectomy, facetectomy and/or 
foraminotomy) any method under indirect image 
guidance (e.g., fluoroscopic, CT), with or without 
the use of an endoscope, single or multiple levels, 
unilateral or bilateral; lumbar 
T 0208 
Q2040* J0588 Injection, incobotulinumtoxin A, 1 unit G 9278

105 
Concepts 
Distributed with lexical tools and 
Categories and relationships Resources and tools 
The Metathesaurus The Semantic Network defines 
contains over five million 133 broad categories and 54 The SPECIALIST Lexicon and lexical 
biomedical concepts from ralationships between categories for provides lexical information and programs
over 100 source vocabularies labeling the biomedical domain for language processing 
Specialist lexicon
Metathesaurus Semantic network and lexical tools 
MetamorphoSys, the UMLS install
and customization program. The knowledge sources 
Data Interoperability 
Examples of HCPCS codes can be found at https://www.federalregister.gov/articles/2011/11/30/2011–28612/ 
medicare-and-medicaid-programs-hospital-outpatient-prospective-payment-ambulatory-surgical-center. 
4.2.3 Interoperability: Mapping Tools 
4.2.3.1 UMLS 
UMLS is a mapping system and toolset used to coordinate between different medical vocabularies

UMLS is a mapping system and toolset used to coordinate between different medical vocabularies 
(http://www.nlm.nih.gov/research/umls/). It is used by medical informatics developers. It contains 
approximately five million concepts–names and one million concepts–relationships between names 
and terms (Figure 4.10). The U.S. NLM, the largest medical library linked to PubMed (23 million jour­
nal and reference articles), maintains these tools with free licensing ( http://www.ncbi.nlm.nih.gov/ 
pubmed). The UMLS defines its charter as “to promote the creation of more effective and interoperable 
biomedical information systems and services, including electronic health records.” 
The architecture of UMLS contains resources to allow interoperability and health information 
exchange (HIE) and designs the tools to create linkages between diverse medical libraries and EHR

exchange (HIE) and designs the tools to create linkages between diverse medical libraries and EHR 
systems. There are three knowledge databases accessed by UMLS: Metathesaurus, Semantic Network, 
and Lexical Tools (see Section 4.5 in Level III for more details on UMLS). 
4.2.4 Medical Databases 
4.2.4.1 MEDLINE/PubMed 
Medical Literature Analysis and Retrieval System (MEDLINE) is the preeminent life science and medical 
database whose content is selected by a NIH panel of experts (i.e., Literature Selection Technical Review 
Committee) that contains approximately 20 million articles and reference materials (http://pubmed.gov). 
Ninety percent are in English, but articles are available in 60 languages. Most of the databases are jour­
nals but a smaller percentage are magazines, news articles, etc. Abstract and searchable keyword access 
is free but some content is protected by copyright and those protected articles can be obtained from the

is free but some content is protected by copyright and those protected articles can be obtained from the 
LoansomeDoc (https://docline.gov/loansome/login.cfm). This website is supported by the NIH. 
A more generic consumer access portal, MedlinePlus (http://medlineplus.gov/), contains more focused 
and fewer technical resources. An example selected from MedlinePlus is shown in Figure 4.11. It is main­
tained by the NIH. It contains approximately 1,000 topics including medications available, treatments, and 
FIGURE 4 .10 Unified Medical Language System architecture.

106 Biomedical Informatics 
FIGURE 4 .11  MedlinePlus consumer information portal: information on the heart and statin drugs available. 
educational videos and links into your EHRs (http://www.nlm.nih.gov/medlineplus/connect/overview. 
html). The specific medical codes used in your EHR taken from one of the standards medical vocabularies 
such as ICD10 or SNOMED embedded in your EHR can be linked directly to MedlinePlus for patient edu­
cation resources and a drug reference guide for interactions and possible side effects linked to RxNorm. 
MedlinePlus also contains abstracts and journal articles on biological and medical sciences and is 
available online for free and is maintained by the NLM (http://www.ncbi.nlm.nih.gov/pubmed). 
4.2.4.2 Medical Subject Headings 
Medical Subject Headings (MesH) is a thesaurus/vocabulary for accessing either specific medical 
resources related to the search topic such as medical journal articles through PubMed database or

resources related to the search topic such as medical journal articles through PubMed database or 
terms/related concepts through a hierarchy of related terms. It is maintained by the U.S. NLM and used 
by the MEDLINE or MEDLARS (online). 
The main MeSH search page provides multiple views and related concepts (Figure 4.12) (https://www. 
nlm.nih.gov/mesh/MBrowser.html). 
The most basic MeSH search parameters under basic headings provide general and then narrower 
terms and subheadings in the field. Searching cardiology results in a display of related terms such as 
cardiovascular disease, vascular medicine, and angiology and related ICD codes illustrated (Figure 4.13). 
Also, you can refine your search by selecting cardiovascular diseases and then selecting  subheadings 
displaying a hierarchical tree structure including cardiovascular abnormalities, heart defects congeni­
tal, and heart septal defects with four subcategories (Figure 4.14): 
1. Aortopulmonary septal defect

1. Aortopulmonary septal defect 
2. Endocardial cushion defects 
3. Heart septal defects atrial 
4. Heart septal defects ventricular

107 Data Interoperability 
FIGURE 4 .12 Medical Subject Headings search page. (From nih.gov.) 
4.2.4.3 Document-Type Definition 
A document-type definition (DTD) is used by PubMed to index articles. It’s a list of markup declarations 
used to describe the elements and context to enhance searching articles. It is consistent with the Standard 
Generalized Markup Language, which is an ISO standard that describes the article’s structure and content. 
Example (Structure) 
<!DOCTYPE html Public “-//W3C//DTD XHTML 1.0 //EN” “http//www.w3.org .......”>
 
<HTML>   BODY of document   </HTML>
 
• 	 It starts with a Document Type (DOCTYPE identifier) <!DOCTYPE html….. 
• 	 It conforms to World Wide Web (W3C) standards conformance //W3C// 
• 	 http//www.w3.org 
• 	 It also conforms to DTD and XHTML /DTD XHTML 
• 	 Or simply HTML version number 5.0 /DTD HTML 5.0/ 
• 	 Language (English) //EN 
• 	 Then the Document Body enclosed in <HTML>..document… </HTML> 
Example (Content)

Example (Content) 
• 	 Specific searchable information using the ENTITY tag with identifiers can accelerate locating the 
article 
• 	 <!ENTITY followed by a specific tag 
• 	 %author    “authors name”> 
• 	 %title     “Cancer Interventions for Lymphomas”> 
• 	 %date”  “1/1/2013”>

108 Biomedical Informatics 
FIGURE 4 .13  Medical Subject Headings basic search results. 
Level II: Application and Theory: Messaging 
HL7 with Embedded SNOMED 
4.3 Introduction
 
This section illustrates specific  communications protocols, formats, and coding schema for the 
transfer of medical data (SNOMED) embedded in a message between EHRs. The HL7 message 
structure is illustrated in Figure 4.15. Embedded into the HL7 communications wrapper is the 
SNOMED content, i.e., the actual medical data that will be communicated and exchanged between 
EHRs (Figure 4.15). 
4.3.1 HL7 Message Architecture 
HL7 communications protocols define standards for the seamless exchange of electronic health infor­
mation (www.hl7.org). Interoperability is defined as the seamless exchange of data between EHRs. There 
are currently 600 plus EHR vendors. 
4.3.2 HL7 Message Structure 
The following example describes a typical HL7 message. HL7 is the transport structure of the message

The following example describes a typical HL7 message. HL7 is the transport structure of the message 
with fields for PID, medications (RXO), notes or comments field abbreviation (NTE), etc. (Figure 4.16).

Source 1 (Physician/Hospital) 
HL7: Structured message 
Application layer Coded Data: SNOMED, IC10, etc.) 
Messaging layer 
Message Query Message adapter
(XML) Message Acknowledge 
Protocol layer Protocol 
(SFTP , HTTP) 
Network layer Packets (UDP ,
TCP/IP Lubliner 2015 
Destination 2 - Receiver (Physician/Hospital) 
 
109 Data Interoperability 
FIGURE 4 .14 Medical Subject Headings cardiovascular disease and hierarchical diagram of related concepts. 
FIGURE 4 .15  Messaging architecture between medical systems/electronic health records: Health Level 7 is the 
communications protocol.

ACC Accident NTE Notes and comments 
AL1 Patient allergy Information ODS Dietary orders 
BLG Billing PID Patient identification 
DG1 Diagnosis PR1 Procedures 
IN1 Insurance PV1 Patient visit 
MSH Message header RX0 Pharmacy prescription order 
a Subset of HL7 messages available, complete list (http://amisha.pragmaticdata. 
com/~gunther/oldhtml/tables.html). 
110 Biomedical Informatics 
MSH |^~&|CERNER|Pharmacy |1234567 |12345678901234
| 11111|
PID | _ | HL7 | _ | 00001234 | Smith ^ John || RXO| 
0101-10-112 | Tylenol 100mg |
 
FIGURE 4 .16 
Smith. 
Example of a Health Level 7 message from a CERNER electronic health record system for John 
Category Example Message Code 
1. Message starts with: 
2. Group: 
3. Segment: 
4. Data type: 
5: Component: Group 
6. Components: 
MSH (message header) 
EVN (event type) 
PID 
PVI (patient visit information) 
AL1 (patient allergy information) 
DG1 (diagnosis), PR1 (procedures), RXO (pharmacy) 
4.3.3 HL7 Codes in Tables

4.3.3 HL7 Codes in Tables 
In the aforementioned sample message, components such as PID and pharmacy orders (RXO) are sub-
field identifiers for the HL7 code set. Tables 4.11 through 4.13 illustrate some of the possible subcodes 
with a link to the complete set of possible messages available. 
4.3.4 HL7 with Embedded SNOMED CT 
The SNOMED CT, the most comprehensive international medical classification available with 300,000 
plus medical codes/concepts, is used to support medical documentation. Each concept has a unique 
TABLE 4.11  HL7 Message Codes (HL7 Table 9999)a 
Value Description Value Description 
TABLE 4.12 HL7 Medical Record Transaction Codes (HL7 Tables 178 and 180)a 
MAC Reactivate deactivated record.
 
MAD Add record to master file.
 
MDC Discontinue record in master file.
 
MDL Delete record from master file.
 
MUP Update record for master file.

REP Replace current version of this master file with version contained in this message.
 
UPD Change file records.
 
a Subset of codes available.

Data Interoperability 111 
TABLE 4.13 HL7 Physiology: Administrative Descriptors (HL7 Table 163)a 
CT Chest tube RACF Right antecubital fossa 
LA Left arm RPC Right posterior chest 
LPC Left posterior chest RSC Right subclavian 
LSC Left subclavian RUA Right subclavian 
LVL Left vastus lateralis RVG Right upper arm 
RAC Right anterior chest RVK Right vastus lateralis 
 
SNOMED Training Videosb 
Hierarchies Explanation 	 Example
Clinical finding/disorder Results from a clinical observation Appendicitis 
Procedure/intervention Activities performed in healthcare Surgery, MRI, dressing change 
• Component environment 
• Direct morphology 
• Substance 
• Focus 
• Intent 
• Specimen 
• Measurement 
method 
Observable entity Action that results in observable data Blood pressure, heart rate, temperature 
Body structure Normal or abnormal physiological Heart valves operating normally, 90% 
descriptions blockage of coronary artery 
Organism Organisms responsible for disease Bacteria, viruses

Organism Organisms responsible for disease Bacteria, viruses 
Substance Chemical in drugs, allergens, Acetaminophen, insulin, etc. 
toxicity, etc. 
Pharmaceutical/biologic Upper-level root hierarchy, indicates Product categories 
product substance categories 
Specimen Analysis of specimens from patients Urine, etc. 
Physical forces Forces that can create injury Electric current 
Event External events that can cause injury Earthquakes, bioterrorism 
Environments and New Jersey, surgery ICU, emergency room 
geographical locations 
Social context Social environments that affect Occupation, economic status, religion, family 
health history 
Staging and scales Assessment scales Stage 4 cancer 
Attributes	 Relate two SNOMED concepts Attribute 
Cancept A Relationship Concept B 
Pneumonia Lung
Site 
a Subset of physiological messages. 
identifier term. They are available in English, Spanish, and German. There are approximately a million

Site 
identifier term. They are available in English, Spanish, and German. There are approximately a million 
relationships defined between terms (statistics as of January 2014). 
The SNOMED CT concepts are arranged in hierarchies to provide embedded context to the terms 
(Table 4.14). In Table 4.14, a procedure will have subcomponents/contexts that document when, where, 
and how the procedure took place. 
TABLE 4.14  SNOMED Hierarchiesa 
 
a http://www.ihtsdo.org/snomed-ct/snomed-ct0/snomed-ct-hierarchies/. 
b http://www.youtube.com/playlist?list=PL4DE2FA9DA297015F .

Explanation Message 
MSH | ^˜& | CERNER | Pharmacy | 1234567-HL7 Header MSH, ­ | 12345678901234 | 11111 |Patient ID (PID)­ PID  | _ | HL7 | _ | 00001234 | Smith ^ Pharmacy (RXO) John | | RXO | 0101-10-112 | Tylenol 100 mg | 
<Procedure> 
SNOMED Component <Id/>
<codeSystem = “2.16.840.1.113883.6.96”-you enter the code system   codeSystemName = “SNOMED CT”reference number for SNOMED   code code = “29850009”-Then the code for the disorder   displayName = “chest pain” />–ending with a / 
 
112 Biomedical Informatics 
TABLE 4.15 Sample SNOMED CT Codesa 
SNOMED CID Code Description 
195967001 Asthma (disorder) 
21522001 Abdominal pain (symptom) 
29857009 Chest pain (finding) 
53741008 Coronary arteriosclerosis (disorder) 
44054006 Diabetes mellitus type 2 (disorder) 
233604007 Pneumonia (disorder) 
54150009 Upper respiratory infection (disorder) 
a Sample of 300,000 codes available: http://www.clinicalarchitecture.com/blog/clinical­

architecture-healthcare-it-blog/july-2009/snomed-ct-core-subset-quick-overview-and-impressio/. 
FIGURE 4 .17 A Health Level 7 header with embedded Systematized Nomenclature of Medicine content message. 
SNOMED tables have 300,000 plus codes that will be used to populate data fields embedded in the 
HL7 wrapper communications message. Table 4.15 lists a few of those codes that are available. 
Embedded in the HL7 message will be the specific SNOMED codes to describe a particular symptom/ 
disorder/finding that can be exchanged between health record systems (Figure 4.17) . 
Building on the aforementioned first HL7 example that contains the start of the message (MSH) 
and the EHR software CERNER, PID, and the pharmacy order (RXO). The SNOMED component 
starts with the word “Procedure” and the code for the SNOMED medical vocabulary system is

starts with the word “Procedure” and the code for the SNOMED medical vocabulary system is 
“2.16.840.1.113883.6.96 ”. The parsing software, which analyzes the message, then pulls the codes from 
the appropriate vocabulary coding tables. The SNOMED procedure ends with “/”. If ICD10 were used, 
instead of SNOMED, we would use a different code, i.e., 2.16.840.1.113883.5.4 for ICD10 version 3. 
4.4 ICD10 
International Statistical Classification of Diseases and Related Health Problems (ICD10), is a medi­
cal vocabulary and classification system maintained by the WHO (ICD11 2017). It contains codes for 
diseases, symptoms, findings, and social circumstances contributing to a disease. ICD10 codes are 
appended to HL7 header messages, some of which are listed in subcategories in Table 4.16 (http:// apps. 
who.int/classifications/icd10/browse/2010/en). Example A02.2 for Localized Salmonella infectors.

who.int/classifications/icd10/browse/2010/en). Example A02.2 for Localized Salmonella infectors. 
ICD10 version 10, schema circa 2013, which has 14,000+ codes and subcategories, also includes health 
management and epidemiologies created by the WHO. Table 4.16 illustrates the 20 general ICD cat­
egories from infectious and parasitic diseases to external causes of morbidity and portability and an 
example of the subcategories A00–A99 from intestinal infections to arthropod-borne viral fevers.

113 Data Interoperability 
TABLE 4.16 ICD10 Classification Categories (WHO)a 
1. Infectious and parasitic diseases 
A00–A09 Intestinal infectious diseases (sample) 
A02, salmonella infection, 
infection or food-borne intoxication 
due to any Salmonella species other 
than  S. typhi and S. paratyphi 
A02.0 Salmonella enteritidis , 
salmonellosis 
A02.1 Salmonella septicemia  
A02.2 Localized salmonella infections : 
Arthritis+ (M01.3*) 
Meningitis+ (G01*) 
Osteomyelitis+ (M90.2*) 
Pneumonia+ (J17.0*) 
Renal tubulointerstitial 
disease+ (N16.0*) 
A02.8 Other specified Salmonella 
infections 
A02.9 Salmonella infection, 
unspecified 
 
A15–A19 Tuberculosis 
A20–A28 Certain zoonotic bacterial diseases 
A30–A49 Other bacterial diseases 
A50–A64 Infections with a predominantly sexual mode of  
transmission 
A65–A69 Other spirochaetal diseases 
A70–A74 Other diseases caused by chlamydiae 
A75–A79 Rickettsioses 
A80–A89 Viral infections of the central nervous system

A80–A89 Viral infections of the central nervous system 
A90–A99 Arthropod-borne viral fevers and viral hemorrhagic 
fevers 
B0–B99 Viral infections; viral hepatitis; HIV; mycoses; 
protozoal diseases; helminthiases; pediculosis, 
acariasis, and other infestations; sequelae of 
infectious and parasitic diseases; bacterial, viral, and 
other infectious agents; other infectious diseases 
2. Neoplasms 
3. Diseases of the blood and blood-forming organs, 
the immune mechanism 
4. Endocrine, nutritional, and metabolic diseases 
5. Mental and behavioral disorders 
6. Diseases of the nervous system 
7. Diseases of the eye and adnexa 
8. Diseases of the ear and mastoid process 
9. Diseases of the circulatory system 
10. Diseases of the respiratory system 
11. Diseases of the digestive system 
(Co
ntinued )

114 Biomedical Informatics 
TABLE 4.16 (Continued) ICD10 Classification Categories (WHO)a 
12. Diseases of the skin, subcutaneous tissue 
13. Diseases of the musculoskeletal system and 
connective tissue 
14. Diseases of the genitourinary system 
15. Pregnancy, childbirth 
16. Conditions originating in the perinatal period 
17.  Congenital malformations, deformations, and 
chromosomal abnormalities 
18. Symptoms, signs, and abnormal clinical and 
laboratory findings, not elsewhere classified 
19.  Injury, poisoning, and certain other 
consequences of external causes 
20. External causes of morbidity and mortality 
a http://apps.who.int/classifications/icd10/browse/2008/en#/I. 
Level III: Advanced Topics: Mapping Tools 
4.5 Unified Medical Language System
 
The UMLS, provided by the U.S. NLM, provides tools to visualize and integrate medical vocabularies, 
publications, electronic medical records, etc. (http://www.nlm.nih.gov/research/umls/about_umls.

publications, electronic medical records, etc. (http://www.nlm.nih.gov/research/umls/about_umls. 
html). The three core components in the UMLS toolset are the Metathesaurus, Semantic Network, 
and Specialist Lexicon. The Metathesaurus  contains a number of databases, such as SNOMED and 
ICD10, whose goal is to resolve multiple naming conventions into a single representative medical term. 
The Semantic Network displays relationships, i.e., parent–child or hierarchical relationships between 
concepts  (Figure 4.18). The Specialist Lexicon interprets common natural language terms embedded, 
for example, in PubMed publications, and resolves that different natural language variations. The 
Specialist Lexicon has a natural language processing component for commonly used English words 
(Figure 4.19). Its overall goal is to enhance the interoperability of EHRs and support HIEs. 
The UMLS defines its charter as “to promote the creation of more effective and interoperable bio­

medical information systems and services, including electronic health records.” 
Biologic function 
Physiologic function Pathologic function 
Organism
function 
Organ
or tissue 
function 
Cell 
function 
Molecular 
function 
Cell or 
molecular 
dysfunction 
Disease or 
syndrome 
Experimental
model of 
disease 
Neoplastic 
process 
Mental or 
behavioral 
Genetic 
function 
Mental 
process 
FIGURE 4 .18  Semantic categories.

TABLE 4.17 Metathesaurus of Medical Terms Entered into the EHR and It Selects a Preferred Term 
Biologically Active
Substance 
Triplet: 
Biologically active substance | complicates |biologic
function |D| biologically active substance | complicates |
injury or poisoning |D| 
Complicates 
Biologic
function D Injury D 
Poisoning D 
Triplet: 
Biologically active substance | disrupts | embryonic
structure |D| biologically active substance | disrupts |
fully formed anatomical structure |D| biologically
active substance | disrupts | physiologic function |D| 
Embryonic
structure D 
Disrupts Disrupts 
Fully formed
anatomical structure 
D 
Disrupts 
Physiologic function
D 
115 Data Interoperability 
FIGURE 4 .19  Semantic mapping example from a series of triplet relationships. 
4.5.1 UMLS Metathesaurus 
1. The Metathesaurus is a multilingual database that contains medical concepts and relationships

1. The Metathesaurus is a multilingual database that contains medical concepts and relationships 
between them. The thesaurus tool contains synonyms of terms entered into the EHRs and recom­
mends a preferred term used across databases (Table 4.17). 
Metathesaurus databases contain
 1.  Diagnoses,  LOINC 
 2. Procedures, current procedural technology
 3.  Diseases,  ICD10 
 4. Vocabularies and thesauri, SNOMED CT
 5.  Additional  categories
 i.  Nursing
 ii. Drugs
 iii.  Anatomy
 iv.  Genetics 
Collection of Terms in the Concept Preferred Term 
disease; Hodgkin Hodgkin Disease 
Hodgkins disease 
Hodgkin Disease 
Hodgkin’s disease, unspecified 
Hodgkin’s disease, unspecified type 
Hodgkin’s disease (clinical) 
Hodgkin’s disease NOS, unspecified site 
Hodgkin’s disease NOS (disorder) 
Hodgkin’s sarcoma (clinical) 
Hodgkin’s sarcoma NOS 
Hodgkin’s sarcoma of unspecified site 
Hodgkin’s sarcoma of unspecified site (disorder) 
Hodgkin’s sarcoma-unspec. site

Hodgkin’s sarcoma-unspec. site 
Hodgkin lymphoma 
Lymphogranuloma, Malignant 
Lymphogranulomatosis 
Lymphogranulomatosis, malignant 
Lymphomas Hodgkin’s disease

116 Biomedical Informatics 
Table 4.17 illustrates the possible ways on how the term “Hodgkin’s disease” could be entered into an 
EHR and how the Metathesaurus database is used to determine a common term used in a series of 
medical vocabularies such as SNOMED and ICD10 to ensure interoperability between systems. 
4.5.2 UMLS Semantic Network 
Semantic types are used to generate categories of terms and their relationships used in the Metathesaurus. 
The relationships between terms are usually parent–child, from a broader category to a narrower one or 
one with more granularities. Terms are also grouped into broad categories/classifications (Figure 4.18) . 
Semantic categories assist in extracting context and meaning. 
Visualizing the relationships between terms, functions, and causalities, UMLS provides mapping 
of tools to not only aid in the development of the triplet relationships (i.e., A is related to B) but also to

of tools to not only aid in the development of the triplet relationships (i.e., A is related to B) but also to 
provide another method for medical practitioners to visualize the chain of causative elements in the 
disease process (Figure 4.19). 
4.5.3 Lexical Tools (Dictionary) 
The UMLS Specialist Lexicon  contains 200,000+ terms that can be used to create new features or add 
new functionality to a medical classification system. It also contains natural language terms to help 
in the parsing of data input by the medical practitioner. This dictionary draws from several standard­
ized sources such as MEDLINE, which contains 23 million medical citations from PubMed; Dorland’s 
Illustrated Medical Dictionary, which is currently published by Elsevier in its 32nd edition that origi­
nally began in 1890; and several other English dictionaries. 
The Specialist Lexicon contains the following (NLM, www.nlm.nih.gov):

The Specialist Lexicon contains the following (NLM, www.nlm.nih.gov): 
a. The lexical tools that provide the entry of nonformatted data presented in sentences. Language 
parsing tools that can determine verbs, nouns, adjectives, etc., can extrapolate meaning from free-
form data entry. 
b. Embedded lexical computer software tools such as a lexical variant generator, normalized string 
generator (Norm), and word index generator (WordIndex) analyzes variations in terminology to 
extract meaning. A number of free UMLS tools can be found at uts.nlm.nih.gov. 
4.6 RxNav 
RxNav , a pharmaceutical database that is p rovided by the NIH, p rovides linkages betw een RxN orm 
names and the various generic and brand name medications, including the NDC FDA codes http:// 
rxnav.nlm.nih.gov/RxNavViews.html. This tool provides multiple formats for viewing the  relationships

rxnav.nlm.nih.gov/RxNavViews.html. This tool provides multiple formats for viewing the  relationships 
between medications and manufacturers, both generic and brand names. Multiple graphical and 
physical views of the drugs including the color, numeric labeling codes, and manufacturers’ copyrighted 
symbols available to cross-reference medications are shown in Figure 4.20. 
4.7 Summary 
Creating a common medical vocabulary and coding schema that can be used planetwide is a daunt­
ing task. Many organizations are pursuing those lofty goals. The added challenge is to synchro­
nize those various databases to ensure exact meaning is maintained when communicating between 
systems. International organizations regularly meet to create equivalencies. It’s unlikely in the 
near future that one system will  prevail, though SNOMED CT and ICD10 and ICD (CM & PCS) 
come close to the goal of a universal medical vocabulary. Communications protocols, such as HL7,

117 Data Interoperability 
FIGURE 4.20   (See color insert.)  RxNav visualization engine visualizing the same drug from multiple manufacturers. 
provide the communications envelope to encase those specific medical messages into a common 
format with 90% using those standards. 
We have embarked on a journey to add EHRs to the instantaneous communications revolution. 
The next phase is to add interoperability between all systems; that effort is taking place in the United 
States under the Health Information Exchanges (HIEs) funded by the NIH. Once interconnected, dis­
ease outbreaks, such as a new strain of flu virus, can be identified and contained quickly. This exponen­
tial interoperability trajectory is bright! 
Questions 
Level I 
 1.  What is data interoperability? 
 a.	  What are the three general categories? Explain each. 
 b. 	 List a few key standards in each of those three interoperability categories. 
 2.  What is the main functionality of HL7? Explain its purpose.

b. 	 List a few key standards in each of those three interoperability categories. 
 2.  What is the main functionality of HL7? Explain its purpose. 
 a.	  What standards are specified (categories)? Briefly explain each. 
 b.	  Explain some of the details from the HL7 communications message shown in Figure 4.2. 
 c. 	 Explain the relationship between the OSI model and HL7. 
 d. 	 What is HL7 RIM? Explain its purpose. 
 3.  What is ISO? 
 a. 	 Explain ISO TC 215. 
 4. Describe the need for IEEE 11073 Health Device Communications Standards. 
 a. 	 Select one of the IEEE 11073 standards links from Table 4.4 and explain some details of spe­
cific communications standards.

5.  What is the role of the NCPDP? 
 a. Explain the e-prescription mandates and penalties. 
 6.  What role do medical classification systems play in interoperability?
 
  Briefly explain the following:
 a.  SNOMED  CT
 b.  SNODENT
 c.  ICD10–11
 d.  LOINC
 e.  RxNorm
 7.  W h at  i s  UMLS? 
 a. Explain the three knowledge databases incorporated in UMLS. 
Level II 
 8. In the HL7 message sent between clinical systems, modify the message to include patient allergy, 
diagnosis data, and insurance: be creative and make up some allergies and diagnoses (Figure 4.16 
and Tables 4.11 through 4.13). 
 9. For the HL7 message incorporating SNOMED CT, add some fields and update the procedure in 
Figure 4.17. 
 a. Do the same for the HL7 message but use ICD10 (use the data from Table 4.16). 
Level III 
 10. Using the UMLS thesaurus framework, create your own set of interchangeable terms for some 
real mythical conditions; be creative (Table 4.17).

10. Using the UMLS thesaurus framework, create your own set of interchangeable terms for some 
real mythical conditions; be creative (Table 4.17). 
 11. Utilizing the UMLS Semantic Network framework, create a specific mapping sample, choose 
some diseases, and create your own semantic mapping sample: use Figure 4.19 as a template. 
Glossary 
Context Management Specification (CCOW) : CCOW is a standard for allowing independent systems 
to synchronize context on a single workstation, providing a seamless interface for the user of  
that workstation (e.g., ensuring consistent user authentication, display of the same patient, 
display of the same order, etc.). 
Clinical Document Architecture (CDA) :  The HL7 Version 3 Clinical Document Architecture (CDA ®) 
is a document markup standard that specifies the structure and semantics of ‘clinical docu­
ments’ for the purpose of exchange between healthcare providers and patients.

ments’ for the purpose of exchange between healthcare providers and patients. 
EHR-S Functional Model (FM) Release 2 2014 : The model that outlines important features and func­
tions that should be contained in an EHR system. Through the creation of functional pro­
files, this model provides a standard description and common understanding of functions for 
healthcare settings. 
Fast Healthcare Interoperability Resources (FHIR) (hl7.org/fhir) : FHIR is a next generation stan­
dards framework (2014) created by HL7. It combines the features of HL7’s version 2 and version 
3 and CDA product lines while leveraging the latest web standards and applying a tight focus 
on implementability for mobile phone apps, Cloud communications, EHR-based data sharing,  
 
118 Biomedical Informatics 
and s
erver communications. 
International Statistical Classification of Diseases and Health Related Problems (ICD10) : Version 10,

and s
International Statistical Classification of Diseases and Health Related Problems (ICD10) : Version 10, 
schema circa 2013, which has 14,000+ codes and subcategories, is a medical classification list 
of diseases, symptoms, diagnoses, health management and epidemiology created by the World 
Health Organization.

119 Data Interoperability 
ICD Clinical Modification (CM) version 10 (ICD10 CM) : Maintained by the Center for Medicaid and 
M e di c ar e  S e rvi c e s  ( C M S ) ,  i t  i s  a  U . S .  N a ti o n al  C o d e ,  w h i c h  p r o vi d e s  m o r e  d e t ail  th an  th e 
WHO’s ICD10, with 68,000 codes. 
Institute of Electrical and Electronics Engineers (IEEE) Standards Association (SA) : Develops stan­
dards for the interoperability electronic of devices. 
International Health Terminology Standards Development Organisation (IHTSDO) : Nonprofit 
organization in Denmark. It owns SNOMED CT (http://www.ihtsdo.org/). 
Integrating the Healthcare Enterprise (IHE) : Nonprofit organization created by the U.S. Healthcare 
Industry and the Radiology Group of North America and supported by the Health Information 
Management Systems Society (HIMSS) ( http://ihe.net/). 
Logical Observation Identifiers Names and Codes (LOINC) : Used to identify medical laboratory 
observations.

observations. 
Reference Information Model (RIM) : Provides software developers with architecture for information 
exchange between electronic health records in accordance with HL7 standards. 
Regenstrief LOINC Mapping Assistant (RELMA) : Search tool for the LOINC clinical database. 
Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) : The most comprehensive 
international medical classification available, as of 2013; it had 300,000 medical codes to sup­
port medical documentation. 
Unified Medical Language System (UMLS): Mapping system and toolset used to convert between differ­
ent medical vocabularies. It is used by medical informatics developers. It contains approximately 
5 million concepts–names and 1 million concepts–relationships between names and terms. 
 1.  Health Information Exchange (HIE) Technical Guidelines (2011) HIMSS. http://www.himss.org/

 1.  Health Information Exchange (HIE) Technical Guidelines (2011) HIMSS. http://www.himss.org/ 
files/HIMSSorg/content/files/HIMSSHIETechnicalOverview.pdf. (Generated by HIE committees). 
 2. Hettick, L. (2013). Data networking basics. Networking World, Feb 2013. (Generated by HIE committees). 
 3. HL7 Message types, http://www.hl7.org/special/committees/vocab/v26_appendix_a.pdf. (Generated  
by HIE committees).
 4. International classification of Diseases 10th revision . World Health Organization. February 26, 
2010, http://apps.who.int/classifications/icd10/browse/2010/en 
 5. Dolin, R. (2004) Introduction to SNOMED clinical terms and its use with HL7, http://www.park­
streetsolutions. com/documents/SNOMED_Overview.Acapulco.pdf. 
 6. Durkin, S. and Just, B. A n  I T  p r i m e r  f o r  h e a l t h  i n f o r m a t i o n  e x c h a n g e, AHIMA http://library. 
ahima.org/xpedio/groups/public/documents/ahima/bok1_036239.hcsp?dDocName=bok1_03629

ahima.org/xpedio/groups/public/documents/ahima/bok1_036239.hcsp?dDocName=bok1_03629 
 7. SNOMED Clinical Term (CT), Reference Manual, http://ihtsdo.org/fileadmin/user_upload/doc/ 
download/doc_UserGuide_Current-en-US_INT_20130731.pdf. (Generated by HIE committees).

Level I: Core Concepts ................................................................................. 122
 
5.1 	 Introduction ...................................................................................... 122
 
5.2 	 HIPAA Title II Security and Privacy ............................................. 122
 
Privacy Rule • Security
 
Level II: Computer Security Best Practices ............................................... 129
 
5.3 	 Defense in Depth .............................................................................. 129
 
Achieving Information Assurance • Access Controls
 
Level III: Advanced Topics .......................................................................... 135
 
5.4 	 Cyber Security for Medical Devices .............................................. 135
 
Future Medical Security Risks for Medical Devices
 
5.5 Summary ............................................................................................ 137

Questions ....................................................................................................... 137
 
Glossary ......................................................................................................... 138
 
References ...................................................................................................... 138
 
5 
Security
 
121

122 Biomedical Informatics 
5.1 Introduction
 
Information security is an ever-evolving endeavor. We are regularly bombarded by large-scale 
security breaches. In 2014, the Department of Health and Human Services (HHS) under the 
Health Insurance Portability and Accountability Act (HIPAA) Title II fined two New York City 
(NYC) hospitals $4.8 million for a security breach [3] of Electronic Protected Health Information 
(ePHI). The hospital systems were secure but a physician’s personal computer/server was at fault. 
In another security breach target, one of the largest retailers in the United States reported that 70 
million customer data had potentially been compromised [9]. The Wall Street Journal  reported that 
“Target attackers were able to gain access to the retailer’s system by way of stolen credentials from 
a third-party vendor.” Target’s systems may have been secure, but a third-party vendor’s security

a third-party vendor.” Target’s systems may have been secure, but a third-party vendor’s security 
was lax, so they gained access through a backdoor. Security breaches often occur through innocu­
ous lapses in security in tertiary systems. Simple, easily hacked passwords such as 12345 , leaving a 
system unattended, and phishing, a form of social engineering where an individual is fraudulently 
contacted to reset his or her password and provide confidential information, are some of the many 
techniques used to breach a system’s security. “They lunge, we parry” is a fencing analogy, a con­
tinual dance of attack/defense, that will probably always be with us. The benefits of electronic health 
records (EHRs) far outweigh any potential security breaches. Healthcare professionals sharing data 
and evaluating the effectiveness of treatments and real-time consults are moving medical practices 
exponentially forward. This chapter discusses medical computer security best practices that will

exponentially forward. This chapter discusses medical computer security best practices that will 
evolve over time (Figure 5.1). 
HIPAA fines for ePHI 2014 for two NYC hospitals (http://www.hhs.gov/news/press/2014pres/05/ 
20140507b.html). 
Target security breach (http://www.washingtonpost.com/business/economy/target-says-70-million­
customers-were-hit-by-dec-data-breach-more-than-first-reported/2014/01/10/0ada1026–79fe­
11e3–8963-b4b654bcc9b2_story.html). 
5.2 HIPAA Title II Security and Privacy 
This text focuses on medical informatics, i.e., software, hardware, operational, and ethical components 
of the healthcare environment that support efficient, effective, and secure information exchange. The 
goal of HIPAA, created in 1996, was to “improve the health, safety, and well being of America popula­
tion” and to create a framework for the EHR infrastructure (Figure 5.2). 
HIPAA Title II describes security as “the safeguards that must be in place to ensure appropriate pro­

tection of electronic Protected Health Information (ePHI), and privacy, that sets limits and conditions 
on the use and disclosure of medical information without patient authorization.” 
These security goals are also described in Section 13402 of the Health Information Technology for 
E c o n o m i c  a n d  C l i n i c a l  H e a l t h  A c t ,  p a r t  o f  t h e  A m e r i c a n  R e c o v e r y  a n d  R e i n v e s t m e n t  A c t  o f  2 0 0 9 
(http://www.gpo.gov/fdsys/pkg/FR-2009–08–24/pdf/E9–20169.pdf ). 
5.2.1 Privacy Rule 
The HIPAA Privacy Rule sets federal standards to protect individuals’ personal health information 
(PHI) and describes limits to disclosure of medical information without patient authorization. The 
exceptions listed in Figure 5.2 f ocus on balancing the patient’s privacy with providing efficient health

exceptions listed in Figure 5.2 f ocus on balancing the patient’s privacy with providing efficient health 
delivery. Possible scenarios: a patient is unconscious, or transferred to a tertiary medical facility, or a

HIPAA Title II Security Primer	 Biometrics (Health Insurance Portability and Accountability Act 1996)
HIPAA Title II
(Health Insurance Portability and Accountability Act 1996) Information assurance Defense in depth 
Administrative Protect, detect and react (F5.com term is defense
(Policies and procedures) in Breath) 
People DNS Web Access Privacy	 Security 
that sets limits and conditions on the use and the safeguards that must be in place to ensure
 
disclosure of medical information without appropriate protection of electronic Protected Technology Dynamic threat defense
patient authorization Health Information (ePHI).
 
Physical Technical	 DDOS protection
(controls) (controls) Operations Exceptions Lubliner 2013 Protocol security
 
1. 	 Compromises a patient’s health; i.e., a
      patient is unconscious (privacy rules waived) Penalties

 -Breaches:2. Public health is threatened -Involving more than 500 individuals the security3. Research (anonymized data)
1. 	 With the permission of an IRB or rule require that they notify HHS immediately.
-More than 500 individuals requires media be notified
       Privacy Board, the patient's privacy -Encrypted PHI:
       rights can be waived they are: -Not required to provide breach notification because
4. Treatment, Payment, Healthcare Operations   the information is not considered “unsecured” 
  
Security	 123 
FIGURE 5.1 (See color insert.) Security and privacy.

(Health Insurance Portability and Accountability Act 1996)
 
Administrative 
(Policies and Procedures) 
Privacy 
That sets limits and conditions on the use and 
disclosure of medical information without 
patient authorization 
Security 
The safeguards that must be in place to
ensure appropriate protection of electronic Protected 
Health Information (ePHI). 
Physical
(Controls) 
Technical 
(Controls)
Exceptions Lubliner 2013 
Public Health Research 
1. Compromises a patient’s health; i.e., a
patient is unconscious (privacy rules waived) 
2. Public health is threatened 
3. Research (anonymized data)
a. With the permission of an IRB or
Privacy Board the patient's privacy
rights can be waived they are:
 
4. Treatment, payment, healthcare operations 
Breach Notification Encrypted PHI 
Penalties 
Breaches:
 
Involving more than 500 individuals the security rule
require that they notify HHS immediately.
 
More than 500 individuls requires media be notified 
Encrypted PHI:

Encrypted PHI: 
Not required to provide breach notification because
the information is not considered unsecured 
124 Biomedical Informatics 
FIGURE 5.2 HIPAA Title II security and privacy rules. 
public health emergency, anonymized data, i.e. patient’s name, Social Security number, etc. are removed 
from the medical record, so it can be shared under strict HIPAA Title II guidelines. These regula­
tions are enforced by the HHS Office of Civil Rights (OCR) (http://www.hhs. gov/ocr/privacy/hipaa/ 
understanding/ coveredentities/usesanddisclosuresfortpo.html). 
1. The privacy rule restricts the use of ePHI without patient consent unless the following are 
given: 
Exceptions 
a. 	 It compromises a patient’s health such that a patient is unconscious and can’t provide consent 
or the speed of lifesaving treatment would be compromised.

or the speed of lifesaving treatment would be compromised. 
b. 	 Public health is threatened wherein data are anonymized, and patient’s identifying informa­
tion is removed, so by this exception, we can track national disease outbreaks. 
c. 	 Research and anonymized data can be used to study the effectiveness of the treatment. 
d.	 Treatment, payment, healthcare operations, and legal system efficiency uses are authorized 
under very limited guidelines. 
i.	 Treatment: coordination of services among practitioners or third-party referral 
services. 
ii. 	 Payment: providers have the right to be reimbursed for their services. 
Exception areas 
1.	 Determining eligibility or coverage 
2. 	 Billing and collection activities 
3.	 Reviewing healthcare services for medical necessity, coverage, and justification of 
charges
 4.	 Utilization review

Security	 125 
5. 	 Disclosures to consumer reporting agencies that are limited to payment history and 
identifying information about the covered entity
 6.	 Risk adjustments 
iii. 	 Healthcare operations: administrative, legal, and efficiencies of operations 
1. 	 Quality assessment and improvement activities, improving health or reducing 
healthcare costs and case management and care coordination 
2.	 Evaluating the competence or qualifications of healthcare professionals, plan per­
formance, training healthcare and nonhealthcare professionals, accreditation, 
certification, licensing, or credentialing activities 
3. 	 Activities relating to the creation, renewal, or replacement of a contract of health 
insurance or health benefits 
4. 	 Medical review, legal, and auditing services, including fraud and abuse detection 
and compliance programs 
5. 	 Business planning and development, such as cost-management and planning 
analyses

analyses 
6. 	 Business management and general administrative activities, including those related 
to implementing and complying with the privacy rule and other administrative 
simplification rules 
2. Individuals have right to view and get copied all medical records. 
3. The scope of protected information covers the following: 
a.	 All information doctors, nurses, and other healthcare providers put in the patient’s medical 
records 
b. 	 Conversations doctor has about the patient’s care or treatment with nurses and others 
c. 	 Information about the patient’s in the patient’s health insurer’s computer system
 d.	 Billing information 
5.2.1.1 Public Health 
Protecting public health, that the needs of the many outweigh the needs of the few or the one (quote 
for science fiction enthusiasts ) provides exceptions of disclosure of ePHI. If an imminent disease

for science fiction enthusiasts ) provides exceptions of disclosure of ePHI. If an imminent disease 
outbreak can be detected and treated quickly, many lives can be saved. In 1918, the flu epidemic, later 
identified as H1N1 influenza virus, infected 500 million out of a worldwide population of less than 
2 billion; essentially 1 in 3 people were infected and 50 to 100 million died, about 4% of the planet’s 
population. It is estimated that during World War I, the movements of troops and refugees and 
malnutrition due to the conflict added to the deadly transmission. The variants that later occurred 
were H1N2 and H3N2. In 1976, a H1N1 virus was detected in Fort Dix and never left the facility due 
to enhanced reporting procedures. In the next year, roughly 48 million people were vaccinated and 
very few died that year. One side effect of rushing out a vaccine was the occurrence of the 500 addi­

tional cases of the Guillain–Barré syndrome, a nervous system disease that causes paralysis, or an 
increased occurrence of the syndrome for 1 in 100,000 vaccinations. Hundreds, as opposed to mil­
lions, were potentially spared infection by early detection and treatment. In today’s global village, 
airline travel has the potential of spreading disease quickly, so early detection is even more urgent. 
The privacy rules permit covered entities to disclose PHI for public health purposes: 
The term “covered entity” under the HIPAA Privacy Rule refers to three specific groups: includ­
ing health plans, healthcare clearinghouses , and healthcare providers  that transmit health informa­
tion electronically. Covered entities under the HIPAA Privacy Rule must comply with the Rule’s 
requirements for safeguarding the privacy of protected health information. ( http://www.hhs.gov/

requirements for safeguarding the privacy of protected health information. ( http://www.hhs.gov/ 
ocr/privacy/hipaa/understanding/special/index.html).

126 Biomedical Informatics 
5.2.1.2 Research 
Medical research, using deidentified information, is allowed but under strict guidelines. In general, 
as in all medical research, if deidentified information is required, i.e., any information that can 
be used to identify subjects must be removed to ensure privacy. Certain privacy provisions listed 
below may be waived. 
 1. 
Institutional review board (IRB) or privacy board approval. With the permission of an IRB or 
privacy board, the patient privacy rights can be waived: 
Exclusions and required documentation: 
 a.	  A statement that the IRB or privacy board has determined that the alteration or waiver of  
authorization, in whole or in part, satisfies the three criteria in the rule: 
 i. 	 A description of the PHI that explains why access has been determined to be necessary 
 ii. 	 A statement that waiver has been reviewed and approved under either normal or expe­
dited review procedures

ii. 	 A statement that waiver has been reviewed and approved under either normal or expe­
dited review procedures 
 iii. 	 The signature of the chair or other designated member of the IRB is affixed 
 2. The criteria of patient privacy waiver include 
 a.	  A plan to protect identifying information from improper use and disclosure. 
 b. 	 A plan to destroy the identifier’s consistent with the conduct of the research, unless there is 
a health or research justification for retaining the identifiers or such retention is otherwise 
required by the law. 
 c.	  Written assurances that the PHI will not be reused or disclosed to any other person or entity, 
except as required by law, for authorized oversight of the research project. 
 3. Preparatory to research, the PHI being sought is used to prepare a research protocol, to determine 
the feasibility of the research. 
 4. Research on protected health information of decedents: in order to study deceased individuals,

 4. Research on protected health information of decedents: in order to study deceased individuals,  
release of PHI may be granted. 
 5. Limited data sets with a data use agreement: limited data on sex, age, and demographics may  
be released as long as they don’t contain PHI of an individual, relatives, or household members. 
This data use agreement should contain the following information: 
 1. 	 Establish the permitted uses and disclosures of the limited data set by the recipient, consistent 
with the purposes of the research, which may not include any use or disclosure that would 
violate the rule if done by the covered entity. 
 2. 	 Limit who can use or receive the data. 
 3. 	 Require the recipient to agree to the following: 
 i.	  Do not use or disclose the information other than that as permitted by the data use agree­
ment or indicated by law. 
 ii. 	 Use appropriate safeguards to prevent the use or disclosure of the information.

 ii. 	 Use appropriate safeguards to prevent the use or disclosure of the information.  
 iii. 	 Report any use or disclosure of the information not provided for by the data use agree­
ment of which the recipient becomes aware. 
 iv. 	 Ensure agents and subcontractors, to whom the recipient provides the limited data set,  
agree to the same restrictions  not to identify the information or contact the individual. 
 6. Research use/disclosure with individual authorization. 
 a.	  Authorization for a research purpose may state that the authorization does not expire till the 
end of the research. 
 b.	  Can be coupled with multiple research activities, such as clinical trials. 
 c.	  For future research, the authorization can indicate that it can be used for future trials so long 
as the authorization describes the nature of those future trials. 
 7. In accounting for research disclosures, the individual has the right to request a detailed account­

7. In accounting for research disclosures, the individual has the right to request a detailed account­
ing of all research uses of his or her PHI.

Security 127 
5.2.2 Security 
The HIPAA Security Rule requires “administrative, physical and technical safeguards to ensure the 
confidentiality, integrity, and security of electronic protected health information.” The original docu­
mentation was created in 1996 but the Final Security Rules were published in 2003 (http://www.hhs.gov/ 
ocr/privacy/hipaa/administrative/securityrule/securityrulepdf.pdf). 
The security rule applies to all healthcare providers, clearing houses, and third-party vendors who 
maintain EHRs. 
5.2.2.1 Administrative Controls and Safeguards 
A covered entity must periodically assess security and risks to electronic PHIs (ePHIs) and reduce risks 
to a minimum. The organization must appoint a security officer responsible for security policy and 
implementation. Role-based access should be implemented where only individuals who have a need to 
ac
cess that data have security privileges. Finally, periodic training and assessment are required to ensure

ac
cess that data have security privileges. Finally, periodic training and assessment are required to ensure  
policies are being met. 
The security administrative controls  fall into three categories: 
1.  Practices
  Company practices
 a.  Education
 b.  Security  practices
 c.  Privacy practices
  Technical  practices
 d.  Physical  security
 e.  Disaster  recovery
 f.  Access  controls
 g.  Authentication 
 h.  Secure communications: internal and external 
 i.  Software best practices
 2.  Procedures 
 a. Designating an information security officer 
 b. Auditing and implementing periodic evaluations of systems 
 c.  Instituting sanctions for infractions 
 d.  Informing patients of privacy rights 
 e. Educating patients in their rights to obtain a copy of their medical records 
 f. Controlling access of PHIs to a minimum needed by third parties
 3.  Policies 
 a.  A covered entity must adhere to HIPAA security and privacy policies.

3.  Policies 
 a.  A covered entity must adhere to HIPAA security and privacy policies. 
 b. A covered entity must retain for 6 years written policies, procedures, actions, and assessments. 
 c. A covered entity must periodically update its rules and procedures related to security practices.  
The term “covered entity” under the HIPAA Privacy Rule refers to three specific groups, including 
health plans , healthcare clearinghouses , and healthcare providers  that transmit health informa­
requirements for safeguarding the privacy of protected health information (http://www.hrsa.gov/ 
healthit/toolbox/HealthITAdoptiontoolbox/PrivacyandSecurity/entityhipaa.html). 
Physical controls: Facility access must be limited to authorized users. Computers and electronic media,  
such as flash drives and DVDs, must be monitored and procedures in place to limit access and policies for

such as flash drives and DVDs, must be monitored and procedures in place to limit access and policies for 
wiping unused hard drives and disposal of retired systems.

128 Biomedical Informatics 
Technical controls: Access controls must be implemented to ensure only authorized personnel have 
privileges. Audits must periodically access procedures and track changes in records, i.e., improper changes 
or deletion of records. Transmission of data must be monitored for unauthorized access. 
5.2.2.2 Breach Notification Rule 
This rule requires that all HIPAA organizations must notify the Federal Trade Commission of any 
unauthorized access of ePHIs. The HIPAA rules define electronic protected health information (ePHI) 
“as the individually identifiable health information held or transmitted in any form or medium by these 
HI
PAA covered entities and business associates, subject to certain limited exceptions.”  In all cases, the  
security rule requires all individuals whose information has been accessed be notified. 
 1.  In breaches involving more than 500 individuals, the security rule requires that they notify the

1.  In breaches involving more than 500 individuals, the security rule requires that they notify the  
secretary of the HHS immediately (Section 164.408). 
 a. 	 In this category that involves greater than 500 individuals, the rule requires media organiza­
tions be notified (Section 164.406 implements section 13402(e)(2) of the act). 
 b.	  The law also requires, in this category, that covered entities and business associates be notified. 
 2. In breaches including fewer than 500 individuals, the organization can retail a log and submit it 
to the secretary of the HHS at the end of the year during which the breaches have occurred. 
In 2007, according to the HHS, a state mental health agency reported the loss of 2.9 million records,  
which was the highest for that year, followed by 375,000, which was the next highest. Table 5.1 illustrates 
that the costs were approximately $17 million to remediate this breach (Table 5.1). 
5.2.2.3 Encrypted PHI

5.2.2.3 Encrypted PHI 
If one of the covered entities chooses to encrypt the individual’s medical information and there is unau­
thorized access, “they will not be required to provide breach notification because the information is not 
considered ‘unsecured protected health information’ as it has been rendered unusable, unreadable, or 
indecipherable to unauthorized individuals .” 
5.2.2.4 Penalties 
Noncompliance of HIPAA Title II results in civil and criminal penalties. It is enforced by the HHS OCR. 
The maximum penalty of $250,000 and 10 years in prison is imposed for obtaining PHI for commercial, 
malicious intent or personal gain. Table 5.2 lists the penalties, maximum prison terms, and guidelines. 
TABLE 5.1 HHS Provided Data of a Single Breach of 2.8 Million Health Records in 2007 
Number of Number of Affected Cost/Affected 
Cost Elements Breaches Individuals Cost/Breach Individuals Cost

Cost Elements Breaches Individuals Cost/Breach Individuals Cost 
E-mail and 1st class mail 106 2,888,804 $12,986 $0.477 1,376,528 
Alternative notices media notice 70 2,888,804 487 0.012 34,080 
Toll-free number 70 2,888,804 117,676 2.851 8,237,309 
Imput cost to affected individuals 70 2,888,804 103,172 2.500 7,222,010 
Notice to media breach 500+ 56 2,887,032 75 0.001 4,200 
Report to the secretary 56 2,887,032 75 0.001 4,200 
Investigation costs: 
Under 500 50 1,772 400 11 20,000 
Over 500 56 2,887,032 2,211 0.043 123,800 
Annual report to the secretary 106 2,888,804 30 0.001 3, 180 
Total cost 160,616 5.89 17,025,306 
Source: Privacy Rights Clearinghouse, a California Nonprofit Corporation, http://www/datalossdb.org.

Fines (%) Maximum Prison Terms Guidelines 
250,000 10 years Obtaining PHI for commercial, malicious intent or 
personal gain 
100,000 5 years Getting PHI under false pretenses. 
50,000 1 year Knowingly and wrongfully using  PHI data 
25,000 per year For each violation For noncompliance, it is determined that the infraction 
was not intentional and remediation, once found, was 
corrected in 30 days 
Security 129 
TABLE 5.2 HIPAA Title II Penalties 
TABLE 5.3 Administrative Transaction Codes 
Eligibility for benefits 270 
Eligibility response by insurance 271 
Claim status inquiry 276 
Referrals 278 
Claim status response 277 
Claim submission 835 
Claim payment 837 
5.2.2.5 Transaction Codes (Title II) 
Under Title II that describes privacy and security are certain transactions to support administrative 
functions such as eligibility for reimbursement, treatment, and referrals. This will be coordinated by the

functions such as eligibility for reimbursement, treatment, and referrals. This will be coordinated by the 
Center for Medicare and Medicaid Services and include Employer Identification Numbers (Table 5.3). 
Level II: Computer Security Best Practices 
5.3 Defense in Depth
 
The concept of defense in depth involves layers of security, similar to an onion, to ensure that if any 
breach occurs, it can be detected and repulsed before it can access the next level where sensitive infor­
mation is obtained. An analogy would be a bank, wherein there are gates, cameras, and security guards 
at the entrance. If any suspicious individual enters, they are stopped or an alarm is triggered. If they 
pass through this first level and approach the teller, that individual could also sound an alarm. There are 
additional layers of locked drawers, daily audits of finances and tellers, and finally a vault with extreme

additional layers of locked drawers, daily audits of finances and tellers, and finally a vault with extreme 
levels of security and access controls for a limited set of individuals. Cameras and security code access, 
audits, and forensics allow them to reconstruct events. If all these failed, there are extreme federal penal­
ties for robbing banks (Figure 5.3). 
Th e  f o l l o w i n g  d e f e n s e - i n - d e p t h  s t r a t e g i e s  w e r e  d e s c r i b e d  i n  a  N a t i o n a l  S e c u r i t i e s  A g e n c y  ( N S A ) 
white paper ( http://www.nsa.gov/ia/_files/support/defenseindepth.pdf ). The term “information assur­
ance” (IA) is used in the context of guaranteeing the safety and validity of data. It can be achieved 
by applying the following security services: availability, integrity , authentication, confidentiality, and 
nonrepudiation. 
(Nonrepudiation legally refers to signatures or contracts where their validity is being repudiated or

(Nonrepudiation legally refers to signatures or contracts where their validity is being repudiated or 
questioned. The term “nonrepudiated” means it cannot be questioned; it is definitely valid. In computer 
terms, it often refers to the proof of the integrity and origin of data or a digital signature, the goal being 
that the validity is so secure that it can’t be questioned or can’t be repudiated.)

Information assurance 
Protect, detect and react 
Defense in depth 
(F5.com term is defense
in breath) 
Terms : 
Domain name system (DNS)
is a hierarchical distributed 
naming system 
People DNS Web Access Distributed denial-of-service 
(DDOS) attack, saturating
Technology Dynamic threat defense server with a large number of 
requests 
DDOS protection Multilayer defense: Stop
Operations network attacks by SHTTP ,
Protocol security DNS, SIP 
SIP typically employs the
Network firewall Real-time Transport Protocol
(RTP ) 
Logging Control Apps Lubliner 2013 
 
Examples of layered defenses 
Class of 
attack 
First line of 
defense 
Second line of 
defense 
Passive Link and Network Security Enabled 
Layer Encryption and 
Traffic Flow Security 
Applications 
Active Defend the Enclave 
Boundaries 
Defend the Computing 
Environment 
Insider Physical and Personnel Authenticated Access 
Security Controls, Audit 
Close-In Physical and Personnel 
Security 
Technical Surveillance 
Countermeasures

Security 
Countermeasures 
Distribution Trusted Software 
Development and 
Run Time Integrity 
Controls 
Distribution 
130 Biomedical Informatics 
FIGURE 5.3 Defense-in-depth strategies. 
5.3.1 Achieving Information Assurance
 1.  People 
 a.	  Process begins with a chief security officer 
 b. 	 Policies and Procedures: Assigning roles and responsibilities 
 c.	  Training and Awareness: System administrators and accountability 
 d.	  System security administration 
 e.	  Physical security: Control 
 f. 	 Personnel security monitor facilities
 2.  Technology 
 a. 	 Architectures for IA validated by a third party 
 i.	  Defense in depth (can be attacked internally or externally) 
 1.	  Defend the network from denial-of-service attacks or distributed denial-of-service 
attack, saturating the server with a large number of requests.

attack, saturating the server with a large number of requests. 
 2. 	 Defend the computer systems infrastructure boundaries: firewalls, intrusion detec­
tion, and access controls (Figure 5.4). 
 3. 	 For layered defenses, any defense can be broken, but if one layer is breached and 
detected, that provides time for a response (www.NSA.gov).

Nested zone based firewalls 
Users 1 and 2 can communicate
 
freely since they are in the same
 Design each zone for azone: due to Zone Membership specific Virtual Privatepolicies Network (VPN) 
User 1 
User 2 Zone 1 Zone 2 
firewall firewall 
To communicate User 3 User 4 
between zones additional 
security privileges are 
necessary 
   
Security	 131 
FIGURE 5.4 Nested security zones increase protection. 
providing nested firewalls, each with a layer of detection and protection: a good 
resource is from Cisco Systems (http://www.cisco.com/c/en/us/td/docs/security/ 
se
curity_management/cisco_security_manager/security_manager/3–3–1/configu­
ration/example/ZBF_ConfigExample.html). 
 4. Use strong key message encryption such as public key encryption (PKE). 
 5. 	 Use infrastructure monitoring software to aid in intrusion detection. The National 
Institute of Standards and Technology (NIST) has a guide for intrusion detection

Institute of Standards and Technology (NIST) has a guide for intrusion detection 
best practices (http://csrc.nist.gov/publications/nistpubs/800–94/SP800–94.pdf).
 3.  Operations
 a.  Security  policies
 b.  Security  management 
 i. Timely security patches and virus updates 
 c.	  Certification and accreditation
 d.  Key  management
 e.  System  assessments 
 i.	  Providing regular security readiness assessments and vulnerability assessments includ­
ing independent third parties. 
 ii. 	 The National Information Assurance Partnership between NSA and NIST along with the 
International Organization for Standardization (ISO) sets standards for IA (http://niap. 
nist.gov) and also lists recommended IA software.
 f.  Disaster  recovery
 i.	  Risk  assessment
 ii. Impact analysis 
 1. Take inventory of assets.
 2.  Assign roles. 
 3. Sell plan to management. 
 4.  Identify possible solutions.
 5.	  Choose  solution. 
 6.  Create a recovery manual.

2.  Assign roles. 
 6.  Create a recovery manual. 
 iii. Disaster recovery testing and planning 
 1.  Test recovery plan. 
 2. 	 Train, maintain, and document.

132 Biomedical Informatics 
The following sections describe specific strategies and technologies to enhance system security. This is 
not an exhaustive list, rather it is a reprehensive compendium of defense-in-depth technologies. 
5.3.2 Access Controls 
Physical 
5.3.2.1 Biometrics 
Biometrics refer to a some physiological characteristic, such as fingerprints, that can be input and con­
verted into digital format and can be used to verify an individual’s identity. Instead of using something 
physical in your possession, a key or a password, biometrics uses who you are to identify you. Biometrics 
can use physical characteristics, like your face, fingerprints, irises or veins, or behavioral characteristics 
like your voice, handwriting, or typing rhythm. Most systems don’t store the complete image or record­
ing. They instead analyze your trait and translate it into a code or graph. Then they compare the trait to 
the information on file. 
5.3.2.1.1 Iris Scanners

5.3.2.1.1 Iris Scanners 
Iris scanners capture a series of 2D Gabor wavelets, which are linear filters used in edge detection that 
capture frequency and orientation, to extract features that are represented as phasors, i.e., vectors in a 
plane. This process is so compact that the iris pattern can be stored in a few hundred bytes. A link to an 
iris scanning code example in MATLAB
®, or Matrix Laboratory that is a programing language envi­
ronment created by MathWorks, illustrates the matrix multiplications. An example of IRIS scanning 
software algorithms is shown in Figure 5.5. 
Multiple authentication layers, similar to defense in depth, increase the level of security. A layered 
system combines a biometric input with a secondary source such as a pin number. Multimodal systems 
combine multiple biometric systems. 
5.3.2.1.2 Fingerprint Scanner 
Ridges on fingers evolved as beneficial evolutionary trait that enabled individual to better grip objects.

Ridges on fingers evolved as beneficial evolutionary trait that enabled individual to better grip objects. 
The actual pattern is created in the womb and is caused by a series of random events and by the 
Biometrics uses unique features,
like the iris of your eye, to identify you 
P4 
pd 
pc 
Ri 
P2 
Ci P3dθ 
Rp P1 pa pb Cp 
θ 
FIGURE 5.5 (See color insert.) Biometric input and retinal analysis, using phasors (vectors in a plane). 
(From MATLAB ® http://matlabsproj.blogspot.com/2012/06/iris-detection-matlab.html; Photo courtesy of Iridian 
Technologies.)

Security 133 
Bifurcation Ridge
ending 
Arch Loop Whorl 
angle between features Enclosure 
Short ridge 
Measuring distance and
FIGURE 5.6 Fi ngerprint analysis. 
composition and density of the surrounding amniotic fluid. A fingerprint scanner compares features of 
the fingerprint referred to as minutiae . The software focuses on points where ridge lines end or where a 
ridge splits into two bifurcations or two lines. Collectively, these unique features are referred to as typica 
(every time a ridge line splits or end its called a typica) (Figure 5.6). 
5.3.2.1.3 DNA Scanner 
The Federal DNA Identification Act in 1994 established a National DNA Indexing System (NDIS) that 
contains DNA profiles, which is part of the larger FBI DNA indexing System (CODIS) that includes 
the software and infrastructure to support this endeavor. The NDIS System is a nationwide database 
containing the DNA profiles contributed by federal, state, and local participating forensic laborato­

ries. CODIS matching algorithm searches a number of indexes, following strict rules that protect per­
sonal privacy. The CODIS algorithm produces a list of candidate matches that they referred to a DNA 
specialist. 
Source: ( http://www.nature.com/scitable/topicpage/forensics-dna-fingerprinting-and-codis-736). 
There are 13 DNA core STR Loci, points in the DNA that are used for matching purposes. An STR 
contains repeating units of a short, three- to four-nucleotide DNA sequence. The number of repeats within 
an STR is referred to as an allele. the STR known as D7S820, found on chromosome 7, contains between 5 
and 16 repeats of GATA. Therefore, there are 12 different alleles possible for the D7S820 STR. 
The FBI established the frequency with which each allele of each of the 13 core STRs naturally occurs in

The FBI established the frequency with which each allele of each of the 13 core STRs naturally occurs in 
people of different ethnic backgrounds. the FBI-determined STR allele frequencies reveals that the prob­
ability of two unrelated Caucasians having identical STR profiles, or so-called “DNA fingerprints ,” is 
approximately 1 in 575 trillion [9] (Reilly, 2001) (Figure 5.7). 
The CODIS database as of 2013 had 10 million offenders and 1.5 million arrestees, not convicted. 
You can extract DNA from almost any tissue, including hair, fingernails, bones, teeth, and bodily flu­
ids. The most commonly used database in the United States is CODIS. CODIS is maintained by the FBI. 
By law, authorities in all 50 states must collect DNA samples from convicted sex offenders for inclusion 
in CODIS. Some states also require all convicted felons to submit DNA. The FBI’s CODIS database uses 
samples that have undergone STR analysis examining 13 loci. 
5.3.2.1.4 Biometric Architecture

5.3.2.1.4 Biometric Architecture 
Biometric systems are comprised of three components: sensors that capture the trait, digital processors that 
capture and store the data, and analytical software that processes and analyzes the image. The environment 
and the quality of the reading, for example, in fingerprinting, may be damaged by some physical activity. 
Another example is voice prints that can be affected by colds. The measurement accuracy will determine

CSF1PO 13 CODIS Core STR Loci 
Known
Known 
Evidence D3S1358 with Chromosomal Positions 
D5S818 
Control
Suspect 1
Suspect 2
Cells
Control
Control 
R
R
R
R
 DNA
D7S820 
LADDE
LADDE
LADDE
LADDE
K562
Victim
Female 
Boyfriend
K562
K562
erm
D8S1179 
Sp
D13S317 
D16S539 
D18S51 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 
D21S11 
FGA 
THO1 
TPOX 13 14 15 16 17 18 19 20 21 22 X Y 
vWA 
CODIS markers 
 
134 Biomedical Informatics 
FIGURE 5.7  (See color insert.)  There are 13 genetic markers that searched in DNA samples. 
the probability of a correct match. False acceptance rate  refers to the percentage of incorrect individuals the 
system recognizes. The false rejection rate  refers to the percentage of correct individuals the system refuses. 
The failure-to-enroll rate refers to the percentage of individuals the system will not enroll due to the quality 
of a unique biometric reading, i.e., the fingerprints are so scarred individual features are not distinct enough.

of a unique biometric reading, i.e., the fingerprints are so scarred individual features are not distinct enough. 
Finally, the failure-to-acquire rate refers to the number of times it takes before the system recognizes them. 
Authentication refers to determining the validity of a user’s identity by a username, password, bio­
metrics, smart card, or some yet-to-be-determined technologies. 
5.3.2.2 Encryption: Cryptography 
The science of analyzing and encrypting data is called “cryptography.” “Encryption” is defined as encod­
ing messages or information so that only authorized parties can read them. 
5.3.2.2.1 Symmetric Key Encryption 
Two popular encryption techniques are symmetric key encryption (SKE) and PKE. SKE uses the same 
keys to encrypt and decrypt messages . The major drawback is that both systems need to have the key; this 
flaw is not true with PKE. The SKE ciphers are prone to attack using a plaintext attack if you have both

flaw is not true with PKE. The SKE ciphers are prone to attack using a plaintext attack if you have both 
sides of the message. The term was coined in Bletchley Park, England, during World War II when the 
technique was used to break German codes. 
If the keys are sufficiently random, the code can be very difficult to crack. The Data Encryption 
Standard, a symmetric cipher, was used by the NIST and later replaced by the Advanced Encryption 
Standard in 2002. 
5.3.2.2.2 Asymmetric Public Key Encryption 
Public key encryption (PKE) systems use asymmetric keys, i.e., different keys at both ends to encrypt 
and decrypt. It is virtually impossible and computationally infeasible to determine the private key from 
the original message and public key. The public key is published and the private key is only known to the 
receiver. The message can’t be decrypted by anyone but the owner of the private key (Figure 5.8).

1. Alice: Creates 2. Alice: 3. Bob:
 
A public—private key pair i Use Bob's public key and her Use Alice’s public key and his
 
ˇ	 private key to encrypt a private key to decrypt a
 message message 
Alice’s Alice’s
 
public key private key
 Bob’s Combine Alice’s	 Combinepublic key keys public key keys Anyone can create a
message but only the
private key holder can
Alice’s decrypt a message	 Bob’s 
private key	 
 
Security	 135 
private key 
FIGURE 5.8 Public key encryption system. 
VPN 
VPN 
server 
Secure tunnel 
Internet 
FIGURE 5.9 Virtual private network creates a secure connection utilizing tunneling. 
5.3.2.3 Virtual Private Networks 
A virtual private network (VPN) allows you to send information securely over the Internet as if it were 
your own private network. It sets up a virtual point-to-point connection, i.e., a permanent link between 
two users, using either dedicated connections, encrypting the traffic or virtual tunneling protocols that

two users, using either dedicated connections, encrypting the traffic or virtual tunneling protocols that 
appear as public messages. Here are some examples: Microsoft’s point-to-point tunneling protocol, 
Cisco’s Generic Routing Encapsulation, Transport Layer Security (TLS/SSL), Secure Shell VPN, and 
Internet Protocol Security  for IPv6, which uses a 128 bit address space. 
There are some advantages of VPNs: 
 1.  Message integrity, tampering can be detected. 
 2.  Messages are authenticated. 
 3. Encryption ensures confidentiality of messages. 
Before the tunnel can be established, both ends of the connection are authenticated with passwords, bio­
metrics, etc. VPNs can also be used for mobile devices by permanently connecting to a fixed IP address, 
which are referred to as mobile VPNs (mVPNs). An mVPN maintains a virtual connection even when 
the endpoint changes and seamlessly handles the network log-ins (Figure 5.9). 
Level III: Advanced Topics

Level III: Advanced Topics 
5.4 Cyber Security for Medical Devices
 
Medical devices are increasingly connected to the network to seamlessly exchange data with EHRs  
and to send remote alarms. Some systems/monitors are configured to send diagnostics to manu­
facturer and provide periodic software updates. The imbedded security on medical devices is often  
limited and susceptible to malware. The Federal Drug Administration (FDA) has published some

136 Biomedical Informatics 
lists of concerns and vulnerabilities for medical devices (http://www.fda.gov/medicaldevices/safety/ 
alertsandnotices/ucm356423.htm). 
Here are FDA warnings published on June 13, 2013: 
• 	 Network-connected/network-configured medical devices infected or disabled by malware 
• 	 The presence of malware on hospital computers, smartphones, and tablets, targeting mobile 
devices using wireless technology to access patient data, monitoring systems, and implanted 
patient devices 
• 	 Uncontrolled distribution of passwords , disabled passwords, hard-coded passwords for soft­
ware  intended for privileged device access  (e.g., to administrative, technical, and maintenance 
personnel) 
• 	 Failure to provide timely security software updates and patches to medical devices  and networks  
and to address-related vulnerabilities in older medical device models (legacy devices)

and to address-related vulnerabilities in older medical device models (legacy devices) 
• 	 Security vulnerabilities in off-the-shelf software  designed to prevent unauthorized device or net­
work access, such as plaintext or no authentication, hard-coded passwords, documented service  
accounts in service manuals, and poor coding/SQL injection 
For healthcare facilities, the FDA is recommending that you take steps to evaluate your network security  
and protect your hospital system. In evaluating network security, hospitals and healthcare facilities  
should consider 
• 	 Restricting unauthorized access to the network and networked medical devices 
• 	 Making certain appropriate antivirus software and firewalls up to date 
• 	 Monitoring network activity for unauthorized use 
• 	 Protecting individual network components through routine and periodic evaluation, including 
updating security patches and disabling all unnecessary ports and services

updating security patches and disabling all unnecessary ports and services 
• 	 Contacting the specific device manufacturer if you think you may have a cybersecurity problem 
related to a medical device; that is, if you are unable to determine the manufacturer or cannot 
contact the manufacturer, the FDA and DHS ICS-CERT may be able to assist in vulnerability 
reporting and resolution 
• 	 Developing and evaluating strategies to maintain critical functionality during adverse conditions 
5.4.1 Future Medical Security Risks for Medical Devices 
Can implantable devices such as a pacemakers or medical delivery systems be hacked? Maybe. As  
more devices are networked to provide real-time monitoring, the potential exists. Medical devices are 
microprocessors, with software, connected to dedicated hardware potentially linked wirelessly through 
Bluetooth connected to a smartphone or tablet to transmit medical data, monitor battery life, and have

Bluetooth connected to a smartphone or tablet to transmit medical data, monitor battery life, and have 
the ability for periodic software updates. These systems have rudimentary security protection, at the 
moment. In 2012 on the TV series  Homeland, a scenario was used to kill the vice president by attacking 
the software on his or her pacemaker. Six months earlier in 2012, the FDA listed guidelines to assess 
medical security risks on medical equipment. Risk assessment of potential security threats seems pru­
dent if not actually imminent. 
Risk management, as defined by the ISO 31000 (http://www.iso.org/iso/home/standards/iso31000. 
htm), refers to a coordinated set of activities and methods that is used to direct an organization and 
to control the many risks that can affect its ability to achieve objectives. According to the Introduction  
to ISO 31000 2009 , the term “risk management” also refers to the architecture that is used to manage

to ISO 31000 2009 , the term “risk management” also refers to the architecture that is used to manage 
risk. This architecture includes risk management principles, a risk management framework, and a risk 
management process. 
In a recent publication, in April 2014 by the Healthcare IT Systems, a group of cyber security  
experts were given access to a number of Midwest healthcare facilities. Over a 2-year period,

Security	 137 
they found numerous vulnerabilities in devices: the “team found that drug infusion pumps used 
for morphine drips and chemotherapy could be remotely accessed to change dosages. An another 
example, they found bluetooth enabled defibrillators that could be manipulated to deliver ran­
dom shocks and prevent shocks from happening” ( http://healthcareitsystems.com/2014/04 / 
hacking-medical-devices-is-easier-than-you-think/). 
5.5 Summary 
The HIPAA in 1996 began the process of quantifying privacy and security standards for patients’ pro­
tected health information (PHIs). Since then, computer security, in all aspects of our daily lives, has 
risen to a higher state of concern. As more of our infrastructures are mobile and linked and electronic 
transfers and payments and even watching entertainment on mobile devices have linked our planet into 
a global communications web, the security of information will be an ever-increasing concern. Will there

a global communications web, the security of information will be an ever-increasing concern. Will there 
ever be an absolute solution? No. An apt analogy would be bank robbers. As we became more urban, 
more centralized banks evolved and became more attractive targets. The technology evolved at the same 
pace to prevent theft. That has made physically robbing banks less likely or at least reducing the loss per 
incident. Electronically hacking banks and credit card companies has increased. Can we stop using 
credit cards or electronic funds transfer? The benefits clearly outweigh the risks. As one technology is 
secure, other new technologies and vulnerabilities arise. So too is the issue of medical security, the ben­
efits of EHRs, and the networked medical devices that far outweigh the risks. 
Questions 
Level I 
 1. Explain the scope of HIPAA Title II Security and Privacy. How do they differ? 
hat c
ontext do they  
 rule. 
or covered entity’s 
, disaster recovery, 
es.

hat c
 rule. 
es. 
  Privacy rule component: 
 a
. 	 Explain at least three provisions of the privacy rule; be specific. 
 b.	  Describe the public health exceptions to the privacy rule, and explain in w
apply? 
 c. 	 Describe the privacy rule exclusions for medical research. 
  Security rule component: 
 d. 	 Describe the administrative safeguards used in implementing the security
 e. 	 Explain the security rule safeguards. 
 2. When there is unauthorized access to patient data, what are the hospital’s 
required notification obligations? Be specific. 
 a.	  What are the potential penalties? 
Level II 
 3. Explain the concept of defense in depth. 
 a.	  What is IA? Explain steps to achieve IA: people, technology, operations
and system architecture. 
 4. What are access controls? Provide a few examples and specific details. 
 5.  Explain the need for encryption to enhance HIPAA Title II. 
Level III

5.  Explain the need for encryption to enhance HIPAA Title II. 
Level III 
 6. Explain cyber security for medical devices. 
 a. 	 Explain the potential security concerns for medical devices. 
 7. Research articles on examples of potential security breaches on medical devic

138 Biomedical Informatics 
Glossary 
CODIS: The program that was established by the Federal DNA Identification Act in 1994 as a national 
identification index of DNA records. 
Defense in depth: The concept that involves layers, similar to an onion, of security to ensure that if any 
breach occurs, it can be detected and repulsed. 
Privacy rule:  This sets federal standards to protect individuals’ PHI and limits to disclosure without 
patient authorization: electronic protected health information (ePHI). 
HIPAA Title II: The law that describes security and privacy, and sets limits and conditions on the use 
and disclosure of medical information without patient authorization. 
Institutional review board (IRB): Or privacy board. 
Public key encryption (PKE): A system that uses asymmetric keys, i.e., different keys at both ends to 
encrypt and decrypt. 
Symmetric key encryption (SKE): The technique that uses the same keys to encrypt and decrypt 
messages.

messages. 
Virtual Private Network (VPN):  The network that allows you to send information securely over the 
Internet as if it were your own private network. It sets up a virtual point-to-point connection, 
i.e., a permanent link between two users, using either dedicated connections, encrypting the 
traffic or virtual tunneling protocols that appear as public messages. 
References
 1. http://www.fda.gov/medicaldevices/safety/alertsandnotices/ucm356423.htm
 2.  http://www.deloitte.com/assets/DcomUnitedStates/Local%20Assets/Documents/Center%20 
for%20health%20solutions/us_chs_networkedmedicaldevice_091913.pdf 
 3. HIPAA fines for ePHI (2014) for two NYC hospitals, http://www.hhs.gov/news/press/2014pres/ 
05/20140507b.html. HHS News Release.
 4.  http://matlabsproj.blogspot.com/2012/06/iris-detection-matlab.html

 5. http://www.nature.com/scitable/topicpage/forensics-dna-fingerprinting-and-codis-736
 6. http://www.hhs.gov/ocr/privacy/hipaa/understanding/coveredentities/usesanddisclosuresfortpo. 
html
 7.  http://www.hhs.gov/ocr/privacy/hipaa/administrative/securityrule/securityrulepdf.pdf
 8.  http://www.hrsa.gov/healthit/toolbox/HealthITAdoptiontoolbox/PrivacyandSecurity/ 
entity hipaa.html 
 9. Reilly, P. (2001), http://www.nature.com/nrg/journal/v2/n4/full/nrg0401_313a.html. 
 10. Y ang, J. and Jayakumar, A. (2014). Target security breach. http://www.washingtonpost.com/  
business/economy/target-says-70-million-customers-were-hit-by-dec-data-breach-more-than­
first-reported/2014/01/10/0ada1026–79fe-11e3–8963-b4b654bcc9b2_story.html.
 11. MATLAB
®, http://matlabsproj.blogspot.com/2012/06/iris-detection-matlab.html

FIGURE 3.1 Ele ctronic health records. 
Implementation
Affordable 
Care Act 
Act 
Tools UMLS 
Expert Systems
HITECH 
Clinical Decision Support
Systems (CDSS) 
Data Entry Forms 
Interoperability Standards 
-DICOM
-ICD10 
-SNOMED 
-LOINC 
-CPT 
-HCPCS 
-HL 7 
-ISO 
-IEEE 
-FHIR 
-CDA 
-CCOW 
Hierarchy 
Diagram 
Health 
SecurityPrivacy	 
Information
(HIE) 
HIPAA 
Consumer
Mediated	 
Exchanges
Query
d Base
Personal Data 
Records 
(PDR) 
Continuity of
Care Record 
(CCR) 
Arden Syntax DSS 
Directed 
Office of the 
National Coordinator 
(ONC) EHR Spec. 
HL 7 RIM Models 
Functional Models 
Functions patient care

FIGURE 3.4 Health Level 7 Reference Information Model models a visual representation of domains and messages exchanged. (From http://www.h l7standards.com/ 
blog/2011/05/31/hl7-v3-rim-is-it-really-that-intimidating/.)

OS
I 7 Layer 
Model 
Transport 
Internet
8. User U l 
7. Message format, human machine interfaces p
p a 
Application header 
e e 
y6. Convert into 0’s, 1’s, and encryption
Permission and authentication 
Presentation 
header5. r r 
Network4. Complete end to end error checking transport n TCP 3. Networkheaders3. Network addressing p Packet 2. Data2. Flow control o 
1. Bits, physical hardware r Frame 1. Physical
t 
 
(a) (b) 
FIGURE 3.16 (a, b) Navigator on left; patient status view on right. 
(a) (b) 
FIGURE 3.17  (a, b) Medication Administration Record (MAR) delivery timetable, MAR drug summary table. 
(From http://www.pearsonhighered.com/realehprep/learn-about/what-is.html .) 
FIGURE 4.3 ISO s even-layer model.

FIGURE 4.20 RxNav visualization engine visualizing the same drug from multiple manufacturers.

(Health Insurance Portability and Accountability Act 1996) 
(Policies and procedures) 
Privacy:	 Security
that sets limits and conditions on the use and the safeguards that must be in place to ensure 
disclosure of medical information without appropriate protection of electronic Protected 
pattent authorization Health Information (ePHI) 
Physical Technical 
(controls) (controls) Exceptions Lubliner 2013 
Public health Research Breach notification Encrypted PHI 
1. 	Compromises a patient’s health; i.e., a
 -Breaches: 2. Public health is threatened -Involving more than 500 individuals the security3. Research (anonymized data)
1. 	With the permission of an IRB or  rule require that they notify HHS immediately.
-More than 500 individuals requires media be notified       Privacy Board, the patient's privacy -Encrypted PHI:

Security Primer Biometrics 
Defense in depth Information assurance (F5.com term is defenseProtect, detect and react in Breath)
 
People DNS Web Access
 
Technology Dynamic threat defense
 
DDOS protection
 
Operations 
Protocol security 
 FIGURE 5.1 Security and privacy.

CSF1PO 
D3S1358 
D5S818 
D7S820 
D8S1179 
D13S317 
D16S539 
D18S51 
D21S11 
FGA 
THO1 
TPOX 
vWA 
13 CODIS Core STR Loci 
with Chromosomal Positions 
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 
13 14 15 16 17 18 19 20 21 22 X Y 
LADDER
K562 Control
LADDER
Victim
Suspect 1 Known
Suspect 2
Female Cells
Evidence Sperm DNA
LADDER 
Boyfriend Known 
LADDER 
 
P4 
P1 pa pb 
P3dθ 
pd 
pc 
P2 
Ri 
Rp 
Ci 
Cp 
θ 
FIGURE 5.5 Biometric input and retinal analysis, using phasors (vectors in a plane). (From MATLAB ® http:// 
matlabsproj.blogspot.com/2012/06/iris-detection-matlab.html; Photo courtesy of Iridian Technologies.) 
FIGURE 5.7 There are 1 3 genetic markers that searched in DNA samples.

EndoWrist   instruments are 
designed with seven degrees
of freedom and mimic the 
dexterity of the human hand Patient and wrist. cart 
Anesthesiologist 
Vision 
cart 
Assistant 
Nurse 
Surgeon uses open-surgery
hand movements that are 
precisely replicated in the
operative field by the
EndoWrist instruments. 
Surgeon at
console 
 FIGURE 6. 2 da Vinci telesurgery system. (From IntuitiveSurgical.com, parent company.)

Medical Apps—On-Demand Doctors’ Visits (Live Video Consultations and Text Chat Health Inquiries) 
Ringadoc 1. 1000 physicians in 40 states $69/month or $868/year 
http://www.ringadoc.com/ 2. Different from other systems that 
select a doctor from an available 
online pool for a consult; options 
include the following: 
 a. Connect with a single primary care 
physician. 
  b. Leave a text message with the 
urgency of situation. 
c. Choice of a larger network of 
physicians. 
Doctor on Demand 1. Licensed physicians $40 per call 
http://www.doctorondemand.com/ 2. Nonemergency medical issue 
3. Pediatric questions 
4. Prescriptions 
5. Specialist referral 
Examples 
Short-term Cold, flu, 
prescriptions  cough, fever, 
and Rx refills allergies 
Urinary tract  Pediatric fever, 
infections advice, or 
other issues 
Vomiting/ STDs 
diarrhea 
Rashes/bites/ Sports injuries, 
3G Doctor (United Kingdom and 
skin problems athlete’s foot 
1. 24 hours day. £35 per session

diarrhea 
1. 24 hours day. £35 per session 
Ireland) 2. Live video chat with a licensed 
http://www.3gdoctor.com/ doctor. 
3. On-demand doctors are available to 
diagnose and address minor medical 
 problems such as rashes, aches, or 
pains. 
4. Doctors can recommend treatments 
and answer health-related questions. 
5. Real-time access to your medical 
records. 
(Continued) 
TABLE 6.4 Examples of On-Demand Medical Consultation Apps

Live Chat (consult)
 
Live Person
 
https://www.liveperson.com/experts/
 
health-medicine
 
ConsultADoctor
 
http://www.consultadr.com/
  
Health book/Health Kit (Apple) 
https://developer.apple.com/ 
healthkit/ 
1. A text chat $1.50/min 
2. Consult a live medical practitioner 
3. Doctor, nurse, oncologist, dentist, 
physical therapist, nurse, allergist, 
optometrist, chiropractor, 
pharmacologist, pregnancy/ 
childbirth specialist, or sex therapist 
4. A detailed list of verified 
professionals to select from 
5. Other specialties, education, 
programming 
1. A service provided for health plans 
that can be tailored for employers to 
service the health needs of their 
employees 
2. Nonemergency, preventive, and 
routine health issues 
3. Provides EHRs through the company 
1. System for integrating health and 
fitness data across Apple’s product 
lines, including charting and

lines, including charting and 
long-term trending and individual’s 
health and fitness progress. 
2. It is a part of IOS 8. 
3. The iWatch will provide additional 
biometric sensors that will pool all 
these data into a single location. 
TABLE 6.4 (Continued) Examples of On-Demand Medical Consultation Apps

TABLE 6.6 Productivity Apps for Physicians 
Mobile MIM 
Radiology Visualization Software 
http://www.mimsoftware.com/about/news-center/ 
Merge iConnect Access System 
Radiology imaging 
http://mobihealthnews.com/15782/ 
merge-healthcare-focuses-on-mobile-access-not-apps-for-remote-medical­
imaging/ 
drawMD 
http://www.drawmd.com/ 
Allows physicians to make diagnosis 
remotely after analyzing CT and MRI 
scans 
• Approved by the FDA 
• Primarily targeted at radiologists 
• Take notes; share information 
• Tools to measure and highlight features 
of the scan 
• Zoom in on details of the image 
• Voxel-based analysis 
• Region-based analysis 
• SUVR computation 
• Cluster analysis 
• Surface projection analysis 
• Quantitative functional 
neuroimaging software
 
• Sliding one finger across the iPad screen 
changes the contrast and grayscale of a 
radiological image. 
• Buttons on the screen allow for 
additional image manipulation. 
• A patient history fly-out menu on the

• A patient history fly-out menu on the 
edge of the patient screen allows 
viewers to bring up as many as three 
studies simultaneously for side-by-side 
comparison. 
• Allows physicians to show details of 
what a surgery entails. 

http://www.visiblebody.com/ap/ipad/ describe issues to patients. 
• Medical students have detailed 
anatomical models. 
• Diagnosis and treatments. 
• Allows doctors to hold video 
conference with patients. 
 
Source: Mobile Medical Productivity Tools. http://www.mednet-tech.com/newsletter/mobile-marketing/top- mobile- apps-
for-doctor s. 
Electrical and chemical Data acquisition: Medical sensors Wireless medical 
conduction basics basic theory and measurements monitoring 
Action potential Electrical conduction Body sensorSubatomic particles Current flow Valence electrons Heart Blood pressure networks (BNSs)c 
Battery chemistry Inductive charging Pulse oximetry 
(ATP) Adenosine triphosphate Lambert-bouguer law i
I = Io e–(ad)
Beer’s law nc i
i = V 
Absorbance (ad) = εcd Data mining and big
Anatomy and physiology primer

i = V 
Anatomy and physiology primer 
Part I: Neurons and nervous system, Part II: Cells, ATP , hearing, kidneys, Part III: Lungs, immune system, strokes, Part IV: Heart disease, cancer brain, spinal cord, muscles, heart, eye pancreas, liver, digestive system blood flow, prostate 
FIGURE 7.1 Medical sensor primer. 
Visible Body • 3D human anatomy allows doctors to 
TABLE 6.6 (Continued) Productivity Apps for Physicians

Periodic table and valence Explanation of Ohms law V = I × Relectrons and conductors subatomic particles
building blocks
 
2E=m c
relationship
between matter
 
and energy
 
Fiber optics quantum
mechanics Inductive charging 
Chemistry and physics of batteries
Alkaline batteries: (ZnMnO2) 
Chemistry: Zn(s) + 2OH –
(aq) ZnO(s) +H 2O(l) +2 e –[e° = 1.28 V] 
2MnO2(s) +H 2O(l) +2 e – Mn2O3(s) + 2OH –
(aq)[e° = +0.15 V] 
FIGURE 7 .2 Linkages between topics covered in the first section. 
Periodic table of the elements Fission chain reaction: 
(A) U235 bombarded by one neutron 
Atomic number (B) Results in fission of its nucleus, i.e., breaks apart 
Symbol Producing krypton, barium and three neutrons 
Atomic weight [1][2][3]These three neutrons bombard other U235 atoms 
(C) Creating a self-sustaining chain reaction 
[C] 
[B] 
[A] [1] 
[2] 
[3] 
Uranium isotopes
 
Mass number Natural abundance Half-life
 
234 0.0054% 2.455 × 10 +5 years

[C] 
[B] 
[A] [1] 
[2] 
[3] 
 
234 0.0054% 2.455 × 10 +5 years 
235 0.7204% 7.04 × 10 +5 years Fission picture source: http://chemphys.u­
238 99.2742% 4.468 × 10 9 years strasbg.fr/mpb/teach/MerlinMarcello/images/fission_ch.gif 
FIGURE 7.3 Uranium isotopes and fission chain reaction. 
The Proton (+ve) is made up of three
(valence) quarks: two up quarks and one downu C t g H quark: HiggsUp Charm Top Gluon boson u u 
LEPTONS QUARKS 
d S b γ d 
Down Strange Bottom Photon 
The Neutron (no change) is made up of three
(valence) quarks: one up quark and two down
e μ τ Z 
GAUGE BOSONS 
quarks: 
Electron Muon Tau Z boson 
Protons and u dneutrons are bound 
together via the
nuclear force 
ν
e νμ ντ W 
Electron Muon Tau 
 
Electrical and chemical conduction primer: electrochemistry 
neutrino neutrino neutrino W boson d 
Standard_Modal_of_Elemantary_Particles svg (SVG file, nominally 774 × 581 pixels, file size 419 KB)

Standard_Modal_of_Elemantary_Particles svg (SVG file, nominally 774 × 581 pixels, file size 419 KB) 
FIGURE 7 .4 Standard model of elementary particles inside a nucleus. (From Creative Commons, http://home. 
web.cern.ch/about/physics/standard-model).

(elements in vertical columns have same properties)
(Copper (Cu), Silver (Ag), Gold (Au) good conductors 
[2, 8, 18, 1] 
Cu 
Ag 
Au 
Zachary Lubliner 2015 
Electrons circulating a nucleus 
-Valence electrons are the 
electrons contained in the 
outermost, or valence, 
electron shell of an atom. 
Valence electrons are 
important in determining how
an element reacts chemically
with other elements: 
Neutrons 
Good conductors 
Protons 
Periodic table 
of the elements 
HE-Helium 
NE-Neon 
Ar-Argon
Kr-Krypton
Don’t interact 
Insert gases 
AU-gold atomic #79
CD-Cadmium #48 
CU-Copper #29
HG-Mercury
ZN-Zinc #30 
RG-roemigen #111 
IB and IIB 
AG-Silver(a) 47 
Copper 
Copyright David Lubliner NJIT 2014 
+ 2 
Ks 
Ls 
Lp Ms 
Mp 
Ms Ns 
2 6 2 6 10 1 
K = 2+(12) = 2
L = 2+(22) = 8
N = 2+(32) = 18
N = 2+(42) = 32 
Thus the maximum number of 
electrons that each of the 
first four shells can hold is: 
(a) 
Electrical properties of atoms 
Periodic table of elements Atomic structure

(a) 
Periodic table of elements Atomic structure 
1 electron, Valence shell 
Electrons: Valence shell: outmost shell that 
interacts electrically and chemically.
Copper (CU) 
–29 Electrons, +29 Protons, 35 Neutrons 
Each shell starting with innermost
Silver (Ag)
–47 Electrons, +47 Protons, 61 Neutrons 
[2, 8, 18, 18, 1] 
Gold (Au) 
–79 Electrons, +79 Protons, 118 Neutrons 
[2, 8, 18, 32, 18, 1] 
(b) 
 FIGURE 7 .6 Va lence electrons, in an atom’s outer shell, conduct current (I). (a) Copper (Cu), silver (Ag), and 
gold (Au) valence electrons. (b) Conductors in the periodic table group 11, all have 1 electron in their valence shell.

atom atom atom atom 
atom 
atom 
atomatomatomatom 
atom 
atom 
atom 
–1 
–1 
–1 
–1 –1 –1 –1 –1 
–1 
–1 
–1–1 
–1 
–1 
–1 –1 
– + 
–1 –1 –1 
–1 
Atoms 
need 
electrons 
Battery
More electrons More Protons 
Lithium Ion Battery Architecture 
(http://www.nexeon.co.uk/technology/about-li-ion-batteries/) 
e – 
e – 
e – 
e – 
e – 
e – 
e – 
e – 
Li+ 
Li+ 
Li+ 
Li+ 
Li+Copper
negative 
current 
collector 
Aluminium 
positive 
current 
collector 
LixSi Li1–xMO2 
Li+ conducting electrolyte 
+– 
C + LiCoO2 LiC6 +L i0.5CoO2 
No net gain in the number of electrons
(one electron enters the wire) knocks
the existing electron out of its valence
shell and takes its place 
Electrons Moving Through A Wire (Yellow Wire) 
The maximum speed
electromagnetic energy can
travel through empty space=
186,000 miles per second 
-In a wire the speed is
approximately 2/3 that speed
-In a biological entity its
about 100 feet per second 
If each atom has 5 electrons 
and 5 protons with a zero net
charge to begin with

charge to begin with 
If one electron is stripped off
now have right side
    positive (+5–4 = +1)
    For the left side 
(+5–5)= 0 
electron moved here 
. y r e t at m ion b u i h t i nd l re a i h a w g rou h g t n i ) mov l l e h e s nc le a v s ( on r t c le nd e y a r e t at B7   7 . E R U G FI

1. Action potential release
acetylcholine: an organic molecule Excitation-contraction coupling (ECC)
 
    that acts as a neurotransmitter
 www.nature.com Action potentials in cardiac
 
Muscle cell myocytes
 Motor neuron ions +ve 
(membrane potential dotted line) Ca2+ (calcium) +123 mv) 
Na+ (sodium) + 67 mv) 
20 mv 1 
5 mv 2 balanced 
depolarization 0 mv 
0 fast action potential 3–70 mv 
–90 mv 
They have repeating 2. Myofibril: tube- 4 relaxed state 4 relaxed state 
K+ (potassium –92 mv) sacromeres which contract:     like structures
defined as a region of     propagate signals
 –ve 
microfilaments composed of  inside the muscles 
myosin and actin 
Brain 
Pulmonary vein: a vein that carries
oxygenated blood from the lungs to the left
Lungs 
atrium of the heart. 
(It’s the only vein that carries oxygenated blood) 
Artery 
To lungs To lungs 
Pulmonary
veins from 
lungs AD PA 
Pulmonary veins 
from lungs 
Pressure exerted 
by blood 
© 2010 Medicine Net, Inc. 
Un-oxygenated

Pulmonary
veins from 
lungs AD PA 
from lungs 
by blood 
blood flows back 
to heart in veins 
Heart 
arteiole and 
capillates (body) 
oxygenated
blood flows 
away from the
heart in 
arteries 
Pulmonary valve 
Tricuspid
valve 
Superior 
vena cava 
Atrial septum 
Inferior 
vena cava 
RA 
RV 
LA 
LV 
Oxygenated rich 
Oxygen poor 
PA = Pulmonary artery 
AO = Aorts 
Ventricular 
septum 
RV = Right ventricle 
LV = Left ventricle 
LA = Left atrium 
RA = Right atrium 
Aortic valve 
Mitral valve 
http://www.emedicinehealth.com/high_blood_pressure/article_em.htm. http://reyesdiannemarie.wix.com/oxygenation#gallery 
 
FIGURE 7 .15 Cardiac myocytes and the ECC action potential triggered by sodium, calcium, and potassium ions. 
FIGURE 7 .19 Bloo d pressure exerted on the artery walls.

Neuron 
Sodium potassium pump 
Dendrites	 Sodium potassium pumps move sodium (Na+) and
potassium (K+) ions across the neuron cell throughSchwann cells 
Nucleus (insulation)	 gaps in the membrane. The purpose is to create a
make up the voltage strong enough to draw electrons across the
Na+ 
–Ve Myelin sheath
K+	 synapse, a gap between neurons. 
Cell body or Axon soma Extracellular space 
Na+ 
Nodes of ranvier PotassiumSodium(spaces)	 K+ 
Na+ 
Voltage gated
cells to propagate
strength of signal
 Cell membrane 
Concentration
Synapse (gap ATPbetween axons and 
other dendrites) ADP Pi 
Intracellular space 
K+ 
Scheme_sodium-potassium_pump-en.svg (SVG file, normally 635 × 285 pixels, file size 192 KB) 
http://en.wikipedia.org/wiki/File: Scheme_sodium­
potassium_pump-en.svg 
Blood 
pressure 
Glucose 
implantable 
Pedometer
 
with GPS
 
There are a number of standards for this evolving
field to standardize these integrated systems 
ISO/IEEE 11073 - Low-level data standards for

plug and play devices integrated into these BSNs
that can contain a maximum of ten connected 
devices. 
The Integrate Heath Environment (IHE) Patient
Care Domain (PDE) is a joint effort by multiple
medical sensor vendors to standardize 
interoperability between sensors and device
interfaces. They are associated with Health
Information Management Systems Society
(HIMSS) and the American College of Clinical
Engineering (ACCE) 
Wireless 
data Smart phone or Tablet used
transmission as a hub to aggregate and
process wireless data 
Pulse oximeter Compressed data stream 101010 (reduces data for
an estimated patients population of 107) from
Petabytes (PB 1015) to Gigabytes (GB 109))
Critical data min/max points transmitted 
FIGURE 7 .20 Neurons and signal transmission across synapses.

FIGURE 7 .20 Neurons and signal transmission across synapses. 
FIGURE 7 .25 Cas e study: BSN data capture integrated into a Smart phone and then forwarded to Cloud storage.

Neurons and the Central Nervous System 
The Central Nervous System (CNS) contains two major
types of cells, Neurons and Glia. They are responsible for
transmitting information. Neurons make up our brains,
information processing system, and communicate signals
throughout our body. (movement, sensory and healing).
Neurons are electrically excitable cells that
communicate information through electrical and
chemical signals. Neurons are connected via synapses, a
gap between neurons, that allows a neuron to pass an
electrical or chemical signal to another neuron. (refer to:
Chapter 7, Neurons/Action Potential).
Dendrites 
Rough ER
(Nissl body) 
Polyribosomes 
Ribosomes 
Golgi apparatus 
Nucleus 
Nucleolus 
Membrane 
Microtubule 
Synapse
(Axodendritic) 
Neurofibrils 
Neurotransmitter 
Receptor 
Synapse 
Axonal terminal 
Node of ranvier 
Synaptic cleft 
Synapse (gap
Synaptic vesicles 
Dendrites Axon 
Microfilament 
Axon hillock Myelin Sheath
Synapse
between neurons)

Synapse
between neurons) 
Synapse (Axoaxonic) 
Nucleus 
(Schwann cell) 
(Insulation) 
(Axosomatic) 
Mitochondrion 
Smooth ER 
   Sodium(Na+)–Potassium(K+)
pumps move positive ions
(Na+ and K+) across the synapse
to make one side more positive
(voltage / potential difference)
so current flows (electrons)
from negative to positive. 
Glial cells surround the 
Synapse 
K+ 
Na+ 
Result –VE +VE voltage neurons and provide support
and insulation between neurons 
(composed of Schwann, microglia,
astrocytes, satellite and ependymal cells).	 Dendrites: Are thin protrusions from the cell body of a neuron that collect chemical
and electrical signals from other neurons. Axons: Are the projection of a neuron that
conducts electrical impulses away from the cell body to the axon terminals 
Level IV: Anatomy and Physiology Primer 
 
Brain

Brain 
The Cerebrum, it’s the evolved part of the brain, the largest part of the
human brain, which comprises 4/5 of its weight. It consists of about two-
thirds of the brain mass and lies over and around most of the structures of 
the brain. The outer portion ranges in thickness between 1.5 and 5 mm,
and is covered by a thin layer of gray tissue called the cerebral cortex. It is
divided into right and left hemispheres
that are connected by the corpus callosum. 
Cerebrum includes the hippocampus, olfactory bulb and basal ganglia 
-Hippocampus, part of the limbic system involved in the integration from
short-term to long-term memory 
-Limbic System: emotion, behavior long term memory
-Olfactory bulb: sense of smell 
-Basal Ganglia: voluntary movements, learning, eye movements, emotion 
The Cerebral Cortex surface, folded in large mamals. Two thirds of the

surface is embedded groves (valleys) called the “sulci”. The ridges are called 
“gyri”. 
Frontal lobe: voluntary movement, planning. Though 
Parietal lobe: includes the somatosensory cortex: touch 
Temporal lobe: hearing and comprehending speech 
Occipital lobe: visual processing center © Lubliner 2015 
The Cerebellum involved in motor control. The functions include balance, 
voluntary movements, motor learning, and some congnitive functions
(language); (10% volume, but contains 50% of neurons brain. 
Mid BrainThe Brain Stem includes the midbrain, Pons 
and medulla oblongata. Functions include the
Pons 
cardiac, respiratory and autonomic (involuntary
functions), blood pressure and heart rate. 
Medulla 
Cerebral Cortex	 Right brainLeft brain 
Frontal lobe Parietal lobe 
Analytical thought
language 
Creativity
Art and Music 
Temporal lobe

Medulla 
language 
Temporal lobe 
Cerebellum 
(Older part brain) 
Hippocampus 
Major internal parts of the Human Brain 
Cingulate
Sulcus 
Corpus
Callosum 
Dioncophalon 
Olfactory bulb 
en.Wikipedia: public domain 
Basal ganglia (purple) 
Occipital
lobe 
Brainstem 
Anterior 
Commissure 
Temporal
Lobe 
Midbrain 
Pons 
Medulla 
Motor cortex 
Premotor 
cortex 
SMA 
Primary motor cortex 
The Motor Cortex 
involved in control of 
volutary actions 
Primary Somatosensory
cortex Posterior 
parietal
cortex 
Level IV: Anatomy and Physiology Primer

Eye Anatomy of Human Eye 
The Eye detects electromagnetic radiation (light) and Pupil CorneaIrisconverts it into electro-chemical impulses in neurons. Posterior chamber Anterior chamber 
Zonular (aqueous humour) 
fibres Lens Ciliary muscle 
Light enters through the cornea and passes through the Suspensory
pupil. The pupil is surrounded by the Iris, that controls ligamentRetina 
Vitreous the size and diameter of the pupil. Behind the pupil is Choroid humourthe lens that focuses light onto the retina that has Sciera 
photoreceptor cells. Hyaloid
canal 
The Retina is a light sensitive layer of tissue made up Optic disc 
of photoreceptor cells located at the back of the eye. It's
made up of Rods which are used in peripheral vision, Optic nerve Fovea 
and Cones, responsible for color vision. Retinal 
blood vessels 
The actual image is portrayed Visible light has a wavelength in the range of 400

upside down on the retina. The Image inverted by the eye nanometers (nm), or 400 × 10−9 m, to 700 nm 
process of reinventing the image is Focal pointa combination of brain architecture 
and processing of the image. (It 
starts at the optic nerve where there 
is a crossing of axons in the optic 
chiasm to the lateral geniculate 
nucleus and then to the primary visual 
cortex.) 
Photosynthesis 
Process by which green plants and certain
other organisms transform light into
chemical energy.
 
In green plants, light energy is captured by
chlorophyll in the chloroplasts of the leaves
and used to convert water, carbon dioxide,
 
and minerals into oxygen and energy-rich
organic compounds (simple and complex
sugars) that are the basis of both plant and
animal life.
 
During the light-dependent stage (light

reaction), chlorophyll absorbs light energy,
which excites some electrons in the pigment
molecules to higher energy levels; these 
Photosynthetic membrane
(thylakoid membrane) H + 
leave the chlorophyll and pass along a 2H+ +½ O2
series of molecules, generating formation of Lumen
 
NADPH (an enzyme) and high-energy ATP 
H2O
 
molecules.
 
The NADPH oxidase (nicotinamide adenine dinucleotide H +
 
phosphate-oxidase) complex is an enzyme complex. Photo-
photo- systemsystem IIIt generates superoxide by transferring electrons from I2e– 
NADPH inside the cell across the membrane and coupling 2e–
 
these to molecular oxygen to produce the superoxide, which ATP
NADP+ 
Electron synthesisis a highly reactive free radical. + 2H+ 
H + 
ATP ADP P 
NADPH+H+ 
carriers 
Stroma 
Light H + 
To Calvin cycle
or dark reaction
© 2006 Herramienta Inc. 
Light
energy

H + 
ATP ADP P 
NADPH+H+ 
carriers 
Stroma 
Light H + 
Light
energy 
Basic photosynthesis 
Oxygen 
Sugar 
Carbon dioxide 
Water 
6CO2+ 12H2O + Light      C6H12O6+6 O2+6 H2O 

Kidneys 
Your kidneys are two bean-shaped organs, each
about the size of your fist. They are located in the
middle of your back, just below your rib cage, on
either side of your spine. Your kidneys weigh
about 0.5% of your total body weight.
 
Although the kidneys are small organs by
weight, they receive a 
huge amount—20%—
 
of the blood pumped by the heart.
 
The large blood supply to your kidneys
enables them to do the following tasks:
 
Regulate the composition of your blood 
keep the concentrations of various ions and
other important substances constant
 
keep the volume of water in your body
 
constant
 
remove wastes from your body (urea,
ammonia, drugs, toxic substances)
keep the acid/base concentration of your
blood constant
 
Help regulate your blood pressure 
Stimulate the making of red blood cells 
Maintain your body’s calcium levels 
Right Kidney Sectioned in Several Planes 
Liver (continued)

Liver (continued) 
Anterior and posterior views of the liver. 
Bile duct 
Kupffer cells 
Blood vessels 
Hepatic cells 
EB Inc. 

Lungs 
They take in oxygen, a gas that your body needs,
and gets rid of waste carbon dioxide
made by your cells.
 
You breathe in and out anywhere from 15 to 25
times per minute.
 
They also help in regulating the concentration of
hydrogen ion (pH) in your blood.
 
You don’t have to think about breathing because
your body’s autonomic nervous system
controls it.
 
The respiratory centers that control your rate of
breathing are in the brainstem or medulla. The
 
nerve cells that live within these centers
 
automatically send signals to the diaphragm and
intercostal muscles to contract and relax at
 
regular intervals.
 
Immune System 
AIDS 
AIDS (Acquired Immune Deficiency
Syndrome) is a disease caused by HIV (the
Human Immunodeficiency Virus). This is a
particularly problematic disease for the
immune system because the virus actually
attacks immune system cells.
 
In particular, it reproduces inside Helper
T cells and kills them in the process.

T cells and kills them in the process. 
Without Helper T cells to orchestrate
things, the immune system eventually
collapses and the victim dies of some 
other infection that the immune system
would normally be able to handle. 
HIV invades the cells of our immune system
and reprograms the cells to become HIV-
producing factories. 
Viruses, like HIV, don’t have cell walls or a nucleus. 
Basically, viruses are made up of genetic instructions
wrapped inside a protective shell. An HIV virus 
particle, called a virion, is spherical in shape and
has a diameter of about one 1/10,000th of a millimeter. 
Ahreoli enlarged 
Alveoli 
Bronchiole 
Terminal 
bronchiole 
Ter tiar y
bronchus 
Primary
bronchus 
Secondary
bronchus 
Photo courlesy National Institute
of Allergy and Infectious Diseases
HIV. the virus that causes
 
AIDS. Is shown budding
out of human immune
 
cell.
 
HIV Replication Animation 
gp120
envelope
protein

cell.
 
gp120
envelope
protein 
gp41
envelope
protein 
RNA 
p17
matrix 
proteins 
Lipid
membrane 
p24
capsule
proteins 
Reverse 
transcriptase 
Anatomy of the AIDS virus 

Y Coll 
MRI scanner gradient magnets 
Z Coll 
X Coll 
Transceiver 
Patient 
Magnetic field
lines 
Current out 
Current in 
S 
N 
  
k 
i 
j 
Sxz P 
L 
Ry A 
I 
FIGURE 8.6 Reference coordinate system diagrams relating scanners and individual 2D slices. ( Source: Image 
from http://www.slicer.org/slicerWiki/index.php/Coordinate_systems) 
fMRI 1990s Whole body scans 21stMRI (1946–1977) (HARDI) High AngularX-ray 1895–1903 CT(contrast)1972–1980 Resolution Diffusion Imaging 
Hold 
head 
stable 
http://igc.ini.usc.edu/mathematics/ 
FIGURE 8.11 Evolution in medical imaging technology. 
FIGURE 8.16 MRI s can, schematic of scanner gradient magnets, and magnetic fields generated. ( Source: Images 
from the National High Magnetic Field Magnetic Lab., at the Florida State University, http://www.magnet.fsu.edu / 
education/tutorials/magnetacademy/mri/fullarticle.html)

FIGURE 8. 25 Indexing images, ImageCLEF tools by shape, color, or texture. 
Principal components
Original waveforms reduction Noisy medical image Dimensionality reduction 
Potential 
turnor 
A Variable with high
variance to discriminate 
important data 
FIGURE 8. 26 Digital image processing architecture. ( Source: From http://www.ncbi.nlm.nih.gov/pmc/articles/ 
PMC3701154/figure/F1/)

FIGURE 10.1  A critical care nurse provides care for a patient in the immediate postoperative period after cardiac 
surgery. 
FIGURE 10. 2  The data that are generated on a critically ill patient often include far more than just vital signs. 
Pictured are the screens from a continuous cardiac output monitor, an intra-aortic balloon pump, a continuous 
renal replacement therapy device, and a ventricular assist device. All of the aforementioned parameters and num­
bers are recorded every hour.

FIGURE 10.11  Smart medication infusion pumps and cardiac monitors are capable of communicating directly 
with the electronic health record (EHR) to download the dose and rate. If this capability is not enabled by the sys­
tem, the nurse is responsible for typing every number into the EHR, usually every hour.

Level I: Core Concepts ................................................................................. 140
 
6.1 	 Introduction ...................................................................................... 140
 
6.2 	 Telehealth ........................................................................................... 140
 
Telemedicine • mHealth
 
Level II: Distributed Healthcare ..................................................................151
 
6.3 	 Introduction .......................................................................................151
 
6.4 	 Medical Apps for Remote Healthcare ........................................... 152
 
6.5 	 Urgent Care Centers ......................................................................... 152
 
Urgent Care Certification Criteria
 
6.6 	 Miniclinics ......................................................................................... 156
 
U.S. Miniclinics • Miniclinic Certification Criteria

Level III: Advanced Topics ........................................................................ 158
 
6.7 	 Mobile Tools to Support Physicians ............................................... 158
 
6.8 Summary ............................................................................................ 160
 
Questions ....................................................................................................... 160
 
Glossary ..........................................................................................................161
 
References .......................................................................................................161
 
6 
Telehea lth
 
139

140 Biomedical Informatics 
6.1 Introduction
 
Telemedicine is the practice of medicine or analyzing medical data remotely. Communications technology 
has reached the singularity point, often referred to as a transformational event. In artificial intelligence, the 
singularity is the creation of intelligent machines, or in astronomy it’s a property with infinite mass such 
as the center of a black hole or the universe before the “Big Bang,” not the TV show, my personal favorite. 
Instant communications is ubiquitous, which is the first essential part of telemedicine. The second is qual­
ity wireless medical monitoring device-software, and some are currently available: iHealth, Fitbit
®, FlexTM, 
and the iWatch. All have medical monitoring technology, this is just the beginning. The term “mHealth” 
is linked to this second step; it refers to medical practice using mobile monitoring devices, a subset of the

is linked to this second step; it refers to medical practice using mobile monitoring devices, a subset of the 
larger telehealth field. The last is the overwhelming need to pivot to telemedicine. In the United States, 
10,000 baby boomers hit 65 every day. Healthcare companies are trying to reduce hospital stays and the 
Affordable Care Act (ACA) is focused on prevention strategies. Telehealth [9] fits the bill for prevention, 
i.e., responding in a timely fashion before conditions become acute and require hospitalization or monitor­
ing recently released inpatients. Telemedicine should become mainstream (Figure 6.1). 
Telemedicine is the use of medical information exchanged from one site to another via electronic 
communications to improve a patient’s clinical health status and delivery of remote clinical ser­
vices using technology [1]. 
American Telemedicine Association (http://www.americantelemed.org) 
6.2 Telehealth

6.2 Telehealth 
Telehealth is an all-inclusive term encompassing remote healthcare and all its support services that are 
delivered utilizing the Internet and wireless/wired communications. Telemedicine is a more narrow 
definition that refers to the delivery of treatment or diagnoses remotely (Figure 6.1). The following is an 
example of the distinction between the two terms: Telemedicine would include the remote diagnosis 
by radiologists, using teleradiology tools, but the transmission infrastructure of Digital Imaging and 
Communications in Medicine (DICOM), the standards for encoding and transmitting medical images 
(see Chapter 8), would fall under the larger definition of telehealth. 
Medicine anywhere is becoming the new norm with the proliferation of smartphones, tablets, and

Medicine anywhere is becoming the new norm with the proliferation of smartphones, tablets, and 
high-speed Internet, fixed and wireless; it has removed many of the previous limitations. Real-time video 
is common and wireless medical devices provide physiologic data. Access to a patient’s medical records, 
one of the last missing components, is almost universally available. Electronic health records (EHRs) now 
tie everything together. A patient walks into an urgent care center or a less acute miniclinic and his or her 
complete patient records can be accessed immediately. Once the last missing piece, the incompatability 
of EHRs, is completely addressed through health information exchanges (HIEs) that integrate different 
systems into a coherent view which are currently under way, distance will no longer be an issue in most 
situations. Trauma, heart attacks, etc. that require immediate attention are the exceptions. Even these life

situations. Trauma, heart attacks, etc. that require immediate attention are the exceptions. Even these life 
threatening conditions are being addressed with implantable defibrillators [10]. 
New technologies, e.g., apps for remote healthcare, such as Doctor on Demand and Ringadoc, pull on 
a large pool of verified professionals, who can provide simple diagnosis and treatments, or at least triage a 
condition immediately and recommend a course of action. The old house calls can be replicated, in most 
cases, by these new technologies. Prevention, a key mandate from the Affordable Care Act (ACA), can be 
more effectively delivered if illnesses can be diagnosed and treated before they become acute. Catching 
outbreaks can be more expeditiously discovered using remote health technology. This chapter discusses 
those technologies, part of the panoply of skills, needed by informatics professionals, the complex inter­
play of systems and software that create the web of healthcare.

Telehealth 
Telemedicine (Delivery of Services and Diagnosis) 
mHealth
Communications (Mobile wireless medical Teleradiology CCRN-E Cost/NeedTelesurgerydevices and software) and medical consults AACN cert.
© Lubliner 2013 -90% radiologists are inWaveLan mHealth FDA Approved   large remote groups -Monitor 10,000 babyIEEE 802.11n 600 Mbit/s First-generation wireless da Vinci System -In 2013, the top 100 firms critically ill boomers reach 65IEEE 802.11ac 6.93 Gbit/s medical devices, 2013  million perf.1.5   have 5,000 radiologists patients every dayWireless Personal Networks Second generation, 2014, -Specialists provide expert  remotely 
Bluetooth4 24 Mbits/s iHealth, Fitbit, iWatch   opinions 24/day -Consultation
IrDA-UFIR 96 Mbits/s Telemental Affordable Care
WUSB 480 Mbits/s Implantable medical devices health Nurse Act focus on
preventionIrDA-GigalR 1024 Mbits/s Teleeducation working in
Home monitoring of patients Crisis response teleICU
and devices: EKG, implantable or eCCU

 -Reduce inpatientassist devices Some apps deliver services that fall under telemedicineElectronic health   costs
records -Reduce cost of Doctors-on-Demand app1. -Reimbursement Qualifications:
Miniclinics (will RN 5 years large facilities RingaDoc.com2.   by medicare require remote consults) with critically outpatient ER SNOMED, ICD11, HL 7, DICOM 3. 3GDoctor.com England -Rural areas ill patients 
Telehealth 141 
FIGURE 6.1 Telemedicine fi eld.

142 Biomedical Informatics 
6.2.1 Telemedicine 
Telemedicine is the delivery of medicine and the diagnosis of medical conditions remotely. It is not a 
separate discipline; it is simply an extension of existing medical services using remote technology due 
to the inaccessibility of these services in rural areas or the need for in-home care or a robust real-time 
monitoring capability, for example, an implantable ventricular assist device (VAD) used as an outpa­
tient device but requiring enhanced monitoring, as opposed to the conventional necessity of patients to 
periodically visit a fixed healthcare site. 
The American Telemedicine Association (ATA) defines telemedicine as follows (http://www.americ­
antelemed.org/): 
communications to improve a patient’s clinical health status. Telemedicine includes a growing

communications to improve a patient’s clinical health status. Telemedicine includes a growing 
variety of applications and services using two-way video, email, Smart phones,  wireless tools and 
other forms of telecommunications technology. 
An excellent resource is the Journal of Telemedicine and Telecare  (http://jtt.sagepub.com/). 
There have been a number of studies comparing the cost-effectiveness of telemedicine versus con­
ventional care. In a paper evaluating 80 studies spanning 20 years (1990 –2010 titled “Systematic review 
of studies of the cost-effectiveness of telemedicine and tableware; Changes in the economic evidence 
over twenty years” ), the results showed conclusive evidence that the cost and access provided by tele­
health provided substantial benefits, especially those individuals who, due to a remote location, would 
have received poorer care  (link: http://jtt.sagepub.com/content/18/1/1.short; Health Economics Unit, 
University of Birmingham, U.K.).

University of Birmingham, U.K.). 
The following are common telemedicine applications:
 1. Telesurgery
 2. Remote psychotherapy 
3. Virtual home visits to manage chronic medical problems have all been demonstrated, although 
deployment remains limited 
4. Remote monitoring of chronic medical conditions using networked medical devices such as blood 
pressure cuffs or blood glucose monitors 
5. Multiple websites describe these and other innovative uses of telemedicine for interested clini­
cians to explore 
6. Remote monitoring of ICU patients by intensivists 
7. Remote dermatologic, pathologic, or radiographic consultations 
8. Monitoring compliance with home drug dispensers 
9. Home fetal monitoring during complicated pregnancies 
Interstate practice of medicine is still limited. 
Liability and malpractice are thorny issues, such as the practice of telemedicine; it presents a new

Liability and malpractice are thorny issues, such as the practice of telemedicine; it presents a new 
form of the patient–caregiver relationship and creates potential hazards, such as technical failures lead­
ing to altered or suboptimal data. An accurate diagnosis depends on reliable data. 
The practices of the healthcare insurers/payers are also lagging behind the technology. Medicare and 
other insurers will reimburse telemedicine interactions that meet a restrictive set of criteria  (Table 6.1). 
Table 6.1 lists conditions and situations that fulfill the Medicare reimbursement criteria for telehealth 
with its associated billing codes. The last two entries added in 2014 refer to monitoring of patients recently 
discharged from a hospital—“Transitional Care Management Services with the following required ele­
ments: Communication (direct contact, telephone, electronic) with the patient and/or caregiver within 2

ments: Communication (direct contact, telephone, electronic) with the patient and/or caregiver within 2 
business days of discharge.” This makes a great deal of sense, with the aid of wireless monitoring devices

Service 
(Telehealth Consultations, Emergency Department, or Initial Inpatient) 
1. Follow-up inpatient telehealth consultations furnished to beneficiaries in 
hospitals or SNFs
 
2. Office or other o
utpatient visits 
3. Subsequent hospital care services, with the limitation of 1 telehealth visit every 
3 days 
4. Subsequent nursing facility care services, with the limitation of 1 telehealth 
visit every 30 days
 
5. Telehealth visit every 30 days 
6. Individual and group kidney disease education services 
7. Individual and group diabetes self-management training services, with a 
minimum of 1 h of in-person instruction to be furnished in the initial year 
training period to ensure effective injection training
 
8. Individual and group health and behavior assessment and intervention 
9. Individual psychotherapy (services furnished after January 1, 2013) 
10. Psychiatric diagnostic interview examination (after January 1, 2013) 
11. End-stage renal disease (ES

RD)-related services included in the monthly 
capitation payment 
12. Individual and group medical nutrition therapy 
13. N
eurological behavioral status examination 
14. Smoking cessation services 
15. Alcohol and/or substance (other than tobacco) abuse structured assessment and 
intervention services (services furnished after January 1, 2013) 
16. Annual alcohol misuse screening, 15 min (after January 1, 2013) 
17.  Brief face-to-face behavioral counseling for alcohol misuse, 15 min (services 
furnished after January 1, 2013) 
18. Annual depression screening, 15 min (after January 1, 2013) 
19.  High-intensity behavioral counseling to prevent sexually transmitted infection, 
face-to-face, individual, includes education, skills training, and guidance on 
how to change sexual behavior; performed semi-annually, 30 min (services 
furnished after January 1, 2013)

20. Annual, face-to-face intensive behavioral therapy for cardiovascular disease, 
individual, 15 min (services furnished after January 1, 2013) 
21. Face-to-face behavioral counseling for obesity, 15 min (January 1, 2013) 
22. Transitional care management services with the following required elements: 
communication (direct contact, telephone, electronic) with the patient and/ 
or caregiver within 2 business days of discharge. Medical decision making of 
at least moderate complexity 
23. Transitional care management services with the following required elements: 
high complexity 
Healthcare Common Procedure 
Coding System (HCPCS)/CPT 
HCPCS codes G0406–G0408 
CPT codes 99201–99215 
CPT codes 99231–99233

CPT codes 99231–99233 
CPT codes 99307–99310 
HCPCS codes G0420 and G0421 
HCPCS codes G0108 and G0109 
CPT codes 96150–96154 
CPT codes 90832–90834; 90836, 90838 
CPT codes 90791 and 90792 
CPT codes 90951, 90952, 90954, 90955, 
90957, 90958, 90960, and 90961 
HCPCS code G0270 and CPT codes 
97802–97804 
CPT code 96116 
HCPCS codes G0436 and G0437 CPT 
codes 99406 and 99407 
HCPCS codes G0396 and G0397 
HCPCS code G0442
 
HCPCS code G0443
 
HCPCS code G0444
 
HCPCS code G0445
 
HCPCS code G0446
 
HCPCS code G0447
 
CPT code 99495 (n
ew 2014)
 
CPT Code 99496 (new 2014)
 
Source: https://www.cms.gov/Outreach-and-Education/Medicare-Learning-NetworkMLN/MLNProducts/downloads/ 
TelehealthSrvcsfctsht.pdf. 
Telehealth 143 
TABLE 6.1 Medicare Telehealth Services and Billing Codes

144 Biomedical Informatics 
that can provide precise physiological readings. Often, current care standards suggest patients return in 
a week, two weeks, etc., which creates an added burden on the patient who may have limited resources; 
it may be physically taxing just after a procedure or the hospital may be a great distance away. 
6.2.1.1 Telesurgery 
Telesurgery is a robotic system that can perform surgeries remotely, also referred to as telepresence, 
with higher accuracy and smaller incisions that reduce postoperative recovery. Most current robotic 
operations are performed by surgeons in the same location. The Federal Drug Administration (FDA) 
approved both the ZEUS telesurgery system and da Vinci Surgical System in 2000. The most recent 
model, the da Vinci Xi System, was FDA approved in April 2014. 
6.2.1.1.1 da Vinci Telesurgery System 
The da Vinci telesurgery system is currently the only FDA-approved system in the United States. There

The da Vinci telesurgery system is currently the only FDA-approved system in the United States. There 
have been approximately 1.5 million surgeries performed since 2000. In minimally invasive operations, 
the da Vinci system is the most commonly used surgical device in hysterectomies and prostatectomies. 
There were 2000 systems in use in 2014. The da Vinci system utilizes a 3D HD camera with a 10 times 
magnification so that extremely small details can be visualized (Figure 6.2). There are feedback mecha­
nisms, called haptic feedback and tactile feedback, that are under development. A third-party company 
VerroTouch is providing haptic feedback for the da Vinci system. The following is a recent case study, in 
2014, describing the technology and process involved in that research. 
6.2.1.1.2 Case Study: Adding Haptic Force Feedback to the da Vinci Telesurgery System

6.2.1.1.2 Case Study: Adding Haptic Force Feedback to the da Vinci Telesurgery System 
Description: Accelerometers that measure tool vibrations are mounted to the patient-side manipulators 
of a da Vinci S robotic surgical system. These sensors lie within the sterile drapes, avoiding the need 
for sterilization. The measured right and left tool vibrations are processed and relayed to speakers on 
the surgeon’s console and to voice coil actuators attached to the console handles. Previously, 11 sur­
geons used a VerroTouch-augmented da Vinci S to perform three in vitro manipulation tasks under four 
feedback conditions: with visual feedback, visual–audio feedback, visual–haptic feedback, and visual– 
audio–haptic feedback. Additionally, two transperitoneal nephrectomies and two midureteral dissec­
tions with ureteroureterostomy were performed by two urologists on a porcine model using a da Vinci 
S augmented with VerroTouch for in vivo validation.

S augmented with VerroTouch for in vivo validation. 
Results: Surgeons who participated in the manipulation task study significantly preferred some form of 
tool vibration feedback over visual feedback alone. Survey ratings and written comments also indicate 
that the additional feedback significantly improved subjects’ concentration. No significant differences 
in root mean square (RMS) force, RMS acceleration, or task completion time were found across feed­
back conditions. In the porcine model, human review of a 30 minute operation excerpt resulted in the 
identification of 1404 manipulation events; subsequent analysis demonstrated that 82% of identified 
events resulted in significant vibrations that were measured by VerroTouch. 
Conclusion/Future Directions : VerroTouch has been successfully implemented both in vitro and in vivo 
and proved reliable in detecting technically relevant instrument manipulation events. VerroTouch is

and proved reliable in detecting technically relevant instrument manipulation events. VerroTouch is 
currently being modified for compatibility with the da Vinci Standard and Si models. While surgeons 
tend to prefer the presence of its feedback, further quantitative studies of the cognitive ergonomic effects 
of VerroTouch are required. We hypothesize that the presence of tool vibration feedback may lead to 
improved control of the surgical instruments, particularly for novices. Studies to test the utility of 
VerroTouch as an assessment tool for surgical skill and a prospective study of the effects of vibrotactile 
feedback on training novice surgeons are planned. 
Case Study Link: http://www.sages.org/meetings/annual-meeting/abstracts-archive/verrotouch-detection­
of-instrument-vibrations-for-haptic-feedback-and-skill-assessment-in-robotic-surgery/

EndoWrist   instruments are
dexterity of the human hand Patientand wrist. cart
Vision
cart 
Assistant 
Nurse 
hand movements that are
EndoWrist  instruments. 
Surgeon at
console 
  
Telehealth 145 
FIGURE 6.2 (See color insert.) da Vinci telesurgery system. (From IntuitiveSurgical.com, parent company.)

146 Biomedical Informatics 
Telesurgery advantages are as follows: 
 1.  Greater surgical precision 
 a.	  Improved access to narrow anatomic spaces 
 2.  Increased range of motion 
 a.	  The instruments provide seven degrees of freedom (three for translation, three for rotation, 
and one for grasping).
 3.  Improved  dexterity
 4.  Enhanced  visualization 
 a.	  The 3D stereoscopic display provides a detailed rendition of anatomic features, even in com­
pact spaces. 
 5.  Less time under anesthesia (depends on the procedure, but closing sutures usually reduces surgi­
cal time) 
 6. Less nerve damage and pain among patients 
The procedures most commonly performed (Figure 6.3) are as follows:
 1.  Urologic  surgery 
 2.  General surgery performed through the abdominal wall
 3. Gynecologic surgery 
 4. Head and neck surgery performed through the mouth restricted to benign (noncancer) and 
malignant tumors (cancer) classified as T1 and T2 (early-stage cancer)

malignant tumors (cancer) classified as T1 and T2 (early-stage cancer) 
 5. Thoracic surgery performed through the rib cage on structures like the lungs 
 6. Heart surgery performed through the rib cage 
In 2013, the FDA reported an increase in adverse effects, including injuries; an FDA warning was 
enacted in July 2013, and in May 2014, the FDA indicated in a letter to the company dated April 25, 2014,  
“that based on the FDA’s evaluation, it appears that the Intuitive Surgical has addressed the violations  
contained in the July 16, 2013 warning letter” (Figure 6.4; http://www.intuitivesurgical.com/company/ 
media/statements/#sthash.evhNWpYE.dpuf). 
6.2.1.2 CCRN-E 
Telehealth requires new skills and training especially in remote critically ill patient monitoring. A 
new certification for registered nurses (RNs), CCRN-E [2], extends the Critical Care Registered Nurse 
(CCRN) certification for RNs who monitor crucially ill patients remotely in a tele-ICU or an e-ICU.

(CCRN) certification for RNs who monitor crucially ill patients remotely in a tele-ICU or an e-ICU. 
They both monitor patients visually and receive data feeds remotely from all the monitors. They also 
have access to the EHRs. Small rural intensive care units (ICUs) may not always have the range of exper­
tise in house. CCRNs fill that gap by providing additional expertise from a remote location. 
2011 
27% 37% 
36% 
Hysterectomy 
Open surgery 
da Vinci surgery 
Other MIS 
U.S. procedure data. 
2011 Prostatectomy 
Open and
laparoscopic surgery
17% 
83% 
FIGURE 6.3 Percentages of hysterectomies and pros performed by telesurgery.

2010–2013 MAUDE Database Analysis by Date of Event 
This analysis presents data available as of October 31, 2013 and will be periodically updated to include new information receive d. Because this new information will affect the
 individual data points, the overall trends in the data should be considered rather than attaching undue significance to any single data point.
 
0.0014
0.0012
 
Overall AE rate trend
Q1 Q4 
2013201220112010 
Q3 Q2Q1 Q4 Q3 Q2Q1 Q4 Q3 Q2 Q1 Q4 Q3 Q2
Rate of death trend 
0.001
0.0008 
-Rate computed by dividing the number of adverse 
0.0006   events by the number of surgical procedures
  completed worldwide through October 31, 2013.
  Q4 2013 procedures are an estimate.
0.0004 -One hundred and twenty seven adverse events from
  attorney claims reported in 2013 without an event
  date are not included. Analysis will be updated when 
0.0002   missing event dates are provided.
-One hundred adverse events from sources other than

  attorneys with an unknown event date have been 
0   included and were assigned the FDA receipt date as the
  event date.
Date 
Overall adverse event rate 
Telehealth 147 
FIGURE 6.4 da Vinci Surgical System adverse eff ect decline.

148 Biomedical Informatics 
The following eligibility criteria necessary to take the CCRN-E exam are listed as follows* ( CCRN-E 
handbook: http://www.aacn.org/wd/certifications/docs/ccrn-eexamhandbook.pdf): 
 1. 
Possession of a current, unencumbered U.S. RN license 
 2.  Meets one of the following clinical practice requirement options:
 a.	  Option 1:  Practice as an RN or APRN for 1750 h in the care of acutely and/or critically ill adult  
patients in a tele-ICU or in a combination of tele-ICU and direct bedside care during the pre­
vious 2 years, with 875 of those hours accrued in the most recent year preceding application.
 b.	  Option 2: Practice as an RN or APRN for at least 5 years with a minimum of 2000 h in the 
care of acutely and/or critically ill adult patients in a tele-ICU or in a combination of tele-ICU 
and direct bedside care, with 144 of those hours accrued in the most recent year preceding 
application.

application. 
 3.  Eligible clinical practice hours are those completed in a U.S.-based facility or in a facility deter­
mined to be comparable to the U.S. standard of acute/critical care tele-ICU nursing practice. 
  (http://www.aacn.org/wd/certifications/content/ccrnefaqs.pcms?menu=certification#What_are_ 
the_CCRN-E_initial_exam_eligibility_requirements_ )  
6.2.1.3 Telemental  Health 
Telemental health is similar to the other tele definitions; it is defined as providing behavioral/mental 
health services, substance abuse, crisis intervention, and education, remotely. Originally used in remote 
crisis situations, in 2014, Medicare [3,4,5] provided guidelines on reimbursement. They still require that 
the coverage area be rural or areas outside a metropolitan area without sufficient available services.

the coverage area be rural or areas outside a metropolitan area without sufficient available services. 
States individually decide eligibility for Medicaid reimbursement. Currently, 42 states allow some form 
of telehealth services (see Table 6.1, codes 8–10, 15–20). 
Medicare also sets additional restrictions: 
• 	 Category 1: Services that are similar to professional consultations, office visits, and office psychiatry  
services that are currently on the list of telehealth services. The request is evaluated based on the  
similarities between the services already eligible for reimbursement and that of the requested service. 
• 	 Category 2: Services that are not similar to the current list of telehealth services. The assessment will  
be based on whether the service is accurately described by the corresponding code when delivered 
via telehealth and whether the use of a telecommunications system to deliver the services produces

via telehealth and whether the use of a telecommunications system to deliver the services produces  
a demonstrated clinical benefit to the patient. Supporting documentation should be included. 
The ATA has taken the leadership in defining guidelines for telehealth services. The following section is 
taken from those guidelines. 
The telehealth services fall under these general categories:
 1.  Services
 a.	  Prehospitalization assessment 
 b.	  Posthospital follow-up care 
 c.	  Scheduled and urgent outpatient visits
 d.	  Medication  management 
 e.	  Psychotherapy and consultation
 2.  Clinical  interviews 
 a .	  T e l e m e n t a l  h e a l t h  i n t e r v i e w s  m a y  b e  c o n d u c t e d  b e t w e e n  p h y s i c i a n s  i n  c o n s u l t a t i o n  o r  
between a physician and another healthcare provider (e.g., a case manager, clinical nurse 
practitioner, or physician assistant [PA]).

practitioner, or physician assistant [PA]). 
 b. 	 Telemental health interviews may be conducted between mental health professionals and a 
patient. 
*  Source: AACN website.

c.	  Telemental health interview may be an adjunct to periodic face-to-face contact or may be the 
only contact.
 3.  Emergency  evaluation 
 a.	  Emergency evaluations for psychiatric hospitalization can be conducted via telemedicine and 
usually will require additional personnel to provide physical control of the environment and 
possibly the patient, for patient safety. 
 b. 	 Situations such as a patient who is suicidal, homicidal, or suffering from dementia or acute 
psychosis may require additional personnel in the room in addition to family members. 
 c. 	 In general, adequate support staff or responsible family members shall be present at the 
remote site in order to safely care for the patient. 
 d. 	 Special attention shall be paid to the enhanced need for privacy and confidentiality and every 
attempt made to preserve the patient’s right to privacy.
 4. Case  management 
 a.	  In large distributed systems where multiprovider case management is needed, videocon­

4. Case  management 
ferencing allows collaboration between all the involved clinical participants regardless of 
distance. 
 b.	  Clinical treatment plans can be developed with input from experts who would not otherwise  
be available.
 5.  Clinical  supervision 
 a. 	 Supervision of trainees (residents or interns) at a distant site can facilitate both training and 
patient care. 
 b. 	 Supervision may be done either in real time with the supervisor present via videoconferenc­
ing or, when appropriate, by the use of store and forward technology. 
  (http://www.americantelemed.org/docs/default-source/standards/practice-guidelines-for­  
videoconferencing-based-telemental-health.pdf?sfvrsn=6 ) 
6.2.2 mHealth 
The term “mHealth” stands for mobile health. It is remote medical care supported by mobile devices.

The term “mHealth” stands for mobile health. It is remote medical care supported by mobile devices.  
It usually refers to using mobile devices such as smartphones, tablets, and other remote technologies 
for medical services and education. It also refers to connecting wireless medical devices, like pulse 
oximeters, blood pressure and glucose monitors, and health fitness and a range of cardiac monitoring 
devices, to these smartphones or tablets and extracting useful information and providing that data  
to medical personnel. This market is expanding so rapidly that there is now an international health  
summit for this field such as the “mHealth Summit” (http://www.mhealthsummit.org/). There are 
also numerous organizations appearing to focus in this area; the influential mHealth Alliance (http:// 
mhealthalliance.org) “advocates for standardization and interoperability of mHealth platform.” It is

mhealthalliance.org) “advocates for standardization and interoperability of mHealth platform.” It is  
hosted by the United Nations Foundation and funded by the Rockefeller Foundation. Its stated goal is  
to “harness the power of wireless technologies to improve health outcomes in low and middle income 
countries.” (I recommend Robin Cook’s “CELL” sci-fi novel on cell phones role in mHealth). 
6.2.2.1 Health and Human Services 
Health and Human Services (HHS) has announced several initiatives to set standards for mHealth.  
Several task forces have been initiated for tele-education, telehealth security, and standards for this 
r apidly expanding field (Table 6.2) (http://www.hhs.gov/open/initiatives/mhealth/). 
6.2.2.2   National Institutes of Health and National Science 
Foundation mHealth Initiatives 
The NIH mHealth training initiatives provide investigators with an introduction to mHealth meth­

odologies that may be used to study behavioral and social dimensions of public health. They work  
Telehealth	 149

150 Biomedical Informatics 
TABLE 6.2 HHS mHealth Initiatives and Recommendations 
1 Facilitating health text messaging development : The task force recommends that HHS develops and hosts evidenced-
informed health text message libraries to leverage HHS’ rich and scientifically based information. This information 
should be open access and free to the public. Areas prime for development include smoking cessation, emergency 
response/preparedness, early childhood health, maternal/child health, heart disease, diabetes, mental health, oral 
health, and obesity. 
2 Research and evaluation: The task force recommends that HHS develops further evidence on the effectiveness of health 
text messaging programs. HHS is currently conducting a formal evaluation of the text4baby program, a public– 
private partnership that is the first free-to-end-user health text messaging program available nationwide. Future

private partnership that is the first free-to-end-user health text messaging program available nationwide. Future 
health text messaging programs by HHS, or in which HHS is a partner, should also include a scientific evaluation 
component. To keep pace with the dynamic nature of mobile technology, robust and periodic (e.g., quarterly or 
annually) assessments of funding opportunities and the development of new/emerging technologies are also 
recommended. 
3 Partnerships among federal government agencies and with nonfederal organizations:  The task force recommends that 
HHS explores and develops partnerships to create, implement, and disseminate health text messaging and mobile health 
(mHealth) programs. It is further recommended that in FY2012 specific HHS staff persons (e.g., HHS mHealth lead) 
serve as main points of contacts to represent HHS in discussions of collaborations or partnerships with other

serve as main points of contacts to represent HHS in discussions of collaborations or partnerships with other 
stakeholders in the mHealth ecosystem. Because health text messaging and mHealth utilize consumer-facing 
technologies and are relevant to many stakeholders, partnerships among HHS, other governmental agencies, and 
nonfederal organizations often are needed to develop successful projects. Identifying specific HHS representatives 
would facilitate the development and coordination of partnerships and should work closely with the HHS chief 
technology officer. 
6 Delineating privacy/security issues:  The task force recommends that HHS conducts further research into the privacy and 
security risks associated with text messaging of health information and establish guidelines for managing such privacy/ 
security issues. Furthermore, mHealth issues should be discussed within the HHS Inter-Division Health IT Policy and

security issues. Furthermore, mHealth issues should be discussed within the HHS Inter-Division Health IT Policy and 
Security Task Force. The exchange of health information via text messages raises privacy and security issues specific 
to this medium. Text messaging programs may be subject to numerous privacy and security laws, including the 
Health Insurance Portability and Accountability Act of 1996 (HIPAA) privacy and security rules. 
7 Regulatory issues:  The task force recommends that relevant HHS agencies (FDA, NIH, AHRQ, ONC, etc.) conduct 
research on future trends of text messaging technologies and establish regulatory guidelines for these interactive systems 
that can be used in treating, curing, mitigating, or preventing diseases or conditions. Future developments in health text 
messaging and mHealth technology will likely create and extend beyond its current capabilities to create interactive

messaging and mHealth technology will likely create and extend beyond its current capabilities to create interactive 
systems that will enable active treatment and prevention of diseases or conditions in humans. Applying medical 
device and clinical research principles to evaluate interactive text messaging programs must take into account the 
safety and effectiveness of SMS technology while also facilitating innovation. 
Source: http://www.hhs.gov/open/initiatives/mhealth/recommendations.html. 
with expert mentors to create their own interdisciplinary mHealth projects. The use of mobile tech­
nology affords methodological advantages over traditional approaches, including reduced memory 
bias, the ability to capture time-intensive longitudinal data, date- and time-stamped data, and the 
potential for personalizing information in real time. (http://obssr.od.nih.gov/training_and_educa­
tion/mhealth/index.aspx)

tion/mhealth/index.aspx) 
“mHealth”—has the potential to be a transformative force. mHealth has the potential to change 
when, where, and how healthcare is provided; to ensure that important social, behavioral, and 
environmental data are used to understand the determinants of health; and to improve health 
outcomes. 
http://obssr.od.nih.gov/scientific_areas/methodology/mhealth / 
Some of the current National Science Foundation (NSF) and National Institutes of Health (NIH) 
grants for mHealth that were funded in 2013–2014 provide an indication of the future directions 
of the mHealth field (Table 6.3) . They are as follows: improving the tracking and communication

Telehealth 151 
TABLE 6.3 NSF and NIH Projects for mHealth 
Title Description 
(R01)PA-14–180 
http://grants.nih.gov/ 
grants/guide/pa-files/ 
PA-14–180.html 
NSF: mHealth Tools for Individuals 
with Chronic Conditions to 
Promote Effective Patient– 
Provider Communication, 
The purpose of this initiative is to stimulate research 
utilizing mobile health (mHealth) tools aimed at the 
improvement of effective patient–provider 
communication, adherence to treatment, and 
Posted: April 18, 2014 Adherence to Treatment and 
Self-Management (R01) 
self-management of chronic diseases in underserved 
populations. 
(R21)(PAR-14–028) 
http://www.fic.nih. 
gov/Programs/Pages/ 
mhealth.aspx 
Application due date: 
February 19, 2015 
NIH: Mobile Health: Technology 
and Outcomes in Low- and 
Middle-Income Countries 
(mHealth) 
Mobile Health: Technology and Outcomes in Low- and 
Middle-Income Countries will support research on the 
development or adaptation of mHealth technology

development or adaptation of mHealth technology 
specifically suited for low- and middle-income 
countries (LMICs) and the health-related outcomes 
associated with the implementation of the technology. 
Funded 2013 Large: Collaborative research: 
Computational Jewelry for Mobile 
Health 
The vision is that computational jewelry, in a form like a 
bracelet or pendant, will provide the properties essential 
for successful body-area mHealth networks. These 
devices coordinate the activity of the body-area network 
and provide a discreet means for communicating with 
their wearer. Such devices complement the capabilities 
of a smartphone, bridging the gap between the type of 
pervasive computing possible with a mobile phone and 
that enabled by wearable computing. 
Funded 2012 NSF-funded project looks to 
mHealth to improve preoperative 
services 
The National Science Foundation has awarded $797,066

services 
The National Science Foundation has awarded $797,066 
to three university professors to research how mobile 
technology can improve coordination in preoperative 
services. 
between doctors and patients for chronic disease follow-up care, remote area access to low-income 
groups, and preoperative education. 
Level II: Distributed Healthcare 
6.3 Introduction
 
This section describes facilities, services, and software that lie outside of traditional inpatient systems 
such as hospitals, emergency rooms (ERs) in hospitals, or a physician’s office. With the advent of 
telehealth, medical services can draw upon external resources that can supplement the infrastructure 
that was previously only available in either larger organizations, such as hospitals that required all 
support services centralized to ensure they were prepared for every eventuality. The same is true for

support services centralized to ensure they were prepared for every eventuality. The same is true for 
urgent care facilities that can replace traditional ERs in most, not all, situations. The line is blurred 
here since many urgent care facilities are extremely well staffed with a comprehensive suite of equip­
ment, especially those that are certified by the Urgent Care Association of America (UCAOA). These 
triage trade-offs are often due to either rural locations where a large facility is a distance away or 
the severity of the injury may not require the complex support facilities of a hospital ER sometimes 
referred to as emergency department [ED]). A number of hospitals have closed in the last few decades, 
due to cost–benefit trade-offs of maintaining full care facilities, but often the ER remains open to pro­
vide local emergency outpatient services, especially in distressed communities where transportation 
or other options are severely limited.

or other options are severely limited. 
With the limited number of physicians and often simple, nonacute treatments that are required such 
as cold, flu remedies, immunization shots, etc., another external facility referred to as miniclinics—the

152 Biomedical Informatics 
largest system is CVS Minute Clinic with currently 800 locations and growing—can provide care cost-
effectively and more conveniently utilizing RNs and PAs, again also supported remotely by telehealth 
technology. 
Last, software on smart devices provides another instant response system available to communicate 
with medical professionals. With the addition of mHealth devices such as wireless pulse oximetry and 
blood pressure and glucose monitors, detailed data can augment the remote diagnosis and treatment. 
6.4 Medical Apps for Remote Healthcare 
This new generation of on-demand medical virtual doctor visits will change the current medical para­
digm, They provide the following benefits: its ability to instantly contact a pool of licensed medical 
practitioners at a low cost starting at $39, who can triage situations immediately, no arranging for 
appointments, traveling to a location, and no waiting. Just select an app on your phone, fill in a few

appointments, traveling to a location, and no waiting. Just select an app on your phone, fill in a few 
fields, and you’re talking to a professional in minutes. This low-cost option may still be out of reach for 
many individuals; $39 may be the cost of food for the family for 1 or more days. We have to have a sub­
sidized plan similar to food stamps to ensure access to all; healthcare is a basic human need. But since 
the cost of a single ER visit averages $500–$1,000 or waiting till a situation becomes acute escalates the 
cost, the overall cost of providing subsidies for early diagnostic services pays for itself and may actually 
lower overall healthcare costs. In the United States, we pay twice/per capita the cost of every country 
with single-payer systems and our outcomes, life expectancy, infant mortality rates, etc., are well below 
the average of other countries. 
In the nonacute category, a cold, mild pain, fever, or any early-stage medical issue, the question that

In the nonacute category, a cold, mild pain, fever, or any early-stage medical issue, the question that 
arises, is whether intervention by a medical practitioner is necessary? Can over-the-counter medications 
and/or bed rest suffice? Do I have to travel to some location, make an appointment, keep my child out of 
school, take time out of work when in a low-income or rural environment simply getting to that location 
may be a significant burden? Often in all of these situations, no action is taken; the rationale usually is 
that it will pass or because of financial or transportation limitations. Miniclinics, in places like CVS 
stores, are one solution if they are close and operate on 24 hour schedules. Medical apps are another 
solution for nonacute care where individuals can get diagnoses and prescriptions remotely from a large 
pool of medical practitioners that have been certified by the site for a relatively small fee (Table 6.4).

pool of medical practitioners that have been certified by the site for a relatively small fee (Table 6.4). 
6.5 Urgent Care Centers 
In the acute care category: U rgent care is a broad term that is defined as follows: “U rgent Care Medicine 
(UCM) is the provision of immediate medical service offering outpatient care for the treatment of acute and 
chronic illness and injury. It requires a broad and comprehensive fund of knowledge to provide such care” 
(https://aaucm.org/about/urgentcare/default.aspx). There are approximately 9,000 centers in the United 
States, with 3 million plus visits/week and 160 million visits/year, and 85% are open 7 days/week (Table 6.5). 
Urgent care associations 
UCAOA: http://www.ucaoa.org/ .
 
National Association for Ambulatory Urgent Care (NAFAC): http://www.urgentcare.org /.
 
American Academy of Urgent Care Medicine (AAUCM): Urgent care medicine (UCM) is the provi­

sion of immediate medical service offering outpatient care for the treatment of acute and chronic 
illness and injury. It requires a broad and comprehensive fund of knowledge to provide such care 
(https://aaucm.org/about/urgentcare/default.aspx). 
Certifications: The UCAOA provides certifications for these facilities. Since these urgent care centers 
are more acute facilities, providing outpatient services, and 94% of the time have physicians on-
site, a certified site provides a degree of assurance that basic care standards are met.

Ringadoc 1. 1,000 physicians in 40 states $69/month or $868/year 
Examples 
diarrhea 
1. 24 hours/day. £35 per session 
3. On-demand doctors are available to

pains. 
records. 
Telehealth 153 
TABLE 6.4 (See color insert.) Examples of On-Demand Medical Consultation Apps 
Medical Apps—On-Demand Doctors’ Visits (Live Video Consultations and Text Chat Health Inquiries)

1. A t
ext chat 
$1.50/min 
ConsultADoctor 
http://www.consultadr.com/ 
employees 

154 Biomedical Informatics 

• 94.1% of centers have at least one full-time employed physician on staff. 
• At the end of 2012, there were 108,000 employees in the United States (revenue 16 billion dollars). 
Schedule 70% open at 8 am or earlier 95% close after 8 pm 
Wait times 69% wait <20 min 28% between 21 and 40 min 3% >40 min 
Location 75% suburban 15% urban 10% rural 
Ownership 35% physician or group physicians 30.5% corporation 25% hospital 
Specialties 47.7% family medicine 30% emergency 9.9% more than one specialty 
Visits 3 million/week 160 million/year 9,000 centers 
Source:  2012. http://www.ucaoa.org/docs/UrgentCareMediaKit_2013.pdf; http://www.ibisworld.com/industry/ 
urgent-care-centers.html. 
The certifications fall into two categories*:
 
Facilities receive a certification of Category 1 or Category 2 depending on their staffing model:
 
Category 1 = licensed physicians (MD/DO) on-site during all posted hours of operation

Category 1 = licensed physicians (MD/DO) on-site during all posted hours of operation 
Category 2 = licensed providers (MD/DO or NP/PA) on-site during all posted hours of operation 
(mixed models) 
6.5.1 Urgent Care Certification Criteria 
 1.  Facility must accept and advertise that walk-in patients of all ages are accepted for a broad spec­
trum of illness, injury, and disease during all hours the facility is open to see patients. 
 a. 	 Pediatric specialty centers are exempt from above age requirement if pediatric-only special­
ization is included in the name of the facility. 
 2.  The following must be available during all posted hours of operation for the facility:
 a.	  X-ray on-site 
 b.	  Phlebotomy services on-site 
 c. 	 Licensed provider on-site with the appropriate state 
 d.	  Licenses and resources to
  i.	  Obtain and read an EKG and x-ray on-site
  ii. 	 Administer PO, IM, and IV medications/fluids on-site

d.	  Licenses and resources to
  ii. 	 Administer PO, IM, and IV medications/fluids on-site 
  iii. 	 Perform minor procedures (e.g., sutures, cyst removal, incision and drainage, splinting) on-site 
  iv. 	 The following equipment and staff trained in its use: portable defibrillator, portable oxy­
gen, and Ambu bag/oral airway, portable drug cart stocked appropriately for all ages of 
patient population (as determined by the facility) 
  v. 	 Working phone to dial 911 and at least two exam rooms, separate waiting area, and 
restricted-access patient restrooms 
 3.  Minimum hours of operation (must meet all three criteria) 
 a.	  7 days/week (not including national holidays; see www.ucaoa.org/certification) 
 b. 	 4+ hours each day
 c.	  3000 hours/year 
 d.	  Note: Alternatively, special circumstances will be considered for a facility if all of the follow­
ing are met: 
 i.	  Facility is part of a multicenter system.

 i.	  Facility is part of a multicenter system. 
 ii. 	 Facility is open 5+ days/week (not including national holidays). 
 iii. 	 Another facility that is part of the same system meets standard minimum hours of opera­
tion criteria  and is ≤5 miles away. 
*   Source: http://www.ucaoa.org/docs/CUC_brochure.pdf. 
Telehealth	 155 
TABLE 6.5 Urgent Care Facilities Statistics 
Urgent Centers

4. Facility must have a physician designated as medical director for the facility (with an active, 
unrestricted license for the state where the facility is located) who is responsible for overall clini­
cal quality. 
 5. Facility must provide clinical care and perform business activities in an ethical manner. 
6.6 Miniclinics 
Miniclinics are walk-in clinics usually staffed by Physician Assistants (PAs) or Registered Nurses (RNs) 
to treat nonacute medical conditions, i.e., not serious enough to require ER care. In March of 2014, 
there were 5,275 clinics with a revenue of $16 billion with an annual growth rate of 8.2%.* The ACA has 
spurred growth in urgent care centers due to the expansion of individuals covered under private and 
government-supported healthcare plans. The ACA, specifically under title IV subsection D and title V 
subtitle A sec 5001, promotes the expansions of preventive and chronic care services. The HHS, in 2012,

subtitle A sec 5001, promotes the expansions of preventive and chronic care services. The HHS, in 2012, 
also funded $730 million to support and expand access via outpatient clinics. 
 1.  Hospitals and health insurers are investing in these clinics to reduce costs. 
 2. With the advent of the ACA and more insured individuals, up to 13 million by March 31, 2014 
(8 million signees and 5 million additional Medicare recipients), the current providers may be 
unable to provide timely appointments without the aid of miniclinics. 
 a. 	 Prevention, one of the ACA directives, involves providing funding for additional clinics. In 
May 2012, the HHS announced $730 million in grants to support community health cen­
ters. Its estimated 900,000 new patients will be serviced by these new and expanded centers 
(http://www.hhs.gov/healthcare/facts/blog/2012/05/healthcenters050112.html):
 i.	  The healthcare law has already supported 190 health centers’ construction and renovation

i.	  The healthcare law has already supported 190 health centers’ construction and renovation 
projects and the creation of 67 new health center sites across the country.
 ii.	  Since the beginning of 2009, employment at health centers nationwide has increased by 15%.
 iii.	  Due to primarily the ACA and the Recovery Act, community health centers are serving 
nearly three million more patients . 
 b.	  The ACA plans are to continue to supply future funding for miniclinics specifically address­
ing the problems of access in inner cities and rural areas: 
 i.	  Over the next few years, the healthcare law will support more than 485 new health  
center construction and renovation projects and the creation of 245 new community  
health center sites, estimating an additional 6,000 jobs and access for 1.3 million new  
patients. 
 ii. 	 The ACA Title IV Subsection D relating to “chronically ill patients” mandates the

patients. 
 ii. 	 The ACA Title IV Subsection D relating to “chronically ill patients” mandates the 
expanded availability of preventive and follow-up care for critically ill patients. A major 
expense and cause of death are discharged critically ill patients who don’t follow their 
medication regimen or follow-up care. This can be resolved with either miniclinics or 
telehealth (http://www.hhs.gov/healthcare/rights/law/title/iv-amendments.pdf). 
 iii. 	 The ACA title V subtitle A sec 5001 “Healthcare Workforce”: 
The purpose of the ACA is to improve access to and the delivery of healthcare services for all individuals,  
particularly low-income, uninsured, minority, and rural populations by
†:
 1.	  Gathering and assessing comprehensive data in order for the healthcare workforce to meet the healthcare  
needs of individuals, including research on the supply, demand, distribution, diversity, and skills. 
*  Source: http://www.ibisworld.com/industry/urgent-care-centers.html.

*  Source: http://www.ibisworld.com/industry/urgent-care-centers.html. 
† Text from HHS.gov. 
156 Biomedical Informatics

Telehealth	 157 
2.  Increasing the supply of a qualified healthcare workforce to improve access to and the delivery of 
healthcare services for all individuals.
 3.	  Enhancing healthcare workforce education and training to improve access to and the delivery of 
 4. Providing support to the existing healthcare workforce to improve access to and the delivery of 
healthcare services for all individuals 
  http://www.hhs.gov/healthcare/rights/law/title/v-healthcare-workforce.pdf 
6.6.1 U.S.  Miniclinics 
Most miniclinics will have increased telehealth options for remote consultations. With the exponential 
growth, currently expanding at 8% a year, it is estimated that most people will use these clinics more 
often than conventional doctor visits: 
• 	 CVS Minute Clinic, with 800 clinics by the end of 2013, is expanding its miniclinics, has planned 
for expansion of 150 clinics/year, and is developing apps for telehealth.

for expansion of 150 clinics/year, and is developing apps for telehealth. 
• 	 In Massachusetts, Blue Cross and Blue Shield have partnered with miniclinics (http://www. 
bluecrossma.com/bluelinks-for-employers/whats-new/special-announcements/cvs-minute­
clinic.html). 
• 	 In Vermont, with the closing of North Adams Regional Medical Center, in 2014, Blue Cross 
has increased access to miniclinics (https://www.bluecrossma.com/bluelinks-for-employers/ 
whats-new/special-announcements/index.html). 
• 	 Walgreen miniclinics (largest drugstore chain in the United States) announced in 2013 “that 
its 370+  Take Care Clinics  will be the first retail store clinics to both diagnose and manage 
chronic conditions like asthma, diabetes, high blood pressure, and high cholesterol. The Nurse 
Practitioners (NPs) and Physician Assistants (PAs) who staff these clinics will provide an entry 
point into treatment for some of these conditions” (http://thehealthcareblog.com/blog/2013/04/12/

point into treatment for some of these conditions” (http://thehealthcareblog.com/blog/2013/04/12/ 
chronic-care-at-walgreens-why-not/). 
• 	 Walmart miniclinics have not been as aggressive as other vendors with drugstores. 
• 	 Rite Aid NowClinic miniclinics, as of the end of 2013, have clinics in Michigan, Maryland, and 
Pennsylvania (https://www.mynowclinic.com/riteaid/locations/). 
• 	 Target: Target Clinics have miniclinics, as of the end of 2013, in Florida, Illinois, Maryland, 
Minnesota, North Carolina, and Virginia (http://www.target.com/store-locator/find-clinic). 
•	  M e d E x p r e s s  U r g e n t  C a r e  i s  t h e  d o m i n a n t  c l i n i c  o p e r a t o r  i n  W e s t e r n  P e n n s y l v a n i a  ( h t t p : / / 
medcitynews.com/2013/08/affordable-care-act-could-lead-to-increase-in-walk-in- clinics/  
#ixzz31WUC3neD). 
• At the end of 2012, there were 115 clinics in 9 states (double from the previous year).

• At the end of 2012, there were 115 clinics in 9 states (double from the previous year). 
• 	 Concentra has 342 miniclinics in 42 states as of 2013, owned by Humana Healthcare. 
6.6.2  Miniclinic Certification Criteria 
The Joint Commission, formerly JCAHO, is the national evaluation and certifying agency for nearly 
15,000 healthcare organizations and programs in the United States, including hospitals, nursing homes, 
laboratories, rehabilitation centers, and behavioral healthcare organizations. The Joint Commission’s 
standards focus on patient safety and quality of care and are updated regularly to reflect the rapid 
advances in healthcare and medicine (http://www.jointcommission.org/).

158 Biomedical Informatics 
The certification standards include (subset of the 180 certification standards) the following: 
 1.  Review and verification of education of the clinics’ personnel 
 2. Licensure and certifications 
 a.	  A copy of their DEA license 
 b.	  A copy of their state license 
 c.	  A copy of their CPR certification 
 d.	  A copy of their national certification
 3.  On-site  surveys 
 a. “Tracing” the patient’s experience—looking at services provided by various care providers 
 b.	  Departments within the organization, as well as “hand-offs” between them 
 c. 	 On-site observations and interviews with surveyors 
 d. 	 Review of documents provided by the organization 
 e.	  Assessment of the physical facility
 4. Medication  management 
 a.	  Addresses the stages of medication use, including selection, storage, and safe management of 
medications; ordering, preparing and dispensing, administration, and monitoring of effect;  
and evaluation of the processes

 5.  Performance  improvement
 6.  Record of care: handling and security of patient records (EHRs) 
The Minute Clinics (CVS) are JCAHO certified, which signifies that they comply with more than 180 
na ti o nal stan dar ds in th e im p l em en ta ti o n o f estab lish ed clini cal p racti ce gui delin es, as w ell as m o r e  
than 500 performance measurements. 
Th e  H e al th  R e s o ur c e s  an d  S e rvi c e s  A dmini s tr a ti o n  ( HRS A )  c e rtifi e s  rur al  c lini cs .  Th e  c ri t e ri a  b y  
which they are certified are listed in the document “Starting a Rural Clinic,” which include a rural 
 healthcare (RHC) certification and policy manuals that conform to individual state laws (http://www. 
hrsa.gov/ruralhealth/pdf/rhcmanual1.pdf). 
6.7 Mobile Tools to Support Physicians

EHRs provide access to a patient’s medical records but they are still in their early phases of implementa­
tion. We are in the early flip-phone phase, reference to the rudimentary early mobile phones, of EHRs  
where ease of use and functionality are still lacking. A number of third-party companies have stepped 
in to fill the gap. It is likely that start-up companies will be purchased by larger EHRs such as Epic and  
Cerner, which is what happened when YouTube was purchased by Google in 2006 for $1.65 billion only a 
few years after its creation, to incorporate cutting edge user interfaces. This field is ripe for future entre­
preneurs. That is why I have included appendices on app development for EHRs, since all Phase I medi­
cal records will need to be upgraded and we need to train or at least inform informatics practitioners of

cal records will need to be upgraded and we need to train or at least inform informatics practitioners of 
the direction we’re moving toward. Also the chapter written on EHR implementation, by a practicing 
clinical nurse specialist, highlights the need to enhance the current nurse/physician interface for usabil­
ity and efficiency. 
There are currently about 5,000 apps on ITunes and Android devices and a few for Blackberry (Mobile 
Health News: http://mobihealthnews.com/). 
There are apps to allow physicians to remotely visualize, enhance, or compare CT/MRIs side by side 
to compare changes over time. Some examples are Mobile MIM or Merge iConnect. Other app softwares  
allow physicians to illustrate surgeries with patients or hold remote video conferences to communicate 
with patients. There are apps to allow surgeons to communicate with families in waiting rooms so they  
can get instant updates after surgery (MDconnectME). Many of these apps tie into EHRs and soon to

can get instant updates after surgery (MDconnectME). Many of these apps tie into EHRs and soon to 
HIEs to share data seamlessly between different vendors (http://www.mdconnectme.com/) (Table 6.6).

Telehealth 159 
TABLE 6.6 (See color insert.)  Productivity Apps for Physicians 
Mobile MIM 
imaging/ 
drawMD 
scans 
of the scan 
 
Allows physicians to make diagnosis

160 Biomedical Informatics 
TABLE 6.6 (Continued) Productivity Apps for Physicians 
Source: Mobile Medical Productivity Tools. http://www.mednet-tech.com/newsletter/mobile-marketing/top- mobile- apps­
Examples of medical productivity tools include Apple’s Research Kit (2015), a tool to allow researchers 
o turn the iPhone into a diagnostics tool, drawing data from mobile devices. The system can potentially 
ollect large amounts of data from millions of consenting iPhone users, thus showing correlations and  
rends. https://www.apple.com/researchkit/. 
.8 Summary 
elehealth is a broad term that refers to providing services, diagnoses, education, and data remotely.

.8 Summary 
elehealth is a broad term that refers to providing services, diagnoses, education, and data remotely. 
verything today is connected and healthcare is quickly following. The quality of medical services soon  
ill  n o t  b e  d e p e n d e n t  o n  l o c a t i o n  an d ,  h o p e full y ,  p e r s o n al  fi n an c e s .  O n c e  wi r e l e s s  m e d i c al  d e vi c e s  
ecome common, or at least accessible in public venues, we can quickly assess an individual’s medical 
tate, not waiting for the traditional doctor’s or ER visit, thus enhancing preventive medicine. Integrated 
ith EHRs, tied into the Cloud, healthcare will become a basic service and right accessible anywhere 
nd costs may decline significantly. 
uestions 
evel I 
1. Explain the difference between telehealth and telemedicine; provide details. 
a.  Describe telemedicine applications. 
2. What are some of the issues in practicing telemedicine across state lines?

2. What are some of the issues in practicing telemedicine across state lines? 
3. What is Medicare’s position on the reimbursement for telehealth services? 
a.  Provide details on specific reimbursed activities. 
4.  What is telesurgery? 
a. What specific advantages does it provide? 
b. What surgical procedures is it most commonly used for? 
c. Summarize the da Vinci telesurgery case study in Section 6.2.1. 
t
c
t
6
T
E
w
b
s
w
a
Q
L

5.  What is the CCRN-E? 
 a.	  In what situations are CCRNs used in telemedicine? 
 6.  What is mHealth? 
 a.	  Explain some examples where mHealth has provided health services not available by any 
other means. 
 b. 	 Explain the NIH mHealth initiatives. 
Level II 
 7.  What is distributed healthcare? 
 a. 	 Explain the role of stand-alone emergency departments (EDs), urgent care, and miniclinic 
centers. 
 b.	  What are the unique regulatory requirements for urgent care and miniclinics? 
 8. What are medical apps? 
 a. 	 Research a medical app and provide details of the service and statistics and speculate on the 
potential benefits over conventional paradigms. 
Level III 
 9.  Describe some of the remote productivity tools available for physicians to visualize and diagnose  
CT/MRIs. 
 a.	  Research a remote productivity tool, not mentioned in the textbook, to aid physicians in prac­
ticing telemedicine. 
Glossary

CT/MRIs. 
Glossary 
CCRN-E extends the Critical Care Registered Nurse (CCRN) certification for registered nurses (RNs) 
who monitor crucially ill patients remotely in a teleICU or an eICU. 
The term  “mHealth”  stands for mobile health. It is remote medical care supported by mobile  
devices. 
Miniclinics  are walk-in clinics usually staffed by physician assistants or registered nurses to treat non-
acute medical conditions. 
Telehealth  is an all-inclusive term encompassing remote healthcare and all its support. 
Telemedicine  is the use of medical information exchanged from one site to another via electronic com­
munications to improve a patient’s clinical health status and delivery of remote clinical ser­
vices using technology. 
Telemental health  is similar to the other tele definitions; it is defined as providing behavioral/mental

Telemental health  is similar to the other tele definitions; it is defined as providing behavioral/mental 
health services, substance abuse, crisis intervention, and education, remotely delivered utiliz­
ing the Internet and wireless communications. 
with higher accuracy and smaller incisions that reduce postoperative recovery. 
Urgent care medicine is a broad term that is defined as follows: “Urgent Care Medicine (UCM) is the 
provision of immediate medical service offering outpatient care for the treatment of acute and 
chronic illness and injury.” 
 1.  American   Telemedicine   Association.   http://www.americantelemed.org/docs/default-source/ 
standards/a- lexicon-of-assessment-and-outcome-measurements-for-telemental-health.pdf?sfvrsn=2 
 2.  CCRN-E handbook. http://www.aacn.org/wd/certifications/docs/ccrn-eexamhandbook.pdf.

2.  CCRN-E handbook. http://www.aacn.org/wd/certifications/docs/ccrn-eexamhandbook.pdf. 
 
Telehealth	 161

162 Biomedical Informatics
 3. HHS.	  http://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLN  
Matters Articles/downloads/MM8553.pdf .  
 4.  HHS 2. https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLN  
Products/downloads/TelehealthSrvcsfctsht.pdf . 
 5. Medicare 	 Telehealth Services. https://www.cms.gov/Outreach-and-Education/Medicare­
Learning-Network-MLN/MLNProducts/downloads/TelehealthSrvcsfctsht.pdf. 
 6. What is mHealth, www.himss.org/library/mhealth. 
 7.  Public Policy TeleHealth. http://www.ihealthbeat.org/perspectives/2013/public-policy-for-telehealth­
in-2013-its-time-for-government-to-lead-or-get-out-of-the-way . 
 8. PubMed Telemedicine. http://www.ncbi.nlm.nih.gov/pubmed/21119593. 
 9.  Telehealth prospects by IHealthBeat. http://www.ihealthbeat.org/perspectives/2013/public-  policy­
for-telehealth-in-2013-its-time-for-government-to-lead-or-get-out-of-the-way .

for-telehealth-in-2013-its-time-for-government-to-lead-or-get-out-of-the-way . 
 10. What Is an Implantable Cardioverter Defibrillator. http://www.nhlbi.nih.gov/health/health-topics/ 
topics/ic.

Level I: Core Concepts ................................................................................. 164
 
7.1 	 Introduction ...................................................................................... 164
 
7.2 	 Electrical and Chemical Conduction Basics ................................ 164
 
Subatomic Particles • Current and Ohm’s 
Law • Electrochemistry • Fiber Optics
 
7.3 	 Data Acquisition: Medical Sensors ................................................ 176
 
Sensors • Electrical Conduction System of the Heart • Blood
 
Pressure • Pulse Oximetry • Neurons
 
Level II: Wireless Medical Monitoring ...................................................... 185
 
7.4 	 Wireless Medical Devices ................................................................ 185
 
Bluetooth Wireless Communications • Body Sensor
 
Networks • Wireless Medical Device Protected 
Spectrum • Integrated Data Capture Modeling for Wireless Medical 
Devices

Devices
 
Level III: Advanced Data Analysis ............................................................. 188
 
7.5 	 Expert Systems: Utilized to Evaluate Medical Data .................... 188
 
7.6 	 Data Mining and Big Data in HealthCare .................................... 189
 
Body Sensor Network Research and Big Data • Future Directions: 
Mining Large Data Sets: NSF and NIH Research Initiatives
 
Level IV: Anatomy and Physiology Primer ............................................... 196
 
7.7 	 Part I: Neurons and Nervous System, Brain, Spinal Cord, 
Muscles, Heart, Eye .......................................................................... 196
 
7.8 	 Part II: Cells, ATP, Hearing, Kidneys, Pancreas, Liver,
Digestive System ...............................................................................202

7.9 	 Part III: Lungs, Immune System, Stroke, Blood Flow, Prostate ..... 208
 
7.10 	 Part IV: Heart Disease, Cancer ....................................................... 214
 
7.11 Summary ............................................................................................ 218
 
Questions ....................................................................................................... 218
 
Glossary .........................................................................................................220
 
References ...................................................................................................... 221
 
7 
Medical Sensors
 
163

Electrical and chemical 
conduction basics 
Data acquisition:
and measurements 
Wireless medical 
Subatomic particles Current flow Valence electrons 
Action potential Electrical conduction 
Heart Blood pressure Body sensor
networks (BNSs)c 
= Io e–(ad)I 
Beer’s law nici = V 
 
164 Biomedical Informatics 
7.1 I nt r o duc t ion
 
Biological organisms developed sensory capabilities to enhance their survival. Identifying foods sources,

Biological organisms developed sensory capabilities to enhance their survival. Identifying foods sources, 
evading predators, enhanced communications, and finding mates are all augmented with more sophis­
ticated methods of perceiving their environment. In the last two centuries, we have developed our own 
enhanced sensory technologies—x-rays, 3D computer tomography (CT), magnetic resonance imaging 
(MRI), EEGs, EKGs, high-resolution electron microscopes, genomic sequencers, etc.—to augment our 
senses to improve healthcare. These diagnostic technologies along with antibiotics, gene therapy, and 
modern pharmaceuticals have doubled life expectancy in the past century increasing our survival by 
utilizing our intellects. Modern Homo sapiens emerged approximately 200,000 years ago and only in the 
last few centuries, utilizing the scientific method, have we begun to be masters of our own fates.

last few centuries, utilizing the scientific method, have we begun to be masters of our own fates. 
This chapter will focus on the exponential growth of sensor technology and the science underpinning 
this growing discipline. Linked to high-speed communications with chip-sized microprocessors that 
can process terabytes (1,012 bytes) of data and mining these large data sets for gems, correlations linking 
diverse diseases and drug therapies, we can provide greater insights into treatments. Linking sensory 
data, from wearable and embedded sensors, body sensor networks (BSNs) etc., a group of sensors can 
provide a holistic analysis of an individual’s medical status. All this data can then be fed, not only into 
electronic health records, but also stored in the Cloud providing larger analytics on the effectiveness 
of medical interventions that further accelerate medical science and possibly doubling, or greater, life 
spans again in the next century (Figure 7.1).

spans again in the next century (Figure 7.1). 
7.2 Electrical and Chemical Conduction Basics 
Before delving into medical sensors, it’s critical to understand the underlying physics, chemistry, and 
electronics principles underpinning medical sensors. A Biomedical Informatics professional needs to 
understand how and why it works and with this basic knowledge contribute to the advancement of the 
science and provide input to the next generation of sensors. 
The intent of this first section is to ensure you are well grounded in the basic concepts of the relation­
ship between atomic structure, the periodic table and its organization, the role valence electrons play in 
FIGURE 7.1 (See color insert.) Medical sensor primer.

Periodic table and valence 
Explanation of
subatomic particles
building blocks 
electrons and conductors Ohms law V = I × R 
2E = mc
 
and energy
 
165 Medical Sensors 
FIGURE 7.2 (See color insert.) Linkages between topics covered in the first section. 
electrical conduction, Ohm’s law and basic circuit theory, the chemistry of batteries that power many 
medical sensors, and inductive charging used to charge batteries especially in the case of implantable 
medical devices. Figure 7.2 encapsulates the core concepts covered in this first section. 
7.2.1 Subatomic Particles

7.2.1 Subatomic Particles 
Electrons are negatively charged subatomic particles. Subatomic means part of a larger atom. Atoms, at 
the most fundamental level, are compressed of energy. If you release the energy in a group of uranium 
or plutonium isotopes, isotopes are relatively unstable atoms that can be more readily broken apart to 
release their internal energy. Isotopes also refer to the fact that the same element such as uranium has 
forms with different numbers of neutrons. So uranium 235 is fissile, which means it can sustain a fission 
chain reaction, leading to the release of its inherent energy used for an atomic bomb. Uranium 235 has 
143 neutrons and 92 protons and makes up 0.72% of all uranium atoms; the rest is primarily uranium 
238 (99.2752%), which has 146 neutrons and 92 protons. U238 can’t be used to support a chain reaction

238 (99.2752%), which has 146 neutrons and 92 protons. U238 can’t be used to support a chain reaction 
due to the fact that it has inelastic scattering where the kinetic energies essentially dissipate on collisions. 
Uranium 235 is different since it allows for elastic chain reactions, i.e., which cause additional reactions, 
i.e., positive feedback, which results in an amplifying effect. Those extra neutrons in 235 strike the other 
nucleus and the chain reaction continues creating a critical mass, i.e., sustained nuclear reaction. Just 
to be complete, there are a number of other uranium isotopes with different numbers of neutrons that 
make up <1% of the remaining family of uranium atoms (U217 to U243; Figure 7.3). 
Fission equation: U235 plus one neutron results in krypton, barium, and three neutrons + energy:
 92 U235 + 0n1 → 55Cs140 + 37Rb93 + 3 0n1 + energy 
E = mc 2 developed by Einstein states that “mass and energy are the same physical entity and can be

E = mc 2 developed by Einstein states that “mass and energy are the same physical entity and can be 
changed into each other.” Physical atoms, at a basic level excluding all the subcomponents or elementary 
particles like quarks, leptons, bosons, and gluons (i.e., there are six types of quarks—up, down, strange, 
charm, bottom, and top—that make up neutrons and protons), have a nucleus with protons (positive 
charge) and neutrons (no charge) with orbiting electrons (negative charge) that all make up the standard 
model of elementary particles. The Higgs boson, postulated in 1964, was recently confirmed by the Large 
Hadron Collider in 2012; it explains why particles have mass generating the Higgs field (particles gain 
matter by passing through the Higgs field) and is an important piece used to explain the standard model 
of elementary particles (Figure 7.4).

[C] 
[B] 
[A] [1] 
[2] 
[3] 
 
FIGURE 7.3 (See color insert.) Uranium isotopes and fission chain reaction. 
d S b γ d 
e μ τ Z 
GAUGE BOSONS

d S b γ d 
e μ τ Z 
quarks: 
νe νμ ντ W 
Electron Muon Tau neutrino neutrino neutrino W boson 
nuclear force d 
 
166 Biomedical Informatics 
FIGURE 7 .4  (See color insert.)  Standard model of elementary particles inside a nucleus. (From Creative  
Commons, http://home.web.cern.ch/about/physics/standard-model). 
Atoms are more complex than the simple +ve proton, neutral neutron, and −ve electron models we 
are familiar with. They contain 17 subcomponents (see Figure 7.4) including the now confirmed Higgs 
boson and Higgs field that gives mass to particles. Atoms have an overall zero net charge. That means

boson and Higgs field that gives mass to particles. Atoms have an overall zero net charge. That means 
the number of −ve negative electrons equals the number of +ve positive protons. 
The succeeding text is a brief description of the standard model of particle physics (Conseil Européen 
pour la Recherche Nucléaire CERN http://home.web.cern.ch/about/physics/standard-model): 
1. All matter around us is made of elementary particles, the building blocks of matter. These par­
ticles occur in two basic types called quarks and leptons. Each group consists of six particles, 
which are related in pairs. 
2. The six leptons are similarly arranged in three generations—the electron and the electron neu­
trino, the muon and the muon neutrino, and the tau and the tau neutrino. The electron, the muon,

167 Medical Sensors 
and the tau all have an electric charge and a sizeable mass, whereas the neutrinos are electrically 
neutral and have very little mass. 
 3. There are four fundamental forces at work in the universe: the strong force, the weak force, the 
electromagnetic force, and the gravitational force. They work over different ranges and have dif­
ferent strengths. Gravity is the weakest but it has an infinite range. The electromagnetic force also 
has infinite range but it is many times stronger than gravity. The weak and strong forces are effec­
tive only over a very short range and dominate only at the level of subatomic particles. Despite its 
name, the weak force is much stronger than gravity but it is the weakest of the other three. The 
strong force, as the name suggests, is the strongest of all four fundamental interactions. 
 4. Three of the fundamental forces result from the exchange of force-carrier particles, which belong

4. Three of the fundamental forces result from the exchange of force-carrier particles, which belong 
to a broader group called “bosons.” Particles of matter transfer discrete amounts of energy by 
exchanging bosons with each other. Each fundamental force has its own corresponding boson— 
the strong force is carried by the “gluon,” the electromagnetic force is carried by the “photon,” and 
the “W and Z bosons” are responsible for the weak force. 
 5. On October 8, 2013, the Nobel Prize in Physics was awarded jointly to François Englert and Peter 
Higgs “for the theoretical discovery of a mechanism that contributes to our understanding of the 
origin of mass of subatomic particles, and which recently was confirmed through the discovery 
of the predicted fundamental particle, by the ATLAS and CMS experiments at CERN’s Large 
Hadron Collider.” 
7.2.2 Current and Ohm’s Law 
The flow of electrons in electronic devices and biological systems is essentially the flow of electrons, −ve

The flow of electrons in electronic devices and biological systems is essentially the flow of electrons, −ve 
charged particles.  Ohm’s law V = I × R (Voltage = Current[I] [times] Resistance) describes the relation­
ship between voltage (V), also called potential difference, which is the force that moves, or pulls, electrons  
through a wire; current (I), which is the measurement or amount of current flowing; and resistance (R),  
which regulates the amount of current. There are many ways to explain voltage. One side of the circuit 
has to be more positive than the other side. It pulls, or attracts, the −ve electrons through the wire. The 
only moving component is these electrons, called current (I), which is measured in amps, and the electrons 
(−ve) are attracted to the positive (+ve) side, i.e., called potential difference between two sides of the wire.

(−ve) are attracted to the positive (+ve) side, i.e., called potential difference between two sides of the wire. 
Resistance is a method of slowing down the electrons to control the amount of current, or electrons.  
Resistance is measured in ohms. Another analogy is water flowing in a pipe. The water is the current 
(electrons); turning on the faucet changes the water pressure, which is the voltage; and if you put rocks in  
the pipe, that would be equivalent to resistance slowing the movement of the water. 
Example 7.1: If volts = 10 and resistance is 2 ohms, then we can calculate the current through the 
circuit as V/R = I or 10 V/2 ohms = 5 amps (amps are a large amount of current). 
Example 7.2: If you increase the resistance to 5 ohms, then 10 V/5 ohms = 2 amps (Figure 7.5). 
Increasing resistance will reduce the current, or number of electrons, moving through the  
wire. 
7.2.2.1 Circuit Diagrams

wire. 
7.2.2.1 Circuit Diagrams 
Conventional current flow : The arrow for current flow, shows the direction of electron movement, I as it  
goes from +ve to negative. Originally, it was thought that +ve particles moved through circuits (before 
 electrons were discovered). This is incorrect but still used in many textbooks.

Electron current flow 
Ohms law Conventional current flow (–ve charge moves) 
Voltage = I current × Resistance (+ve charge moves) correct 
2 Ohms +
 + 
+ 10
 – –
V R– Volts 
Conventional current flow: The arrow for i current flow i  appears to be going from +ve 
to negative. Originally, it was thought that +ve 
Example © Lubliner 2013 particles moved through circuits. (before
Given 10 V and resistance 2 ohms electrons were discovered). 
Rearrange equation (divide both sides by R) Electron current flow: This is in reality the
V/R= I way a circuit works –ve electrons  move 
10 V/2 ohms=5 amps answer through a circuit. 
(an amp is large amount of current or Be careful, text books are inconsistent. Some 
electrons, typically we use milliamp (mA) a still use the old conventional (wrong) current
thousands of an amp1/1000 Or a micro amp flow notation. 
(μA) A millionth of an amp (1/1,000,000) 
168 Biomedical Informatics 
FIGURE 7.5 Ohm’s law. For example, V = I × R.

FIGURE 7.5 Ohm’s law. For example, V = I × R. 
Electron current flow : This is in reality the way a circuit works; –ve electrons move through a circuit, 
from −ve to positive. Correct representation of current flow. 
Be careful, textbooks are inconsistent. Some still use the old conventional (wrong) current flow notation. 
7. 2 . 3 E lec t r oc hem i st r y 
This section focuses on the linkages between chemistry, physics, and electrical conductors . Understanding 
the molecular connection of valence electrons, current flow, or a voltage caused by a chemical reaction in 
a battery is critical to understanding the underlying principles of medical sensors. Quantum mechanics 
addresses physics at the atomic level. When energy is applied to an atom, an electron can jump from 
a lower energy shell to a higher one in a discrete quantum. Once it returns back to its stable state, a

a lower energy shell to a higher one in a discrete quantum. Once it returns back to its stable state, a 
photon is given off. This principle used is medical imaging. Adenosine triphosphate (ATP), chemical 
energy, utilizes the same quantum process, which is responsible for the energy released when ATP is 
hydrolyzed; add H
2O, and it is converted to ADP (diphosphate); a phosphate is broken off and the energy 
is released. This section introduces some of those concepts linking chemistry, physics, and electronics. 
Electrochemistry is “a science that deals with the relationship of electricity to chemical changes and the 
interconversion of chemical and electrical energy.”* 
7. 2 . 3.1 Conductors 
Wires or conductors are made of materials that have valence electrons in their outer shells that can be 
easily stripped off. In the periodic table, metals such as copper (Cu), silver (Ag), and gold (Au) are all in

easily stripped off. In the periodic table, metals such as copper (Cu), silver (Ag), and gold (Au) are all in 
the same vertical column (group), which indicates similar electrical properties (Figure 7.6). 
Batteries have zero voltage, no charge; they are composed of chemical solutions that can be charged 
by moving electrons from one side to another. If the chemical solution on the positive side has +5 pro­
tons and −4 electrons (+5 − 4 = +1), it has a net charge or voltage of +1. The electrons were moved to the 
negative side, which now has +5 protons and −6 electrons (+5–6 = −1). Then if a wire was placed between 
* Source: Merriam Webster.

Neutrons 
Copper 
+ 2 
Ks 
Ls 
Lp Ms 
Mp 
Ms Ns 
26 2 6 1 0 1 
Protons 
HE-Helium 
NE-Neon 
Ar-Argon
IB and IIB 
(a) 
(Copper (Cu), Silver (Ag), Gold (Au) good conductors 1 electron, Valence shell

(Copper (Cu), Silver (Ag), Gold (Au) good conductors 1 electron, Valence shell 
Cu 
[2, 8, 18, 1]
Ag 
Gold (Au) 
Au Each shell starting with innermost
© Zachary Lubliner 2015 
(b) 
  
169 Medical Sensors 
FIGURE 7 .6 (See color insert.) Valence electrons, in an atom’s outer shell, conduct current (I). (a) Copper (Cu), 
silver (Ag), and gold (Au) valence electrons. (b) Conductors in the periodic table group 11, all have 1 electron in their 
valence shell.

170 Biomedical Informatics 
both sides of a battery, you would need to place some resistance in the wire or the electron flow would be 
so high the wires would melt; electrons will flow from the negative to positive side till they are balanced, 
i.e., net charge of zero (Figure 7.7). 
Lithium ion batteries are common in electrical devices. They contain a negative electrode made of 
carbon (graphite), the positive electrode is a metal oxide (lithium cobalt oxide), and the electrolyte is a 
lithium salt in an organic solvent. 
7.2.3.2 Batteries 
Batteries provide electrical energy from chemical reactions. They incorporate electrochemical cells, 
which allow the flow of ions. Ions are atoms with an imbalance of electrons and protons, i.e., are posi­
tively and negatively charged (negative charge refers to molecules that have more −ve electrons than 
+ve protons). Alessandro Volta designed the first battery in 1800, but the general concept was discussed

+ve protons). Alessandro Volta designed the first battery in 1800, but the general concept was discussed 
by Benjamin Franklin in 1748. The first practical battery cells appeared in the 1830s. 
Batteries are classified by chemistry, voltage, specific energy, energy density, specific power, C rates, 
and load (measured in watts [w], volt-amps [VA], and power factor [pf] where 1 is optimum):
 1. Chemistry : Most common are nickel and lithium (different chargers are recommended).
 2. Voltage: Potential difference between two points (one side has more charge, +ve or −ve).
 a. Open-circuit voltage. 
b. Closed-circuit voltage (underload).
 3.	 Capacity: Measured in ampere-hours (AH) at a given discharge rate (for example, 20 amps deliv­
ered for 10 h = 20 × 10 = 200 AH) (it is usually less than the max capacity rating).
 4. Specific energy : Is energy per unit mass. It is measured in watt-hours/kilogram (also called gravi­
metric energy density).

4. Specific energy : Is energy per unit mass. It is measured in watt-hours/kilogram (also called gravi­
 5.	 Energy density : Is energy stored in a given unit of space. It is measured in watt-hour/L (liter of 
volume) (also called volumetric energy density).
 6. Specific power: Is the load density, how much current can it draw.
 7. C rates: Charge and discharge rates.
 8. Load: Drawing energy from the battery with reduced charge and resistance drops over time. 
Convention compares battery ratings over a 20 hours period at 68°F. A 50 AH battery releases 2.5amps 
over 20 h (50 AH = 2.5 amps × 20). Battery ratings are quantified by the relationship between capacity, 
current, and discharge time described by Peukert’s law , developed originally for lead–acid batteries. 
Another perspective is the efficiency factor for discharging a battery. In a lead–acid battery that has 180 amp

Another perspective is the efficiency factor for discharging a battery. In a lead–acid battery that has 180 amp 
rating, you would expect 180 amps for 1 hour and 90 amps for 2 hours, but that is not the case. In reality 
you would get 180 amps for 37 minutes, a 63% loss due to the inherent limitations of batteries. The rule is 
the smaller the current draw, the closer it gets to the maximum rating of the battery. Finally, the Peukert 
value increases with age, which also limits the total current available. 
7 .2.3.2.1 Peukert Equation for Battery Efficiency 
Peukert’s law determines battery efficiency, which is the relationship between what is put in and what 
is removed. Lead–acid batteries have a 75% efficiency, so only three-fourths of what’s put in can be uti­
lized (i.e., this is affected by discharge rates and temperature). Battery capacity is the useable amount 
of energy in a battery. In general, a manufacturers’ listed capacity, in AH, is only 80% available for use.

of energy in a battery. In general, a manufacturers’ listed capacity, in AH, is only 80% available for use. 
For example, if a battery has 1,000 AH, only 800 amps are actually available. An AH is the total amount 
of electrical charge transferred when a current of 1 amp flows for 1 hour. A Peukert value of 1 indicates a 
well-performing battery with good efficiency and minimal loss (Figure 7.8). 
Peukert values for common batteries are as follows : 
• 	 Lithium ion batteries: 1.08 
• 	 Nickel based: 1.1–1.5 
• 	 Lead–acid batteries of 1.3–1.4 used for k in the succeeding formula I
k

–
   
171 Medical Sensors 
atom
atom 
atom
atom 
atom
–1 
–1
–1 
–1
–1 
–1–1 
–1–1
–1 –1 –1 
–1 
+ 
–1 
–1 
If each atom has 5 electrons
net charge to begin with
186,000 miles per second
(+5–5)= 0 
Atoms
need
electrons
Battery
Lithium Ion Battery Architecture
(http://www.nexeon.co.uk/technology/about-li-ion-batteries/)
e – 
e – 
e – 
e – 
e – 
e – 
e – 
e – 
Li + 
Li +
Li+
Li+ 
Li + Copper
negative
current
collector 
Aluminium
positive
current
collector 
Li x Si Li1–x MO2 
+– 
C + LiCoO2 LiC6 +L i0.5 CoO2 

positive
current
collector 
+– 
 (one electron enters the wire) knocks
Electrons Moving Through A Wire (Yellow Wire)
For the left side
. y r e t at m ion b u i h t i nd l re a i h a w g rou h g t n i ) mov l l e h e s nc le a v s ( on r t c le nd e y a r e t at B)  . t r se n  i r o l  co ee S (7   7 . E R U G FI

Peukert’s law for batteries: Peukert’s law is the efficiency factor for discharging a battery
(1 is excellent, 1.2 Ok and 1.5 poor efficiency)(relationship between capacity, current and discharge rates)
 
QP Available capacity vs. amp draw for 120 Ah battery
t = 
Ik 120
 
Capacity of a lead
100 X acid battery atQP  is the capacity when discharged at a rate of 1 amp. Peukert numbers
I 1.08  is the current drawn battery (A). 80 of 1.08–1.50 
1.12 t  is the amount of time (in hours) that a battery can sustain. 
60 k  is a constant around 1.3. 
losses; higher
Example: for the black line on the chart: 
a battery draw 120 AH (amp-hour capacity) = Qp 
Available capacity (Ah)
A value close to 
1.2 1 has the smallest 
40 1.3 numbers deliver 
lower capacities.
20 
The battery draw Ik=10 amp1.3 1.5 Source: von Wentzel= 19.95 
 (2008)Answer t = 120/19.95 = Approximately 6 h 0 0 1 0 2 0 3 0 40 50

20 
 (2008)Answer t = 120/19.95 = Approximately 6 h 0 0 1 0 2 0 3 0 40 50 
Ampore draw (A)The output is not what is put in because of inherent losses Lithium battery K = 1.08 and these losses escalate with the load. The higher the Nickel based K = 1.1–1.2 current draw the greater the loss Lead acid battery K = 1.3–1.5 
172 Biomedical Informatics 
FIGURE 7.8 Peukert equation for calculation battery efficiency. 
The term “ba ttery m em o ry effect” r ef ers to ba tteries tha t h o l d l ess charg e if th ey ar e charg ed an d  
di s c h ar g e d  a t  l ess  th an  full  p o w e r ,  f o un d  in  r e c h ar g e a b l e  b a tt e ri es  m a d e  fr o m  ni c k e l –ca dmi um  an d  
nickel–metal hydride. The environmental impact is that batteries with lead and cadmium in lead–acid 
and nickel–cadmium batteries have to be treated as  hazardous materials. 
7.2.3.3 Battery  Classification

7.2.3.3 Battery  Classification 
The following is a list of characteristics of popular batteries. Batteries are classified by their performance 
c h ara ct e ris ti cs.  F o r  e xam p l e,  ar e  hi gh - s ur g e  curr e n ts  n ee d e d  w h e n  s tartin g  car s  (l ea d – a ci d  p r o vi d es  
high-surge current)?
 1.  Lead–acid batteries  (invented in 1859; are the oldest rechargeable battery) 
 a. 	 Ability to provide high-surge currents, used in automobiles.
 b.	  Inexpensive. 
 c.	  Low energy-to-weight ratio. 
 d. 	 Used as backup for cell towers. 
 e. 	 Chemistry: (negative plate) Pb(s) + HSO
−
4 (aq) → PbSO4(s) + H + (aq) + 2e−. 
 f. 	 Advantage over other chemistries. It is relatively simple to determine the state of charge by 
measuring the specific gravity of the electrolyte. 
 g. 	 Excessive overcharging can result in gassing, releasing hydrogen and oxygen, which can

 g. 	 Excessive overcharging can result in gassing, releasing hydrogen and oxygen, which can 
result in an explosion if not properly vented. 
 h. 	 Environmental concerns: Some of the lead products are very toxic and have to be properly 
handled when discarding. Toxins dangerous to children.
 2.  Nickel–iron rechargeable batteries  (NiFe) (invented in 1899) 
 a.	  Have nickel-ion-hydroxide and iron plates. 
 b. 	 Used in backup systems but have poor charge retention. 
 c. 	 Chemistry: 2NiOOH + 2H 2O + 2e−  ↔ 2Ni(OH)2 + 2OH−. 
 d. 	 The charging and discharging transfer of oxygen from one electrode to the other. 
 e. 	 Environmental impact: Do not have to be treated as hazardous materials.
 3.  Nickel–zinc rechargeable battery  (NiZn) (In 1901, Edison received a patent [#684,204]) 
 a. 	 Often used in AA and AAA batteries. 
 b. 	 Higher discharge ratio, up to 75%, compared to lead–acid batteries.

a. 	 Often used in AA and AAA batteries. 
 b. 	 Higher discharge ratio, up to 75%, compared to lead–acid batteries. 
 c.	  After 30 charges, batteries tend to self-discharge more quickly.
 d.	  Chemistry:  2H2O + Zn + 2NiOOH ↔ Zn(OH)2 + 2Ni(OH)2.
 e.	  Usually  expensive.

173 Medical Sensors
 4. Alkaline batteries (ZnMnO2) (developed in 1899) 
 a.  Contain zinc and manganese dioxide. 
 b. Higher energy density than zinc–carbon batteries. 
 c. Largest percentage of batteries made in the United States.
 d.  Chemistry:  Zn −
(s) + 2OH−
(aq) → ZnO(s) + H2O(l) + 2e  [e° = 1.28 V].
 e.  2MnO −
2(s) + H2O(l) + 2e  → Mn 2O3(s) + 2OH−
(aq) [e° = +0.15 V]. 
 f. Most are not designed for recharging, though some are. 
 g. Newer alkaline batteries are allowed to be disposed of as regular domestic waste.
 5.  Lithium ion batteries (Li-ion) 
 a. There are environmental benefits with reduced toxins compared to conventional batteries. 
 b.  Lightweight: They have higher capacity/weight ration than convention batteries. 
 c. Low discharge rate 1.5% per month. 
 d. Safety issues if overcharged or overheated. 
 e. Do not suffer from memory charging effect. 
7 .2.3.3.1 Battery Energy Density Levels

d. Safety issues if overcharged or overheated. 
7 .2.3.3.1 Battery Energy Density Levels 
Energy density is defined as “the amount of energy stored in a given system or region per unit volume.”* 
The succeeding chart illustrates the energy density comparison ranging from lead–acid to lithium– 
cobalt batteries (Figures 7.9 and 7.10). Lead–acid has 50% of the energy capacity of lithium oxide. 
7.2.3.4 Inductive Charging 
Charging devices without a physical connection can be an important feature of implanted or wire­
less medical devices. Any opening in the skin is a pathway for infection. So the optimal configura­
tion is wireless inductive charging. Inductive charging involves two coils separated by a small distance. 
Current going through a coil produces a magnetic field. A second coil utilizes that magnetic field to 
create current flow in the second device, thus charging the implanted battery.

create current flow in the second device, thus charging the implanted battery. 
Lithium cobalt batteries, or more specifically Lithium Lithium cobalt oxide 
Nickel Cobalt Aluminum Oxide (LiNiCoA1O2), -High specific energies used for cell phones 
are able to store the highest capacity, or specific energy
per unit size. 
Cobalt oxide A. High specific energy and power densities
Lithium ions B. Long life span 
C. Used in electric vehicles 
D. Negatives: high cost and safety issues 
Lithium manganese cobalt
Lithium manganese or more specifically Lithium Nickel -3D structure: cathode crystalline structure 
Manganese Cobalt Oxide (LiNiMnCoO2), and lithium phosphate, -50% more energy than nickle-based chemistries. 
Lithium Iron Phosphate (LiFePO4 ), have higher load, power draw 
capabilities. Manganese
oxide A. Nickel is known for its high specific energy, but low stability 
B. Manganese has low internal resistance and low specific energies 
 Lithium ions

 Lithium ions 
http://batteryuniversity.com/leam/article/
types_of_lithium_ion 
FIGURE 7.9 Comparison of high-energy lithium cob lot versus high-energy lithium manganese. 
* Source: Dictionary.com .

Highest load, can
draw more power Highest capacity
energy levels 
180 
160 
140 
120 
Watt hours/kilogram
(energy density) 
Wh/kg
100 
80 
60 
40 
20 
0 
Lead acid NiCd NiMH Li
– Li– NMC Li– 
phosphate manganese cobalt 
  
174 Biomedical Informatics 
FIGURE 7 .10  Comparison of battery energy densities. (From http://batteryuniversity.com/learn/article/types_ 
of_lithium_ion.) 
Definition: Inductive charging  is a method by which a magnetic field transfers electricity from an 
external source to a mobile device without the use of standard wiring. It does this by generating a 
magnetic field and creating a current in the receiving device. Electricity can move through the air 
and recharge your device’s battery. 
(http://wireless-charger-review.toptenreviews.com/wireless-chargers-inductive-charging­
explained.html.) 
When transferring energy between coils and the transformer equation in the succeeding text, trans­

formers are used to step up or down current. When you plug in a charger for your phone, a transformer, 
which has two coils, reduces voltage from 110 ac to 9 V dc. 
The transformer equation relates to the turns of wire on the coil, i.e., a coil is wire wrapped around a 
metal post a few thousand times. The equation relates the voltage between the first, primary coil to the 
secondary coil. Transformers work with alternating current that creates a changing magnetic field. So 
in the secondary coil, you then convert the ac to dc (Figure 7.11): 
Vp/Vs = Np/Ns 
where 
Vp is the voltage in the primary core 
Np is the turns of wire in the primary core 
Vs is the voltage in the secondary core 
Ns is the turns in the secondary core 
7.2.4 Fiber Optics 
Electrons are not the only way information can flow through wires. Photons, packets of energy, can flow

Electrons are not the only way information can flow through wires. Photons, packets of energy, can flow 
through fiber-optic cables, pure glass materials, with almost no resistance. Photons are generated when 
energy is applied to an atom. An electron moves from a lower energy shell to a higher one. Quantum 
mechanics states that electrons are in fixed orbits and can only exist at discrete shells or energy levels. 
When that moved electron returns to its preferred low shell or lower-energy state, one packet of energy 
or photon is given off (Figure 7.12).

Transmitting coil Receiving coil Primary 
core 
Coils Secondary 
core 
R1 
D5 + L1 L2 
L1 
C3 C4 Li-Ion 
C1 Battery 
L2 
– Magnetic field 
http:/ /homemadecircuitsandschematics.blogspot.com/ 
In secondary core you need a
circuit to convert AC current 
External charger Implantable Advanced neuro­
modulation system implanted to
control pain 
to DC 
http://www.implantable-device.com/2012/01/12/st-judes-ans­
rechargeable-spinal-cord-stimulators-eon-and-eon-mini/ 
 
–
–
–
 
175 Medical Sensors 
FIGURE 7 .11 Inductive current circuit and coils, conversion from ac to dc, and implantable neuromodulation 
system with 10-year life span charged externally using inductive charging device. 
Spectrum of Electromagnetic Radiation 
Region 
Energy imparted to atom,
electron moves to next 
shell 
When electron return to 
previous shell it gives off
one photon (packet)
of energy 
In empty space, the
photon moves at c (the
speed of light 186,000
miles/s) and its energy
E and momentum P are

of energy 
E and momentum P are 
related by E + cP. 
The photon is the 
elementary particle 
responsible for 
electromagnetic 
phenomena. It is the carrier 
of electromagnetic radiation 
of all wavelengths, including 
gamma rays, X-rays,  ultraviolet 
light,  visible light, infrared light, 
microwaves, and radio 
waves. The photon differs 
from many other elementary 
particles, such as the electron 
and the quark, in that it has 
zero rest mass 
@Copyright David Lubliner NJIT 2014 
No chargeProtons 
+ 
Neutrons 
The word “quantum’’ (Latin,
“how much”) in quantum
mechanics refers to a 
discrete unit that quantum
theory assigns to certain
physical quantities, such as
the energy of an atom at rest
(see Figure 1, at right). The
discovery that waves have
discrete energy packets 
(called quanta) that behave in
a manner similar to particles
led to the branch of physics

that deals with atomic and 
subatomic systems 
Wavelength
(Angstroms) 
>109 >10 <3 × 109 <10–5 
109 –1 06 
106 – 7000 
7000 – 4000 
4000 – 10 
10 – 0.1 
<0.1 
10 – 0.01 
0.01 –7×1 0 –5 
7×1 0–5 –4×1 0 –5 
3×1 09 –3×1 0 12 
3×1 012 –4.3×1 0 14 
10–5 – 0.01 
0.01 – 2 
2–3 
3–1 03 
103 –1 05 
> 105 
4.3×1 0 14–7.5×1 0 14 
7.5×1 0 14–3×1 0 17 
3×1 017–3×1 0 19 
>  3×1 019 
4×1 0–5 –1 0–7 
10–7 –1 0–9 
<10–9 
(centimeters) 
Frequency
(Hz) 
Energy
(eV) 
Radio 
Microwave 
Infrared 
Visible 
Ultraviolet 
X-Rays 
Gamma Rays 
Quantum mechanics (photons generated) 
FIGURE 7 .12 Quantum mechanics, photons created when electrons return to their original shells.

Resistance to regulate current flow
V = IR Voltage = current*resistance
 
1–v e 1–v e 
SynapseBattery space between neurons
 
–l = (5P+) (–6E) negative
 
1–v e 1–v e 
1– v e 1– v e
 
5P+ 5N 5P+ 5N
 
Dendrite 1– v e 1– v e Axon 
1–v e 1–v e 
Potential difference, or voltage, between the
two electrodes; i.e. one side is more positive + + 
than the other. We move –ve eletrons, charge Positive ions moved across the gap making one side more positive,the battery, from one side to the other. potential difference 
© Potential difference Lubliner 2012 
 
176 Biomedical Informatics 
7.3 Data Acquisition: Medical Sensors 
Medical data acquisition falls into a number of categories: electrical (EEG/EKG), electromagnetic, imag­
ing (MRI, PET), chemical, biological, and genomic data sequencing. This section describes the theory 
behind some of those data acquisition technologies and explains various medical sensors and scanners.

behind some of those data acquisition technologies and explains various medical sensors and scanners. 
A prerequisite for mining data and extracting meaning is a basic understanding of those technologies 
that generate this information. 
7.3.1 Sensors 
Electrical current in nerve cells, at the highest level of abstraction, current flows (electrons −ve) move 
toward a positive potential, i.e., one side of a wire or nerve is positive. In a battery, you have two chemical 
solutions, initially both neutral; let’s say, for argument, that the atoms on each side of the battery have 10 
protons and 10 electrons. When charging a battery, you move electrons from one side to the other, i.e., 
one side has 9 electrons and the other 11 electrons (Figure 7.13). This provides a positive potential differ­
ence between the two sides of the battery, i.e., one side is more positive than the other. When connecting

ence between the two sides of the battery, i.e., one side is more positive than the other. When connecting 
a wire between terminals of the battery, the electrons, negative, move to the positive side. Once both 
sides are neutral, both have 10 protons, positive, and 10 electrons, the potential difference disappears, 
and no current flows. 
The same is true for electron flow in the body. In order for current to flow, a potential difference must 
be created from one synapse, the space between neurons, to the next. This is achieved by pumping posi­
tive ions across that gap between nerves. This sodium (NA
+)–potassium (K+) pump (Figure 7.13). 
7.3.2 Electrical Conduction System of the Heart 
7.3.2.1 Action Potential 
EKG measures the electrical activity of the cardiac muscle of the heart. When the sinoatrial (SA) node, 
the pacemaker of the heart located in the right atrium, initiates signals, it then sends signals to the atrio­

ventricular (AV) node, then the bundle of His, and the right and left bundle branches and then to the 
Purkinje fibers that propagate the signals to the ventricles. 
FIGURE 7 .13 Potential difference in a battery and 4b potential generated in synapse.

177 Medical Sensors 
NA+ K+ 
In order to create the (action) potential for
the SA node to initiate an electrical signal,
potassium rushes out returning the potential to
negative stopping current (electron) flow 
–20 mv 
–60 mv 
0 mv 
Time 
NA+ CA2+ K+ 
Pacemaker cell 
Third, potassium channels open up and
first more sodium (NA+) enters the cell then
potassium (K+) leaves 
–20 mv 
–40 mv 
Second, calcium channels open up and calcium
rushes in creating an (action) potential 
NA+ K+ 
© Action potential lubliner 2012c 
FIGURE 7 .14  Action potential in cardiac nerves. 
In the SA node/pacemaker step 1, a large number of sodium ions (NA+) and a small number of potas­
sium ions (K+) are migrating through the cell. Then in step 2, calcium (CA 2+) channels open up, creating 
an (action) potential, i.e., cells become more positive generating a current (flow of electrons) in milli­

volts, a thousandth of a volt (Figure 7.6). In step 3, a potassium channel opens up so more potassium ions 
flow out and the potential difference returns to negative, stopping the flow of current. 
The action potential in cardiac muscle cells is initiated by a sodium spike that generates a calcium 
spike, which then produces muscle contraction (Figure 7.14). The voltage of a cell is usually measured in 
millivolts (mv), a thousandth of a volt. 
7 .3.2.1.1 Excitation–Contraction Coupling 
This section is intended to provide more detail than the previous action potential section specifically 
focusing on electrical properties. The cardiac myocyte is a muscle cell that is 100 μ in length. It is com­
posed of bundles of myofibrils that contain filaments. The myofibril, tubelike structures, propagates

posed of bundles of myofibrils that contain filaments. The myofibril, tubelike structures, propagates 
signals inside the muscles. They have repeating sarcomeres, which contract and have regions of micro-
filaments composed of myosin and actin. Excitation–contraction coupling (ECC) is the process whereby 
an action potential triggers a myocyte to contract [4]. 
ECC: The action potential in cardiac myocytes (Figure 7.15). 
The interior of the muscle cells have a negative charge, so moving positive ions in and out of the cells 
produce action potential, a fast positive spike that triggers the cell to contract. The positive ions are Ca
2+  
(calcium +123 mv), Na + (sodium +67 mv), and K + (potassium −92 mv); the ions move into and out of 
cells, via voltage-gated cells, that change the polarity inducing muscle contraction. 
 1. Begins with a baseline negative state (−90 mv)— stage 4 
 2.  Threshold (70 mv): Ca2+ and Na+ enter the cell and become more positive— stage 0

Muscle cell Motor neuron myocytes
 ions +ve 
2+Ca  (calcium) +123 mv) (membrane potential dotted line) 
+Na  (sodium) + 67 mv) 
20 mv 1 
0 fast action potential –70 mv 3
–90 mv 
They have repeating 2. Myofibril: tube- + 4 relaxed state 4 relaxed state 
K  (potassium –92 mv) sacromeres which contract:     like structures
 –ve 
microfilaments composed of     inside the muscles 
178 Biomedical Informatics
FIGURE 7 .15  (See color insert.)  Cardiac myocytes and the ECC action potential triggered by sodium, calcium, 
and potassium ions. 
3.  Fast  Na+ channels open, Na+ enters the cell, and voltage-gated cells close when it reaches 20 mv— 
stage 1

stage 1
 4. K + channels open and move to negative, and Ca 2+  enters and stabilizes (flat line 5 mv)— stage 2
 5.  Ca2+ channels close and it goes negative— stage 3 
7.3.2.2 Cardiac Conduction System 
The heart takes deoxygenated blood from the veins, entering through the right side of the heart; blood 
passes through the right atrium and right ventricle and then moves to the lungs to oxygenate the blood 
(and releases CO
2); it then returns to the left atrium and left ventricle and passes out of the aorta to the 
arteries and to the rest of the body. 
7 .3.2.2.1 Definition 
• 	 The  SA node is located in the right atrium where the superior vena cava joins the atrial tissue; the 
SA node acts as the main pacemaker in the heart. 
• Automaticity: AV cells can depolarize by themselves.

• Automaticity: AV cells can depolarize by themselves. 
• 	 Depolarization : Muscle cells, cardiac myocytes, are made up of negatively charged cells; when 
positive ions are pumped into the cell, calcium (Ca 2+), sodium (Na +), and potassium (K +), the  
polarity of the cell becomes positive and the cell contracts (negative to positive membrane 
potential). 
7 .3.2.2.2 Electrical Conduction in the Heart 
Step 1: The SA node is composed of negatively charged cells that can depolarize by themselves called 
automaticity. They send out depolarization signals, to start other muscles cells to contract (from 
the SA node, the impulse travels through the right and left atrium along three internodal tracts) 
(Figures 7.16 and 7.17). 
Step 2 : This depolarization signal goes simultaneously to the left atrium, called Bachman’s bun­
dle, and to the AV node. It travels along three internodal tracks: anterior, Wenckebach’s, and  
Thorel’s.

Thorel’s. 
Step 3: The AV node creates a 0.1 second delay (explanation: the atria contracts, the signal is sent from 
the first SA node to the atria, then the depolarization signal travels to the AV node and delays, 
and then the ventricles contract; the purpose is to move the blood first from the atria and then

2 Located in the left ventricle 
Bachmann’s 
bundle 
2 
Right bundle 
Left posterior
bundle 
Atrioventricular 
node 
Sinoatrial node 
Intermodel 
pathways Transitional fibers 
AV node 
-AV fibrous tissue 
-Penetrating portion of 
AV bundle 
-Distal portion 
-Left bundle 
Ventricular septum 
Right bundle
branch 
1 
AV node juncture of the atria and ventricles 
3 Internodal pathways SA to AV 
His bundle 
Purkinje
fibers 
 
SA 
node 
Bachman’s 
bundle 
Left 
atria 
AV 
node 
0.1 s 
3 Internodal 
tracks 
Bundle of HIS 
Right
ventricle 
Left 
ventricle 
Right
atria 
1 
2 
3 
4 
5 
Beat 1 Beat 2 
VA node 
Ventricles 
contract 
SA node 
atria’s 
contract 
0.1 s delay
by AV node 
0.1 s delay
by AV node 
Time 
Left bundle 
Purkinje fibres 
 FIGURE 7 .17 Electrical conduction system of the heart. 
179 Medical Sensors 
FIGURE 7 .16  Intermodal pathways from the SA node to the AV node. 
they contract and push the blood to the ventricles, which then also contract; timing needs to be

they contract and push the blood to the ventricles, which then also contract; timing needs to be 
properly sequenced). 
Step 4: The AV node sends the signal to the bundle of His. 
Step 5: From there, it splits to the right bundle wires (nerves) and left bundle (the left bundle broken 
into left posterior fascicle and right anterior fascicle). 
Step 6: The signal spreads out to smaller nerves in the ventricles called the Purkinje fibers.

(ADP) Adenosine Di(2) phosphate 
(ATP) Adenosine Tri(3) phosphate P + ENERGY + ADP 
(Three phosphates P+P+P ) Adenosine (two phosphates P + P) 
The hydrogen atom gives hydrogen OH OHRNA 
Add H2O 
Phosphate 
Adenine 
subcomponent of
DNA 
NH2 
hydrolyze 
NH2 
group 
P 
O 
O 
OH 
O P 
O 
OH 
O 
O 
OH 
P O 
O 
N 
N 
N 
N 
OH 
O P x 
O 
Phosphate group 
OH
ENERGY (e – ) 
Hx O 
O O 
P O P O 
OH OH O 
N 
N N 
N 
Valence electron is shared in a 
Ribose 
subcomponent of H2O 
high energy state (higher orbit) and oxygen to the phosphate andand when released electron OH OH contributes the other hydrogen to themoves to a lower orbit diphosphate molecule. And releasesreleasing energy (quantum energy (stable resonance state) physics) 
 
180 Biomedical Informatics 
7. 3. 2 . 3 Adenosi ne T r iphosph ate 
ATP is a molecule that provides energy to power biological systems, i.e., intercellular energy transfer or

ATP is a molecule that provides energy to power biological systems, i.e., intercellular energy transfer or 
chemical energy in cells for metabolism, an enzyme-catalyzed reaction. ATP is made up of three phos­
phate groups, each having a phosphate atom with three oxygen atoms, and an adenosine molecule that’s 
composed of adenine (subcomponent of DNA: adenine, guanine, cytosine, and thymine) and ribose, a 
subcomponent of RNA. 
When ATP is hydrolyzed and H
2O is added, it breaks into a phosphate and ADP and releases energy 
that can be used for intercellular energy. One hydrogen atom bonds to the diphosphate molecule, the 
other to the phosphate, creating a resonance state, a stable state for the molecules (Figure 7.18). As we 
discussed earlier, when describing quantum mechanics, electrons want to return to their stable states. 
So in ATP, the third phosphate shares an electron in a higher energy state with another phosphate group,

So in ATP, the third phosphate shares an electron in a higher energy state with another phosphate group, 
i.e., an electron in a higher orbit, but when hydrolyzed, it releases energy and returns to its original lower 
stable electron state, orbit (Figure 7.18). 
7 .3.3 Blood Pressure 
Blood pressure is the pressure on the walls of blood vessels that is exerted by circulating blood and is 
measured by the force per unit area. Blood pressure is the brachial arterial pressure usually measured in 
the upper arm as blood moves away from the heart. 
 1.  W
hen the heart muscle contracts, called systole, it pumps blood out of the heart through the arter­
ies to the rest of the body. This blood pressure on the arteries is systole. Normal blood pressure is  
120 or lower. Hypertension, or high blood pressure, is 140 or above. A systolic pressure of 120–139 
is prehypertension, meaning there is an elevated risk of heart disease. 
 a. 	 The heart contracts in two stages.

 a. 	 The heart contracts in two stages. 
 i.	  In the first stage, the right and left atria contract at the same time, pumping blood to the 
right and left ventricles. 
 ii. 	 Then the ventricles contract together to propel blood out of the heart.
 2. Then the heart muscle relaxes , called diastole , before the next heartbeat. This allows blood to fill 
up in the heart again. This is the lower reading in blood pressure that indicates the pressure on the 
arteries when the heart rests between beats. Normal values are 80 or below. A diastolic pressure of  
90 or above is hypertension and 80 to 89 is prehypertension. FIGURE 7 .18 ATP molecule, which hydrolyzes released energy, results in ADP. (From http://en.wikipedia.org / 
wiki/File:Adenosintriphosphat_protoniert.svg.)

Brain 
Lungs (It’s the only vein that carries oxygenated blood) 
Artery 
Pulmonary
veins from 
lungs AD PA 
Pulmonary veins
from lungs 
LA 
by blood Heart 
Superior 
vena cava 
Atrial septum RA LV Aortic valve 
heart in 
arteries 
Tricuspid
valve 
Inferior 
vena cava 
RV 
AO = Aorts 
septum 
 RA = Right atrium
Oxygen poor RV = Right ventricle 
 
181 Medical Sensors 
FIGURE 7 .19  (See color insert.)  Blood pressure exerted on the artery walls.

FIGURE 7 .19  (See color insert.)  Blood pressure exerted on the artery walls. 
The conventional device used to measure blood pressure is called the sphygmomanometer. It has a pres­
sure gauge, and when the cuff is inflated to a pressure higher than your systolic pressure, it stops blood 
flow. The pressure is slowly released and, through a stethoscope, a hearing device, a whooshing sound is 
heard, and at this point, the systolic pressure is measured; when this sound goes away, the diastolic pres­
sure is measured (Figure 7.19). A number of wearable (watch) blood pressure devices are available that 
conform to the same process (accuracy of wearable devices is within 5% of manual devices). 
7.3.4 Pulse Oximetry 
Pulse oximetry is a noninvasive method of monitoring oxygen saturation of a patient’s hemoglobin, 
the protein in blood that carries oxygen. Pulse oximetry can alternatively be measured invasively by

the protein in blood that carries oxygen. Pulse oximetry can alternatively be measured invasively by 
arterial blood gas (ABG) analysis. Individuals without coronary disease have a pulse oximetry read­
ing of 90% to 95%. In transmissive pulse oximetry, the process uses a pair of light-emitting diodes 
on one side of a finger and a photoreceptor on the other. There are two LEDs, one red at 660 nm 
wavelength and a second at 905 to 940 nm in the infrared range. The absorption at these wavelengths 
differs between its oxygenated hemoglobin and deoxygenated state. The ratio of the two can be calcu­
lated using the two frequencies. The absorption is calculated from the minimum versus peak values of 
the pulsing arterial blood flow, which makes simultaneous monitoring of the pulse critical. Reflective 
pulse oximetry can be used in more areas of the body but can lead to inaccurate readings in cyanotic

pulse oximetry can be used in more areas of the body but can lead to inaccurate readings in cyanotic 
tissues close to the surface having low oxygenation, or areas where arterial and venous pulsations 
mask readings. 
Limits of pulse oximetry 
• 	 Hypoperfusion : Inaccurate low readings may be caused by vasoconstriction, i.e., narrowing of the 
blood vessels that results from contraction of the muscular walls of the vessels or poor circulation 
in the extremity. 
• 	 Calloused skin. 
• Movement (shivering).

182 Biomedical Informatics 
7.3.4.1 Physics of Pulse Oximetry 
The two wavelengths of light used in pulse oximetry are red at 660 nm and infrared at 905 to 940 nm. 
Radiation absorption is governed by two laws, Beer’s law and the Lambert–Bouguer law. 
 1.  Lambert–Bouguer law involves 
 a.	  A solution of thickness (d) 
 b.	  The solution is transilluminated by monochromatic light ( l) 
 i. 	 Definition: Transilluminate refers to passing a strong light through an organ or part of 
the body in order to detect disease or abnormality. 
 c.	  Incident light (lo): The direct light that falls on a surface: 
 I = Io  e−(ad)
 2.  Beer’s  law 
  The absorbance is a linear function of the molar concentration. 
  Definition: The molar concentration, C i, is defined as the amount of a constituent n i measured in  
moles divided by the volume of the mixture V: 
nC i
i  
 V 
3.  Beer–Lambert  law 
  Definition: Attenuation of light by a material passing through a substance. A photon is absorbed

nC i
i  
 V 
  Definition: Attenuation of light by a material passing through a substance. A photon is absorbed 
by matter, the electrons, and transformed into internal energy or thermal energy. The reduction 
in intensity of the light wave is referred to as absorption. 
 a.	  ε is the molar extinction coefficient: 
 i. 	 The greater ε is, the greater the absorption, which means less light is transmitted. 
 ii. 	 Oxygenated hemoglobin (HbO 2) at 660 nm has a lesser extinction coefficient than hemo­
globin (Hb) and therefore absorbs less red light.
 b.	  c is the molar concentration.
 c.  d is the thickness of the layer.
 
  Absorbance (ad) = εcd
 
  Definitions:
 1.  Oxyhemoglobin (oxygenated hemoglobin  [HbO2]) saturation is the ratio, expressed as a percentage 
of the amount of oxygen relative to the total amount of hemoglobin in the blood.
 2.  Hemoglobin is an iron-containing protein bound to red blood cells and makes up nearly all the

2.  Hemoglobin is an iron-containing protein bound to red blood cells and makes up nearly all the 
oxygen presence: except there is a small amount dissolved in the plasma. It’s a metalloprotein, a 
generic term for a protein that contains a metal ion cofactor. 
 a. 	 Hemoglobin is responsible for transporting oxygen from lungs to other parts of the body. 
Oxyhemoglobin (HbO
2) is the red hemoglobin that is a combination of hemoglobin and oxy­
gen from the lungs. 
 b.	  A hemoglobin molecule can carry a maximum of four oxygen molecules. For example, 100 
hemoglobin molecules could carry a maximum of 400 oxygen molecules (100 × 4); if it only 
carried 360 oxygen molecules, (360/400) × 100% = 90% saturation rate. 
 c. 	 The protein makes up about 96% of the red blood cells’ dry content (by weight) and around 
35% of the total content (including water) in mammals. 
 i.	  It carries a portion of the body’s respiratory CO
2, about 10% of the total, and the regula­

i.	  It carries a portion of the body’s respiratory CO
tory molecule nitric oxide.

183 Medical Sensors 
7.3.4.2 Arterial Blood Gasses 
ABG requires drawing blood from an artery, often taken from the radial artery at the wrist or the femoral 
artery in the groin, but a number of other sites are used. ABG provides more comprehensive information 
than simply pulse oximetry information, which is vital for critically ill patients in intensive care units. 
ABG measurements 
 1.  pH of the blood. 
 2. Partial pressure of carbon dioxide and oxygen. 
 3. Transcutaneous carbon dioxide measurement is an alternative method of obtaining similar infor­
mation as well. 
 4. An ABG test measures the arterial oxygen tension (PaO
2). 
 5. Carbon dioxide tension ( PaCO2). 
 6.  Arterial oxygen saturation is ( SpO2) in the range of 95% to 100%. 
 a.	  Defined as the ratio of oxygen to the total concentration of hemoglobin present in the blood. 
 7.  Venous Oxygen Saturation (SvO2) (Range 65%–75%)

7.  Venous Oxygen Saturation (SvO2) (Range 65%–75%) 
 b.	  Percentage of oxygen bound to hemoglobin in blood returning to the right side of the heart.  
This is the oxygen remaining after the tissues remove what they need. It is used to determine 
when a patient’s body is extracting more oxygen than normal. It’s taken from the tip of the 
pulmonary artery catheter 
Oxygen delivery ( DO
2) = cardiac output (HR × stroke volume) × oxygen content (Hb × SaO 2)
 c.	  Rationale: If SvO2 decreases , it indicates that the tissues are extracting a higher percentage of  
oxygen from the blood than normal. 
 i.	  It may imply that the cardiac output is not high enough to meet tissue oxygen needs. 
 ii. 	 Another explanation is that the patient has resorted to anaerobic metabolism. (Anaerobic 
metabolism is the creation of energy through the combustion of carbohydrates in  the 
absence of oxygen.) It indicates that the tissues are unable to extract enough oxygen. It

absence of oxygen.) It indicates that the tissues are unable to extract enough oxygen. It 
can be seen in late septic shock or poisoning such as cyanide.
 iii. 	 Measuring SvO
2 before and after a change can determine if the therapy was beneficial. 
 iv. 	 It’s also helpful when evaluating changes to ventilator therapy. 
7.3.5 Neurons 
Neurons are electrically excitable cells that communicate information through electrical and chemi­
cal signals. Neurons are connected via synapses, a structure that allows a neuron to pass an electrical 
or chemical signal to another neuron (Figure 7.20). Na
+ ions, from other neurons, are attached to the 
neuron via the dendrites, synapse in between the connection, thin filaments. When enough of these 
dendrites send a sufficient amount of Na
+ ions, the action potential of the cell is triggered and a signal 
is sent along the neuron. As the charge dissipates along the length of the neuron, electrotonic spread,

is sent along the neuron. As the charge dissipates along the length of the neuron, electrotonic spread, 
voltage-gated channels open up to add more Na
+ ions amplifying the signal. 
The architecture of a neuron starts with a nucleus surrounded by a cell body or soma. They have a 
number of branching structures called dendrites that receive signals. Dendrites are connected to other 
neurons. If multiple signals on different dendrites reach a threshold, they are added up to generate 
a composite signal. They trigger an action potential, and a signal is sent along the axon. This signal 
might trigger muscles or other neurons. Neurons are connected through axons, long conductors, that 
are covered with Schwann cells covered in an insulating myelin sheath. The myelin sheath creates an  
insulated wire that allows signals to flow faster than action potentials. There are gaps between these

insulated wire that allows signals to flow faster than action potentials. There are gaps between these 
insulators; myelin sheaths are called nodes of Ranvier. The rationale, reiterating concept from earlier, of 
the nodes of Ranvier is that since current dissipates along the neuron, called electrotonic spread, at these

Neuron 
Dendrites 	 Sodium potassium pumps move sodium (Na+) and
Nucleus (insulation) gaps in the membrane. The purpose is to create a
make up the voltage strong enough to draw electrons across theNa+ –Ve	 Myelin sheath
Nodes of ranvier Na+ 
Potassium(spaces)	 Sodium K+ 
Voltage gated Na+
 
K+ 
 
184 Biomedical Informatics 
FIGURE 7 .20  (See color insert.)  Neurons and signal transmission across synapses.

FIGURE 7 .20  (See color insert.)  Neurons and signal transmission across synapses. 
junctures, voltage-gated channels open up to allow in more Na+ ions in to propagate the signal down the 
length of the neuron, essentially amplifying the signal (Figure 7.20). 
Sodium–potassium pumps move sodium (Na+) and potassium (K+) ions across the neuron cell through 
gaps in the membrane. The purpose is to create a voltage strong enough to draw electrons across the syn­
apse, a gap between neurons; it’s a structure that permits a neuron (or nerve cell) to pass an electrical or 
chemical signal to another cell and create current flow. It uses ATP cellular energy to bind the Na
+ and K+ to 
proteins to the surface of the pump to draw in or expel ions. The neuron cells are negative inside and positive 
outside creating a voltage (potential) difference. There are positive sodium and potassium ions outside the

outside creating a voltage (potential) difference. There are positive sodium and potassium ions outside the 
neuron and the cell is negative inside. As we discussed earlier, a resting balance −ve 70 mv is maintained by 
channels in the neuron cell membrane that allows Na
+ and K+ to move in and out of the neuron to maintain 
this resting balance. Finally, the channels maintain the negative potential difference inside due to the fact 
that these channels are less permeable to Na
+ flowing in and more permeable to K+ flowing out. 
When signals propagate along neurons, Na + ions flow in channels into the neuron membrane, cre­
ating a current, and over distances in the neuron, these Na + ions dissipate (called electrotonic spread, 
meaning the concentration per unit area is less; voltage-gated channels open up further down the neu­
ron to add more Na
+ ions in to propagate the signal [Figure 7.21]). 
Definition:

Electrotonic spread . A change in membrane potential (e.g., a receptor potential or synaptic potential) 
originating in one region of a cell (Δ V0) is associated with local transmembrane currents that distrib­
ute and flow intracellularly and extracellularly to adjacent membrane regions (at distance d), where 
they in turn cause changes in membrane potential (Δ V(d)). However, the underlying currents get 
progressively smaller with distance because fractions of them are diverted through transmembrane 
ion leak channels. Thereby, the elicited adjacent membrane potential changes (Δ V(d)) are reduced 
in size and altered in shape (electrotonic decrement), http://www.springerreference.com/docs/html / 
chapterdbid/116505.html.

185 Medical Sensors 
Outside +ve the signalNa+
 
channel
 
Na+ Na+ 
Na+Na+Na+ Na+ Na+ Na+ 
Na+ 
Na+ Na+ 
Voltage gated Na+ 
channel opens to allow in
more Na+ to propagate
Na+ 
Electrotonic spread 
(charge dissipates) 
Outside +ve 
K+ K+ 
K+ 
Channel 
©Lubliner 2013 
Na+ 
Na+ 
Na+Na+Na+ Na+ 
Na+Na+ 
Na+ 
Neuron membrane 
Inside neuron –ve 
Na+ 
Na+Na+ 
K+ 
FIGURE 7 .21  Electrotonic spread: charge dissipates over the length of the neuron so additional voltage-gated 
channels open up to allow in more Na + ions to propagate the signal. 
Level II: Wireless Medical Monitoring 
7.4 Wireless Medical Devices
 
Wireless medical devices are defined as “any medical monitoring technology, worn or implanted, that gather 
physiological information [14].” These devices can contain local data storage for subsequent download or to 
transmit data in real time via various wireless technologies such as Bluetooth or protected wireless spectrums

transmit data in real time via various wireless technologies such as Bluetooth or protected wireless spectrums 
designated by the Federal Communications Commission (FCC) as indicated by 802.11b specifications. 
These sensors are classified as either stand-alone devices or integrated in a sensor network where all 
devices share a common microprocessor controller that sends information as an integrated package. Both 
hospitals and individuals now currently utilize these devices. Research has indicated that these real-time 
data have reduced follow-up admissions. A new field is emerging where BSNs, an integrated suite of 
mobile medical monitors, are often integrated into clothing that can be a significant aid to prevent more 
serious conditions. 
As wireless medical devices or body sensor webs become common, large real-time data streams 
from millions of devices are creating a new challenge in real-time data mining/big data, defined as

from millions of devices are creating a new challenge in real-time data mining/big data, defined as 
extremely large data sets [11]. To analyze this data in near real time, or to respond to possible life-
threatening conditions in a timely matter by locally intelligent processing, tablet or PC, can display 
trends in an easily decipherable format. Filtering this data at the transmission source to transmit 
just summary information; and any anomalous readings; i.e., high blood pressure or high glucose 
levels, can be used to reduce large data sets to manageable levels. Life expectancy has doubled in the 
last 100 years; the potential to match this rate of improvement utilizing real-time wireless sensors 
integrated with smart devices/phones has the potential to be transformational. 
7 .4.1 Bluetooth Wireless Communications 
Bluetooth is one of the most accepted international wireless standards for wireless medical devices. It’s

Bluetooth is one of the most accepted international wireless standards for wireless medical devices. It’s 
characterized at short range and recently in low-power variants with well-defined security protocols. It 
also contains specifications for personal area networks, piconets, of up to eight integrated devices.

ECG sensor 
node 
io-feedback 
Artificial 
pancreas 
EMG 
sensor node 
ECG and 
Blood pressure Tit sensor 
B
SpO2 and 
ZigBee lotion sensor 
Body
 
area Personal
 
Pulse oximetry network server
 
sensor node
 
Motion 
sensors 
Inertial
 
Network coordinator and
 
temperature/
humidity sensor
 
186 Biomedical Informatics 
There is an international organization/special interest working group (SIG) ( https://www. 
bluetooth.org/apps/content/) that includes representatives from most medical equipment manu­
facturers and publishes standards and holds regular seminars. The group also certifies testing 
laboratories to ensure Bluetooth standards meet local regulations. Health Level 7, another inter­
national working group (www.HL7.org ) that establishes electronic medical record (EMR) stan­
dards, closely works with this and other standards organizations such as the Health Information

dards, closely works with this and other standards organizations such as the Health Information 
M a n a g e m e n t  S y s t e m s  S e c u r i t y  ( H I M S S ) .  H I M S S  “ f o c u s e d  o n  p r o v i d i n g  g l o b a l  l e a d e r s h i p  f o r 
the optimal use of information technology (IT) and management systems for the betterment of 
healthcare” (www.HIMSS.org). 
7.4.2 Body Sensor Networks 
A BSN (Figure 7.22) is a series of medical devices, either external or implanted, worn by patients. 
The concept is linking a series of devices, using Bluetooth, short-range communications with a com­
puter or smart device into an integrated packaged signal. Bluetooth IEEE 802.15.4 standard up to 
this point has been a relatively inefficient system with higher transmission power required for com­
munications. A new low-power Bluetooth called Wibree may provide longer battery life for these 
BSNs [10].

BSNs [10]. 
There are a number of standards for this evolving field to standardize these integrated systems: 
• 	 ISO/IEEE 11073: Low-level data standards for plug-and-play devices integrated into these BSNs 
that can contain a maximum of 10 connected devices. 
• 	 The Integrate Health Environment : Is a joint effort by multiple medical sensor vendors to stan­
dardize interoperability between sensors and device interfaces. They are associated with HIMSS 
and the American College of Clinical Engineering. 
FIGURE 7 .22 BSNs. (Images from Robust Low Power VLSI Group; http://rlpvlsi.ece.virginia.edu/category/ 
projects/body-sensor-networks.)

Smart phones, tablets 
technology 
EMR 
database 
Intelligence
created in 
the Cloud 
Cloud 
Wireless 
Internet 
Physical
Dedicated 
monitoring
devices 
Structured 
Management 
system;
patient,
medication, 
material flow 
Nonstructured 
Wireless 
disjoint by
various agencies
and responders 
Monitoring
independent
devices 
connected 
Triage facilities;
various emergency
responders 
mediated 
Wireless Medical Monitoring Lubliner 2012 
devices 
independent;
Smart phones,
Tablets 
integrated by
Apps 
Devices could 
be parachuted
into 
emergency
situations with 
pre-installed
Apps 
Loosely – Structured 
 
187 Medical Sensors 
7.4.3 Wireless Medical Device Protected Spectrum 
In May 2012, the FCC set aside part of the spectrum, 2,360 to 2,400 MHz, for use by low-power medi­
cal devices. The term for these low-power medical networks, typically used in hospital environments,

cal devices. The term for these low-power medical networks, typically used in hospital environments, 
is medical body area networks. This spectrum was selected to prevent interference from Wi-Fi devices. 
Initially, this spectrum will be used by medical device manufacturers in relatively structured environ­
ments but will evolve for all wireless medical devices. 
7 .4.4 Integrated Data Capture Modeling for Wireless Medical Devices 
There are sea changes evolving in structured, fixed medical facilities and nonstructured private emer­
gency care delivery and loosely structured technology–mediated monitoring (Figure 7.23). This includes 
transport, ambulances, triage environments, disaster, and military and personal healthcare. This new 
model involves integrating multiple data sources into EMRs, personal data records, and continuity of 
care records and providing intelligent software to correlate data.

care records and providing intelligent software to correlate data. 
In structured environments, the need to correlate patient data, common physiological monitoring 
parameters, blood pressure, heart rate, pulse oximetry, blood gases, etc., requires integration into a larger 
data repository, EMRs that include medications, lab tests, MRI/CT scans, and feedback from medical 
practitioners. Expert systems [5] are evolving to manage and report on potential adverse scenarios. 
In nonstructured environments, a disaster scenario involves a number of patients (N) with various 
levels of acuity and the need to coordinate response and transport based on acuity triage models. This 
can be divided into several subcategories: professional, trained personnel entering the environment, 
FEMA, Red Cross, or city or federal services; volunteers, local respondents responding to assist family 
or neighbors; and possible automated devices, either dropped in methods to utilize the large base of

or neighbors; and possible automated devices, either dropped in methods to utilize the large base of 
wireless smart cell devices. 
FIGURE 7 .23 Structured, nonstructured, and loosely structured medical monitoring.

0
1
2
3
4
5
6
7 
correlation to existing data 0 
Quary engine Knowledge
Age Symptom 1 62% 
Sex Symptom 2 base 75% 
History Symptom 3 rules and 
data 5 6 
N1 2 3 4
 
7
 8 
system versus diagnosis 
clinical data Mg++ K+ 
 
188 Biomedical Informatics 
This typically involves personnel finding and deploying monitoring equipment. Since wireless devices 
are relatively short range, some temporary wireless network/monitoring structure need to be linked into 
longer-range systems for coordination, point-to-point versus wide-area response. GPS and establishing 
patient ID also augment these systems. 
Level III: Advanced Data Analysis 
7.5 Expert Systems: Utilized to Evaluate Medical Data
 
“Expert Systems are computerized applications that combine computer hardware, software and specialized

“Expert Systems are computerized applications that combine computer hardware, software and specialized 
information to imitate expert human reasoning and advice” [4]. The core components of an expert system are 
a knowledge base, composed of rules and facts, and an inference engine, supplied with data from a user, that 
selects the appropriate rules based on the data and calculates probabilities that the rules apply to a particular 
situation. An additional component is feedback from clinical data that cross checks the validity of the rule/ 
diagnosis that then adds to the refinement of the expert system knowledge base (Figure 7.24). 
are then generated, i.e., an example of a system used for determining heart arrhythmias states to the

mias. The system asks the individual to enter potassium and magnesium results from blood tests to 
validate or refute the hypothesis. This type of feedback mechanism provides more accurate diagnosis 
where additional data increase the probability of an accurate diagnosis. This is an example of a rule-
based expert system. 
Inference engines determine which rules match those of the supplied data and match those with 
the highest probabilities. There are forward-chaining inference (FCI) engines that analyze the facts to 
some conclusion or disease. These systems are used to predict outcomes; an example of an FCI system

some conclusion or disease. These systems are used to predict outcomes; an example of an FCI system 
is E-mycin, written in lisp, which was used to identify bacteria causing infections developed at Stanford 
University [7]. It provided a 69% success rate, which was higher than practitioners at the time. A back­
ward-chaining inference engine is from hypothesis to the facts used primarily for diagnosis; an example 
is the knowledge engineering environment. 
Other paradigms for medical expert systems are case-based reasoning (CBR), cognitive systems, and 
crowd-based expert systems. The CBR utilizes an evolving library of cases where matches are made to 
FIGURE 7 .24 Expert system architecture.

189 Medical Sensors 
the current case, rather than utilizing a standard rule-based engine; this is similar to the process of how 
doctors make a diagnosis. The process involves these three steps: retrieve similar cases, reuse the case 
to solve similar problems, revise and modify the case, and retain the new case with updates for the case 
library (4Rs). 
Cognitive systems [13]  are a series of artificial intelligence paradigms with “the ability to engage in 
abstract thought that goes beyond immediate perceptions and actions.” Originally, comprehensive arti­
ficial intelligence systems attempted to model human consciousness but due to their lack of success were 
modified for a more narrow expertise in specific domains of knowledge. Examples are chess programs 
that are the equal of the best master level chess players. Cognitive systems utilize structured representa­
tions and probabilistic models to support problem solving utilizing concepts from psychology, logic, 
and linguistics.

and linguistics. 
Crowd source, wisdom of the crowds, provides a new method to extract large amounts of relevant 
from the web. An example is IBM’s “Watson,” famous for beating experts on the Jeopardy game show, 
This crowd source–based approach has shown some success on social networking sites, where specific 
diseases are targeted and individuals supply anecdotal data. 
7.6 Data Mining and Big Data in Healthcare 
Data mining can be defined as the process of finding previously unknown patterns and trends in data­
bases and using that information to build predictive models. In healthcare, data mining focuses on

bases and using that information to build predictive models. In healthcare, data mining focuses on 
detailed questions and outcomes. What symptoms, quantitative data, and clinical outcomes in combi­
nation lead to specific diagnosis and treatments. As discussed in the previous expert systems section, a 
combination of probabilistic and human-directed diagnosis evolves into an evolving knowledge base. 
This works well with a finite data set but with big data defined as “a collection of data sets so large and 
complex that it becomes difficult to process using on-hand database management tools [12]. ” Imagine 
millions of individuals with real-time wearable or implanted medical sensors sending data through 
Smart phones. The data stream would certainly be in the terabyte range, but as these devices became 
ubiquitous, petabyte levels of data are not unreasonable. Information can be summarized and evaluated

ubiquitous, petabyte levels of data are not unreasonable. Information can be summarized and evaluated 
locally on ever-evolving Smart phones, but additional analysis and correlation, on a regional or global 
level, would require new stochastic techniques, i.e., algorithms to analyze random events. This seems 
like a contradiction in terms. Markov chains, random events, quantified as a time series events or lim­
ited by a field space, or a finite geographical area or subpopulation can provide a deterministic function 
used to correlate or classify seemingly random events. Examples are plumes of breast cancer patients 
that appear to be random but with large enough data sets can create correlations, i.e., the butterfly effect, 
the concept that a butterfly flapping its wings in on one area can create small finite effects over larger 
distances. Tracking the cause back to that original butterfly or a random mutation of flu virus anywhere

distances. Tracking the cause back to that original butterfly or a random mutation of flu virus anywhere 
in the world could predict and prevent epidemics. 
7.6.1 Body Sensor Network Research and Big Data 
Big data is usually defined as “data sets with sizes beyond the ability of common software tools to cap­
ture, curate and process within a tolerable elapsed time” [16]. Data sizes range from terabytes ( 10
12) to 
petabytes (1015). 
Another looming big data challenge is the real-time processing and analysis of BSN data. As mil­
lions of individuals begin to use mobile health monitoring equipment, external and implanted sensors, 
it’s estimated that, at the minimum, terabytes ( 10
12) and at the high-end petabytes ( 1015) of data will be 
generated daily [3].

1.  D evelop a methodology to categorize structured versus nonstructured wireless medical data. 
 2. Analyze data streams from various mobile devices. 
 3.  Determine optimum frequency of data capture. 
 4. Develop algorithms/expert systems to extract critical data. 
 5. Develop software to provide both detailed and event-oriented visualization. 
 6. Determine efficiencies of raw data versus compressed data streams on overall traffic. 
Phase II: Clinical Trials 
 7. Compare wireless medical devices/BSN raw data versus compressed data traffic. 
 8. Analyze outcomes of compressed data versus raw data. 
7 .6.1.2.3 Testing Methodology 
Three environments/frameworks were utilized for integrating wireless data. 
Structured: Used in conventional hospital settings 
 1.  Nonstructured worn as mobile devices at home/work 
 2. Loosely structured, technology mediated; fires, hurricanes, disaster scenarios, etc., where fixed 
and personal devices are integrated to create dynamic ad hoc networks

and personal devices are integrated to create dynamic ad hoc networks 
190 Biomedical Informatics 
7.6.1.1 Body Sensor Network Research 
A research project at New Jersey Institute of Technology is currently under way to reduce the data 
generated by BSNs by a factor of 1,000 by preprocessing the information into summaries that just high­
light anomalies. For example, if your blood pressure stays consistent 20 hours of the day, rather than 
transmitting all the individual data points, a brief summary describing the range and duration and the 
anomalies outside of this range is forwarded to a medical practitioner. 
7.6.1.2 Case Study: Body Sensor Network Research, Mining Large Data Set 
Title: Body Sensor Networks and Big Data Algorithms to Reduce Real Time Data Streams from Petabytes 
to Gigabytes (Lubliner, D., Endo, T., and Gregoriev, E.) 
This research explores algorithms, data compression techniques, and sociological cues that narrow

This research explores algorithms, data compression techniques, and sociological cues that narrow 
the scale of raw data transmissions and provides techniques to categorize and summarize root cause 
medical triggers, i.e., physiological events that indicate the precursors of more serious life-threatening 
medical conditions. 
7 .6.1.2.1 Introduction 
The medical challenge of the twenty-first century is to exploit the evolving field of wireless medical 
sensors to proactively treat medical conditions reducing emergency room visits and treating chronic 
diseases before they become acute, significantly reducing healthcare costs. The evolving field of body 
sensor networks (BSNs) provides a framework to integrate external and internal sensors into a single 
coherent data stream. The challenge with the ubiquitous use of BSNs is to reduce the scope of daily data 
streams, estimated in the petabyte (PB) 10
15 range, which could double current wireless data traffic over­

whelming our wireless data infrastructure. 
A BSN is a series of medical devices, either external or implanted, worn by patients linked together to 
form a coherent picture of an individual’s medical state. BSNs link a series of devices, using Bluetooth 
or short-range RF communications with a computer or smart device into an integrated packaged signal. 
In this research project, creating an integrated network of external and implantable sensors was 
solved by utilizing Bluetooth and a software application embedded into a Smart phone. These raw data 
were then sent to a central server for processing and analysis (Figure 7.25). 
7.6 . 1 . 2 . 2  R e s e a r c h M e t h o d o l o g y 
Phase I:

Blood that can contain a maximum of ten connected 
pressure devices. 
Wireless 
Glucose transmission as a hub to aggregate and
implantable process wireless data 
Pedometer
 
with GPS
 
Compressed data stream 101010 (reduces data forPulse oximeter an estimated patients population of 107) from
 
191 Medical Sensors

191 Medical Sensors 
FIGURE 7 .25  (See color insert.)  Case study: BSN data capture integrated into a Smart phone and then forwarded 
to Cloud storage. 
The testing methodology varied significantly depending on the environment. In a well-structured 
hospital environment, all environmental factors were controlled: diet, controlled stimulus (i.e., no unex­
pected stress), and nursing reports to fill in any other factors that might influence wireless data readings. 
In a nonstructured environment, individuals wearing sensors at home or work, the research relied on 
an application embedded on their Smart phones for individual to record events, diet, etc., to provide 
context to the data. Sociological data are a key to provide context to the medical readings. 
7 .6.1.2.4 Data Analysis 
Wireless medical data were recorded from two out of the three environments, i.e., (1) structured and (2)

Wireless medical data were recorded from two out of the three environments, i.e., (1) structured and (2) 
nonstructured environments. (3) Loosely structured, i.e., analyzing wireless medical sensors in a disas­
ter, will be explored in future research. The chart as shown in Figure 7.26 is an example of wireless blood 
pressure data captured from 62 individuals, where suspect readings were flagged and plotted to provide 
a graphic display to practitioners. Working with medical staff at a local hospital, they indicated that they 
were interested in a visual presentation of the data that quickly indicate steady-state readings, i.e., consis­
tent values, and those anomalies that diverged from the norm. We both presented a graphic representa­
tion where values exceeded some threshold, diastolic above 80 in the graph for a number of patients. Then 
if they wanted to delve deeper, a table would show precise readings, again highlighting anomalies in red.

if they wanted to delve deeper, a table would show precise readings, again highlighting anomalies in red. 
7 .6.1.2.5 Results 
By aggregating data, i.e., summarized events that remained stable over periods of time, and flagged 
anomalies that appeared outside of normal measurement ranges, values highlighted in red (Figure 7.27), 
we were able to reduce a patient’s daily data into a concise summary. An example is a patient’s systolic/ 
diastolic for 10/24/12 that was in the range of 131–121/85–93 and providing a graph. Individual anomalies 
were removed from the report if they didn’t persist for several sequential reading but were available in a

Data Sets 
Patient
1000 
10/1/13
91/131 123 
92 
127 
89/128
78/110
74/107
79/114
80/119
73/115
77/117
73/109
79/118 75/114
72/110
74/111
79/118
77/115
78/119 75/118
78/120
78/120
78/120
78/120
78/120 
75/112
77/115 78/120 72/112
77/118 79/115
79/118 72/109
70/110
73/114
72/109
72/109
72/109
72/109
72/109 
74/116
78/117
79/118
79/118
79/118
79/118
79 
77/117 2/33
0/0
1/16
0/0
0/0
0/0
0/0
0/0
1/16
Transmitted10/60 16%
6/100 
78/11979/ 
75/118
77/113
72/112
72/112
72/112
72/112
72/112 
1118 
91/131 92/135 94/138 94/137 94/141
10/2/13 10/3/13 10/4/13 10/5/13 10/6/13
1001
1002
1003
1004
1005
1006
1007
1008
1009 
Systolic/Diastolic Low/High
Readings(%) 
Sample Blood Pressure Data, where suspect reading flagged
and plotted to provide a graphic display to practitioners 
Linear regression model: this method minimizes the sum of
squared vertical distances between the observed responses in
the dataset and the responses predicted by the linear approximation.
100
 Series 1
80
 Series 2
Series 360

100
 Series 1
80
 Series 2
Series 360
Series 4
40
 Series 5
20
 Series 6 
Series 50 Series 31 2 3 4 5 Series 1 6 7 8 9 10 
Data consist of n observtions {yi, xi}n i = 1. Each observation includes a
scalar response yi and a vector of p predictors (or regressors)xi . In a linear
regression model, the response variable is a linear function of the regressors:
yi =xrβ + ci , where B is a vector of unknown parameters and x are scalar variables.i 
 
192 
FIGURE 7 .26 Case study: data generated with red indicating anomalies in readings. 

1 2 3 4 
120 
BP Reduced to 
approximately 100
bytes per message 
100 
Systole 
80 
4K bytes per 
message 
Mean 60 (Min/Max critical
points where data
exceeded norms are 
transmitted) 
40 
Diastole 0 2 4 6 8 10 1 5 10 15 20 0 0.5 1.0 1.5 2.0 
Time (ms) Time (s)	 Time (s) 
 
193 Medical Sensors 
FIGURE 7 .27  Case study diagram: data analyzed and compressed to transmit summary and anomalies. 
tabular form from the Cloud server if requested. Individual anomalies were determined to most likely 
due to shifting of sensors. The devices were able to take additional readings when anomalies occurred 
to validate if they were caused by sensor movement during some activity. In addition, an audible signal 
on the Smart phone asked the patient, during the anomaly, to describe his or her activity at that point in 
time in a brief drop-down list of choices that were easy to analyze and annotate on the patient’s records. 
7 .
6.1.2.6 Data Analysis (Figure 7 .27) 
 1. Blood pressure absolute.

7 .
 1. Blood pressure absolute. 
 2. Blood pressure changes in order to detect hemodynamic instabilities. 
 3. Physiological rhythms that deliver insight into the hemodynamic control function and/or fluid 
management. 
 4. Further pulse wave analysis provides additional cardiovascular parameters. 
 5.  Results in data transmission reduction to 2.5% of original data stream . 
By aggregating data in a single integrated record that summarizes information into a continuity of 
care record, essential information can be transmitted without loss of critical medical information. The 
reduction in data transmitted is about 1/100 the original size. Extrapolated over millions of patients 
simultaneously wearing BSN daily, transmitted data would be reduced from petabytes to terabytes in a 
population of 1 million. We believe this can be further reduced by transmitting delta information, i.e.,

population of 1 million. We believe this can be further reduced by transmitting delta information, i.e., 
comparing previous daily readings to current values and just transmitting delta changes over a period of 
time, i.e., blood pressure increases 3% over a 30-day period. That may be the only information a medical 
practitioner may need. 
7.6.2  	Future Directions: Mining Large Data Sets: 
NSF and NIH Research Initiatives 
The following section describes initiatives underway to analyze the growing field of big data including 
ini tia tiv e un derwa y b y th e N a ti o nal Sci en ce F o un da ti o n (N S F ) , N a ti o nal Insti tu tes o f H eal th (NIH ) ,  
and Department of Defense (DOD) to provide significant research funds to enhance analysis of medical

194 Biomedical Informatics 
data, geological, and defense research. The hope is that these new methodologies may be extrapolated 
to other disciplines. NSF and NIH research is often a predictive indicator for future medical innova­
tions, similar to previous Defense Advanced Research Projects Agency (DARPA) investments that were 
responsible for many of today’s internet and computer advancements [1]. 
This field of big data is the focus of support by several U.S. research agencies, NSF, DOD, and NIH 
committing $200 million in 2012 to this “Big Data Initiative.” 
To gain an understanding of these initiatives, the following was a solicitation on an NSF page to 
researchers to submit big data research grant proposals [8]. 
The Obama Administration announced a “Big Data Research and Development Initiative.” By 
improving our ability to extract knowledge and insights from large and complex collections of

improving our ability to extract knowledge and insights from large and complex collections of 
digital data, the initiative promises to help solve some the nation’s most pressing challenges. 
To launch the initiative, six Federal departments and agencies today, March 29th, 2012  
announced more than $200 million in new commitments that, together, promise to greatly  
improve the tools and techniques needed to access, organize, and glean discoveries from huge  
volumes of digital data. 
The NIH also has dedicated significant funds to the analysis of larger data sets, specifically focused on  
genomic research. The NIH announced in 2012 that the world’s largest set of data on human genetic 
variation, produced by the International 1000 Genomes Project, was available on the Amazon Web 
Services (AWS) Cloud. Two hundred terabytes is the equivalent of 16 million file cabinets filled with text.

Services (AWS) Cloud. Two hundred terabytes is the equivalent of 16 million file cabinets filled with text. 
The source of the data, the 1000 Genomes Project data set, is a prime example of big data where data sets  
become so massive that few researchers have the computing power to make the best use of them. AWS 
is storing the 1000 Genomes Project as a publicly available data set for free and researchers will only pay 
for the computing services that they use. 
Large data sets are also currently being generated by researchers in other fields, which are the focus 
of a number of research initiatives: 
• 	 “EarthCube”—a system that will allow geoscientists to access, analyze, and share information 
about our planet. 
• 	 The DARPA is an XDATA program, established to develop computational techniques and soft­
ware tools for analyzing large volumes of data, both semistructured (e.g., tabular, relational, cat­

egorical, metadata) and unstructured (e.g., text documents, message traffic). Also to harness and 
utilize massive data in new ways and bring together sensing, perception, and decision support to 
make truly autonomous systems that can maneuver and make decisions on their own. 
• 	 A project that will integrate three powerful approaches for turning data into information— 
machine learning, Cloud computing, and crowd sourcing. 
• 	 The Smart Health and Wellbeing program of the NSF whose goal is the “transformation of health-
care from reactive and hospital-centered to preventive, proactive, evidence-based, person-cen­
tered and focused on wellbeing rather than disease.” The categories of this effort include wireless 
medical sensors, networking, machine learning, and integrating social and economic issues that 
affect medical outcomes.

affect medical outcomes. 
The following is a representative funded research grant in the field of wireless medical devices. These of 
bleeding edge research initials have the potential to shape advancements in medical data mining. This 
research proposal was selected by experts in the field assembled at the NSF. 
“NSF award to utilize Wireless Medical Sensors to Manage and Proactively Treat Chronic Illnesses . 
Forty percent of all medical costs are associated with treating patients with chronic illnesses in the last 
two years of their lives.”

10K 
100K 
1M 
10M 
100M 
1G 
10G 
100G 
1T 
10T 
100T 
100 
Wireless Medical Data Transmission rates Lubliner 2012 
1K 10,000 100,000 1M 10M 100M 
monitored 
1M per person 
100K per person 
1K per person 
Data transmission rates for wireless medical devices Data transmitted/per day 
10 
 
195 Medical Sensors 
Telemedicine technologies offer the opportunity to frequently monitor patients’ health and opti­
mize management of chronic illnesses. Given the diversity of home telemedicine technologies, it 
is essential to compose heterogeneous telemedicine components and systems for a much larger 
patient population. The objective of this research is to thoroughly investigate the heterogeneity 
in large-scale telemedicine systems for cardiology patients. To accomplish this task, this research 
seeks to develop (i) a novel open source platform medical device interface adapter that can seam­

lessly interconnect medical devices that conform to interoperability standards, such as IEEE 11703, 
to Smart phones for real-time data processing and delivery; (ii) a set of novel supporting technolo­
gies for wireless networking, data storage, and data integrity checking, and (iii) a learning-based 
early warning system that adaptively changes patient and disease models based on medical device 
readings and context. 
The challenge of the aforementioned grant is to not just collect data but to build in sociological com­
ponents, stress, economic conditions, etc., that might generate transient results and to proactively treat 
patients with early conditions thus reducing costly hospital stays and increasing their quality of life. 
Results from previous studies have shown that filtering out unusual readings may result in more reliable

Results from previous studies have shown that filtering out unusual readings may result in more reliable 
data. Also integrating smoking, drinking, etc., helps quantify the results. So apps allow users to input 
data regarding their frame of mind or habits; while the data are being monitored on the wireless medical 
devices, we can provide invaluable information for analysis of causal effects to physiological readings 
(Figure. 7.28). 
Assuming wireless mobile medical devices become common, estimates of data generated daily, with 
only a million users, range from 1 terabyte to 1 petabyte/day (Figure 7.28). To put this in perspective, the 
FIGURE 7 .28 Smart health data transmission projections as wireless medical sensors become commonplace.

1.  Neurons and nervous system
 2.  Brain
 3. Spinal chord
 4. Muscles
 5.  Heart
 6.  Eye 
Neurons and the Central Nervous System  (See color insert.) 
types of cells, Neurons and Glia. They are responsible for Dendrites Microtubule Synapse 
transmitting information. Neurons make up our brains, Neurofibrils Synaptic vesicles 
information processing system, and communicate signals Neurotransmitter Synapse (Axoaxonic) 
throughout our body. (movement, sensory and healing). Receptor Synaptic cleft 
Neurons are electrically excitable cells that Rough ER Axonal terminal 
communicate information through electrical and (Nissl body) 
chemical signals. Neurons are connected via synapses, a Polyribosomes Node of ranvier 
gap between neurons, that allows a neuron to pass an Ribosomes Synapse Synapse (gap
electrical or chemical signal to another neuron. (refer to: Golgi apparatus (Axosomatic) between neurons)

electrical or chemical signal to another neuron. (refer to: Golgi apparatus (Axosomatic) between neurons) 
  Sodium(Na+)–Potassium(K+)
pumps move positive ions Synapse Axon hillock Myelin Sheath
(Na+ and K+) across the synapse Nucleus (Insulation) 
to make one side more positive Nucleolus Nucleus 
(voltage / potential difference) Membrane (Schwann cell) 
+ Microtubule 
so current flows (electrons) K
from negative to positive. Mitochondrion 
+ Na Smooth ER Glial cells surround the Microfilament 
neurons and provide support Result –VE +VE voltage Microtubule 
and insulation between neurons Synapse
(composed of Schwann, microglia, Dendrites Axon 
astrocytes, satellite and ependymal cells). 
Dendrites: Are thin protrusions from the cell body of a neuron that collect chemical
conducts electrical impulses away from the cell body to the axon terminals

196 Biomedical Informatics 
digital storage for the Library of Congress is 200 terabytes. The population in 2012 is 300 million in the 
United States and 7 billion worldwide, and 50% of Americans have some type of Smart phone or tablet. 
In the next 25 years, 20% of the U.S. population will be over 65 making either wearable smart medical 
devices or those abilities directly embedded in smart devices are likely to expand rapidly. This flood of 
potential data dwarfs all other applications. Data mining of this treasure trove of medical data will be 
the challenge of the ensuing decades to come. 
This last section, segmented into four parts, is a basic Anatomy & Physiology (A&P) Primer geared 
toward the BMI practitioner. BMI professionals should be encouraged to take A&P I and II courses, but

toward the BMI practitioner. BMI professionals should be encouraged to take A&P I and II courses, but 
if they haven’t, this section is presented in a format that can be easily used in PowerPoint presentations.
* 
7.7  	Part I: Neurons and Nervous System, Brain, 
Spinal Cord, Muscles, Heart, Eye 
Human physiology I 
* Illustrations taken from Creative Commons A&P resources.

197 Medical Sensors 
Brain (See color insert.) 
The Cerebrum, it’s the evolved part of the brain, the largest part of the Cerebral Cortex Left brain Right brain 
human brain, which comprises 4/5 of its weight. It consists of about two- Analytical thought Creativity
thirds of the brain mass and lies over and around most of the structures of language Art and Music 
the brain. The outer portion ranges in thickness between 1.5 and 5 mm, Frontal lobe Parietal lobe and is covered by a thin layer of gray tissue called the cerebral cortex. It is
divided into right and left hemispheres Occipital
that are connected by the corpus callosum. lobe Temporal lobe 
Cerebrum includes the hippocampus, olfactory bulb and basal ganglia
 
 Cerebellum          short-term to long-term memory
 Brainstem (Older part brain) -Limbic System: emotion, behavior long term memory
 en.Wikipedia: public domain 
-Olfactory bulb: sense of smell

Brainstem (Older part brain) -Limbic System: emotion, behavior long term memory
 Olfactory bulb 
-Basal Ganglia: voluntary movements, learning, eye movements, emotion
 
surface is embedded groves (valleys) called the “sulci” . The ridges are called
“gyri” . 
Hippocampus Basal ganglia (purple) Temporal lobe: hearing and comprehending speech 
Occipital lobe: visual processing center © Lubliner 2015 Motor  cortex 
Major internal parts of the Human Brain Premotor Primary motor cortex 
The Cerebellum involved in motor control. The functions include balance, Cingulate cortex Primary somatosensory
voluntary movements, motor learning, and some congnitive functions Sulcus SMA cortex Posterior Corpus

(language); (10% volume, but contains 50% of neurons brain. parietalCallosum cortex 
Diencephalon 
Anterior 
The Brain Stem includes the midbrain, Pons Mid Brain Commissure 
Temporaland medulla oblongata. Functions include the Pons Lobe 
cardiac, respiratory and autonomic (involuntary Midbrain 
Pons The Motor Cortex 
functions), blood pressure and heart rate. Medulla Cerebellum involved in control of  
Medulla voluntary actions 
Brain (cont.)
 
Motor cortex is the region of
 Motor cortex 
the cerebral cortex involved in
 Premotor Primary motor cortex the planning, control, and
 cortex Primary Somatosensory execution of voluntary
 SMA cortex movements
 Posterior 
Primary motor
 parietal 
cortex generates neural
 cortex 
impulses sent to the spinal cord
that control the execution of
 The motor 
movement
 areas are located 
The supplementary motor
 in both 
area (SMA), involved in the

 The motor 
movement
 in both 
 hemispheres
planning of movement, planning
 The right half
controls the left 
of sequences of movement, and
 side and left half 
the coordination of the two sides
 the right side 
of the body

Spinal chord 
The Vertebral column is divided into the cervical, thoracic, and lumbar regions. The spinal nerves that branch out
are called Lower Motor neurons. They exit at each vertebral level and contain sensory and motor segments. 
Posterior 
nerve roots 
Posterior roots 
Posterior 
roots 
Posterior 
roots 
Anterior Divisions of spinenerve roots 
C1 C2 
C3 C4Ligamentum C5
 
enticulatum dura
 C6
 
C7
 
Anterior roots C8
 
T1
 
Spinal nerve in T2
 
T3
its sheath T4 
T5
 
T6
 
Anterior roots
 T7 
T8 
T9 
T10 
T11 
T12 
Ligamentum
L1denticulatum L2 L3
Anterior roots L4 
L5 
S1 
S2 
S3
Spinal nerve in S4 
S5
its sheath 
Overhead (axial)view 
Transverse costal facet Costal facet 
(costovertebral
joint) 
Superior articular
Process and facet 
Superior  costal facet 
Spinous process 
Costotransverse facet 
(costovertebral joint) 
The thoracic nerves are divided into 
anterior and posterior branches called the
dorsal ramus and ventral ramus. They connect to

upper body deep tissue and skin and
muscles. 
The vertebra are stronger than the cervical
bones, which allows them to absorb greater
force on the mid back and prevent injury. 
http://en.wikipedia.org/wiki/Thoracic_vertebrae 
Cervical nerves 
Head and neck 
diaphragm 
Deltoids 
wrist extender
 
Triceps
hands
 
Thoracic nerves 
Chest muscles 
Abdominal muscles 
Lumbar nerves 
Leg muscles 
Sacral nerves 
bowel 
Sexual function 
Body 
It is surrounded by
rings of bone called
vertebra. The eight
vertebra in the neck 
are referred to as 
Cervical nerves. The 
next twelve are 
Thoracic and control 
the chest and 
abdominal muscles. 
The Lumbar vertebra 
control the leg
muscles and Sacral 
nerves control the 
bowel and affect 
sexual function. 
Cervical vertebra C1–C7 
[and 8 cervical nerves (c1–c8)]
C1 is the suboccipital nerve.
They have the greatest range of

motion, of the vertebrae, so as to 
support the head and its movements 
Thoracic vertebra T1–T12
 
(attached to the thoracic
cage, they protect the organs
in the chest and have a more
 
limited range of motion).
The thoracic nerves T1 and T2
 
connect to the shoulder and
 
arms, T3, T4, T5, T6, connect to
 
the chest, the last five
 
connect to the chest and
 
abdomen.
 
198 Biomedical Informatics

Muscles 
Muscles perform four essential functions: They
maintain body posture, stabilize joints, produce
movement, and generate heat we need to survive.
This illustrates what different muscles do Fat cells 
and how muscles work together. 
Skeletal Muscles Muscle fibers 
Skeletal muscle, or striated muscle, is the type of
muscle you can see and feel. Learn about skeletal
muscle and its complex structure.
Skeletal muscle is also called striated muscle, 
because when it is viewed under polarized light or
Cross section of a skeletal muscle (200×) showing
the muscle fibers (red) and the fat cels (white) stained with an indicator, you can see alternating
striations. 
Cardiac and smooth muscles
Smooth muscle and cardiac muscle contract Relaxed smooth muscle cell involuntarily. While most of the processes are
similar, there are some notable differences between 
the actions of skeletal, cardiac, and smooth muscle. 
Contracted smooth muscle cell Skeletal muscle is a well-organized body tissue.

During muscle contractions, sections of muscle fiber
fit together like pieces of a puzzle. 
Heart 
The Right side of the heart collects
oxygen-poor blood from the body (veins)
and pumps it to the lungs where it picks
up oxygen and releases carbon dioxide. 
Brachiocephalic artery 
Left common 
carotid artery 
Left subclavian 
artery 
Aorta 
The Left side of the heart collects oxygen
rich blood from the lungs and pumps it to
the body (arteries) (the pulmonary veins [4] are 
one of the few veins that carry oxygen: from the 
lungs to the aorta). 
Superior vena cava 
Right pulmonary
arteries 
Right pulmonary veins 
Right atrium 
Left pulmonary
arteries 
veins 
Left atrium 
Semilunar valves 
Blood enters the heart through the Atria
(smaller chambers) which collect the blood and
pass it on to the ventricles. Its role is as a

holding chamber and pump. 
Atrioventriculer 
(tricuspid) valve 
Chordae tendineae 
Right ventricle 
(mitral) valve 
Left ventricle 
Septum 
The ventricles (larger chambers) pump
blood: Right ventricle to the lungs, left
ventricle to the Aorta. 
Inferior vena cava 
The valves are flaps of tissue that
prevent backward flow of blood (one way
transport) 
1. Mitral Valve 
2. Tricuspid Valve 
3. Aortic Valve 
4. Pulmonary Valve 
Atria ventricular 
(between upper atria and lower ventricles) 
Semi lunar valves 
(in the arteries leaving the heart) 
199 Medical Sensors

Heart (blood pressure) 
Systole is the period of contraction of the ventricles of the Pressure waveform (different from EKG which
is electrical) heart. In a single heartbeat Systole causes the ejection of
blood into the aorta (left) and lungs (right). During systole, Maximum aortic pressure following120 
arterial blood pressure reaches its peak, which is normally ejection is termed the systolic pressure 
about 90 – 120 mm of mercury in humans. 
The lowest pressure in the
Diastole is the relaxation of the heart muscle, aorta, which occurs just
accompanied by the filling of the chambers with blood. before the ventricle ejects
Initially both atria and ventricles are in diastole, and there is blood into the aorta, is 
a period of rapid filling of the ventricles followed by a brief termed the diastolic 80
atrial systole. At the same time, there is a corresponding Systole pressureDiastole decrease in arterial blood pressure to its minimum, normally

Systolic Diastolic about 80 mm of Mercury in humans. 
Normal less than 120 and less than 80Korotkoff sounds are the sounds that medical personnel
listen for when they are taking blood pressure using a non- Prehypertension 120–139 or 80–89 
invasive procedure. There are five Korotkoff only two are High Blood Pressure 140–159 or 90–99(Hypertension) Stage 1 primarily used for blood pressure: systolic (first) and High Blood Pressure
diastolic (fourth: within 10 mmHg above the diastolic blood (Hypertension) Stage 2 160 or higher or 100 or higher 
pressure). Some devices are also using the fifth. The other Hypertensive Crisis Higher than 180 or Higher than 110 
three used to detect heart disease. (As the cuff relaxes, and (Emergency care needed) 
blood flow returns to the arm. The first sound heard is the

blood flow returns to the arm. The first sound heard is the 
Korotkoff sound—indicates systolic pressure.) 
Heart (continued)
 
Electrical system:
 
A special group of cells that have the ability to
generate electrical activity on their own are
responsible for the heart beating.
 Aorta 
The natural pacemaker of the heart is called
Superior vena cavathe sinoatrial node (SA node). It is located in
the right atrium. The heart also contains
specialized fibers that conduct the electrical
1. SA node impulse from the pacemaker (SA node) to the
rest of the heart.
 
2. AV node 3. Bundle of His 
The electrical impulse leaves the SA node (1)
and travels to the right and left atria, causing 4. Right bundle 4. Left bundle
them to contract together. This takes 0.04 s.  branch branch 
There is now a natural delay to allow
the atria to contract and the ventricles to fill up 5. Purkinje

with blood. The electrical impulse has now  fibers 
traveled to the atrioventricular node (AV Inferior vena cava 
node) (2). The electrical impulse now goes to
Copyright 1999. Howstuffworks.com. Inc. the Bundle of His (3), then it divides into the
right and left bundle branches (4) where it
rapidly spreads using Purkinje fibers (5) to the
muscles of the right and left ventricle, causing
them to contract at the same time.
 
200 Biomedical Informatics

201 Medical Sensors 
Heart (continued) 
Although the pacemaker cells create the electrical impulse that causes the heart to beat,
other nerves can change the rate at which the pacemaker cells fire and how strongly
the heart contracts. These nerves are part of the autonomic nervous system. The
autonomic nervous system has two parts—The sympathetic nervous system and the
parasympathetic nervous system. The sympathetic nerves increase the heart rate and
increase the force of contraction. The parasympathetic nerves do the opposite. 
All this activity produces electrial waves we can measure. The measurement is typically
represented as a graph called an electrocardiogram (EKG). Here is an example of three
heartbeats from an EKG 
P wave 
Each part of the tracing has a lettered name: 
P wave: coincides with the spread of electrical activity over the atria and the beginning
of its contraction
 
QRS complex: coincides with the spread of electrical activity over the ventricles and

the beginning of its contraction.
T wave: coincides with the recovery phase of the ventricles. 
QRS complex T wave 
Arrhythmia 
• 	 An irregular heartbeat, or arrhythmia, can result from a change in the hea rt’s standard 
 ce
lls of the 
 stimulated. 
 to a disunity  
l fibrillation) 
 imminently 
 of the heart,  
e heart; it is  
, or V-fib) can 
mping of the 
ual suffering  
defibrillation 
 defibrillation 
ythm. It does  
he heart will  
 life as 
itants, or 
electrical conduction system. 
• 	 A s
erious variety of arrhythmia is known as fibrillation. The muscle
heart normally function together, creating a single contraction when
Fibrillation occurs when the heart muscle begins a quivering motion due
in contractile cell function. Fibrillation can affect the atrium (atria
or the ventricle (ventricular fibrillation); ventricular fibrillation is
life-threatening.

life-threatening. 
• 	 A trial fibrillation is the quivering, chaotic motion in the upper chambers
known as the atria. 
• 	 Ventricular fib rillation occurs in the ventricles (lower chambers) of th
always a medical emergency. If left untreated, ventricular fibrillation (VF
lead to death within minutes. When a heart goes into V-fib, effective pu
blood stops. V-fib is considered a form of cardiac arrest, and an individ
from it will not survive unless cardiopulmonary resuscitation (CPR) and 
are provided immediately. 
• 	 CPR can prolong the survival of the brian in the lack of a normal pulse, but
is the intervention which is most likely to restore a more healthy heart rh
this by applying an electric shock to the heart, after which sometimes t
revert to a rhythm that can once again pump blood. 
Almost every person goes into ventricular fibrillation in the last few minutes of

the heart muscle reacts to diminished oxygen or general blood flow, trauma, irr
depression of electrical impulses themselves from the brain.

Eye (See color insert.) Anatomy of Human Eye 
The Eye detects electromagnetic radiation (light) and	 Pupil Cornea
 
converts it into electro-chemical impulses in neurons.
 Iris 
Posterior chamber Anterior chamber 
fibres Lens Ciliary muscleLight enters through the cornea and passes through the Suspensory
pupil. The pupil is surrounded by the Iris, that controls Retina ligament 
the size and diameter of the pupil. Behind the pupil is Vitreous
 
the lens that focuses light onto the retina that has Sciera humour
 
photoreceptor cells.
 
Choroid 
Hyaloid
canal 
The Retina is a light sensitive layer of tissue made up Optic disc
made up of Rods which are used in peripheral vision, Optic nerve Fovea
 
and Cones, responsible for color vision.
 Retinal 

 Retinal 
process of reinventing the image is Focal pointa combination of brain architecture
 
and processing of the image. (It
 
starts at the optic nerve where there
is a crossing of axons in the optic
chiasm to the lateral geniculate
nucleus and then to the primary visual
 
cortex.)
 
202 Biomedical Informatics 
7.8  	Part II: Cells, ATP, Hearing, Kidneys, 
Pancreas, Liver, Digestive System
 1.  Cells
 a.  DNA
 b.  RNA
 c.  Proteins
 2.  ATP 
 a.  Photosynthesis
 3.  Hearing
 4.  Kidneys
 5.  Pancreas
 6.  Liver
 a.  Gallbladder
 7.  D i ge s t i ve  s y s t em

Cell 
Animal eukaryotic  cell DNA (Deoxyribonucleic acid) 
Cells are the basic functional unit of Hydrogen
living organisms. They are smallest unit Oxygen
that can replicate. Humans contain Nitrogen 
Carbonapproximately 100 trillion cells. Phosphorus 
Plants and animals are made up of 
eukaryote cells which contain 
compartmentalized areas, organelles,
where metabolic activities take place. 
T A 
The cell's nucleus contains its DNA, a 
blueprint which is organized as linear 
molecules of 23 pairs of chromosomes 
C Gthat carry all the information that help a 
cell grow, survive and reproduce.
RNA (Ribonucleic acid) is involved in 
coding, decoding and expression of 
Genome genes. It plays a role in catalyzing 
Cellbiological reactions. One of these is Chromosomes 
protein synthesis where mRNA directs genes 
Genes contain the assembly of ribosomes. instructions 
Proteins are required for the structure, for making
DNA proteinsfunction, and regulation of the body’s 
tissues and organs.

tissues and organs.  
Protein myoglobin 
ATP (adenosine triphosphate) 
Adenosine 5΄-triphosphate For your muscles—in fact, for every cell in your body—
the source of energy that keeps everything going is
 H2N 
called ATP . ATP is the biochemical way to store and use
 
energy. 
 N 
NO O OAdenosine 5΄-triphosphate (ATP) is a multifunctional
O– nucleotide that is most important as a “molecular P O P O P O N N 
currency” of intracellular energy transfer. In this role ATP O
– O– O– O 
transports chemical energy within cells for metabolism. 
OH OHIt is produced as an energy source during the
processes of photosynthesis and cellular respiration
 Chemical name 5-(6-aminopurin-9-yl)­and consumed by many enzymes and a multitude 3,4-dihydroxy-oxolan­of cellular processes including biosynthetic 2-yl methoxy-hydroxy­reactions, motility and cell division. phosphoryl

ATP consists of adenosine—itself composed of an oxy-hydroxy-phosphoryl
adenine ring and a ribose sugar—and three oxphosphonic acid 
phosphate groups (triphosphate). 
Abbreviations ATP 
Chemical formula C10H16N5O13P3 
203 Medical Sensors

Incus 
Maleus 
Eardrum 
Stapes 
Eustachian 
tube 
Cochlea 
Vestibular 
cochlear 
nerve 
Photosynthesis (See color insert.) 
Stroma 
chemical energy. 
and used to convert water, carbon dioxide, 
animal life. 
The NADPH oxidase (nicotinamide adenine dinucleotide
phosphate-oxidase) complex is an enzyme complex. 
It generates superoxide by transferring electrons from
NADPH inside the cell across the membrane and coupling
these to molecular oxygen to produce the superoxide, which
is a highly reactive free radical. 
molecules to higher energy levels; these

leave the chlorophyll and pass along a
series of molecules, generating formation of
NADPH (an enzyme) and high-energy ATP
molecules. 
Photo
H2O 
Photo-
system II 
2e – 
Electron 
carriers 
synthetic membrane
(thylakoid membrane) 
2H+ +½ O2 
H + 
H + 
Lumen 
Photo-
system
I 
2e – 
NADP+ 
+ 2H+ 
H + 
ATP 
synthesis 
NADPH+H+ ATP ADP P 
Light H + 
© 2006 Herramienta Inc. or dark reaction 
Hearing 
The ear has three major regions: the outer ear, the
middle ear and the inner ear. 
The process of hearing begins when sound waves
make it to the middle ear, causing the ear drum to
Semicircular canals vibrate. 
The human ear is the anatomical structure responsible 
for hearing and balance. 
Pinna 
The second part of the outer ear, the external auditory
canal, is a passageway in the temporal lobe of the skull, External

Pinna 
canal, is a passageway in the temporal lobe of the skull, External 
which leads from the outside of the head and extends auditory
inward and slightly upwards. In the adult human, it is canal 
lined with skin and hairs and is approximately 1 inch (2.5
Lobulecm) long. 
The third part of the outer ear, the tympanic membrane
or eardrum, is a thin, concave membrane stretched 
across the inner end of the external auditory canal much
like the skin covering the top of a drum. The eardrum
transmits sound to the middle ear by vibrating in
response to sounds traveling down the external
auditory canal. 
Light
energy 
Oxygen 
Sugar 
Water 
6CO2 + 12H2O + Light      C6H12O6 +6 O2 +6 H2O 
204 Biomedical Informatics

Kidneys (See color insert.) 
 
weight, they receive a huge amount—20%—
 
constant
 
Pancreas/diabetes 
The Pancreas is located behind the liver and stomach. In addition

The Pancreas is located behind the liver and stomach. In addition 
to secreting digestive enzymes, the pancreas secretes the
hormones insulin and glucagon into the bloodstream. The release
of insulin into the blood lowers the level of blood glucose (simple
sugars from food) by enhancing glucose to enter the body cells,
where it is metabolized. If blood glucose levels get too low, the
pancreas secretes glucagon to stimulate the release of glucose from
the liver. 
Type 2 diabetes means that your body doesn’t make enough
insulin, or doesn’t properly use the insulin your body makes. Insulin,
which is made in your pancreas, helps your body’s cells use sugar
from your bloodstream, which comes from foods and drinks. Sugar
is a source of energy for cells. Type 2 diabetes,is rising fast in the 
United States. It accounts for most diabetes cases.Typically, with 
type 2 diabetes, the body still makes insulin, but its cells can’t use it.

type 2 diabetes, the body still makes insulin, but its cells can’t use it. 
This is called insulin resistance. Over time, high levels of sugar build 
up in the bloodstream. Being overweight and inactive increase the 
chances of developing type 2 diabetes. 
Type 1 diabetes. This form often affects children, but adults can
develop it, too. In this form of diabetes, the body can’t make insulin.
The immune system by mistake attacks the cells in the pancreas
that make and release insulin. As these cells die, blood sugar levels
rise. People with type 1 diabetes need insulin shots. 
The pancreas secretes insulin
in response to glucose levels
in the blood. 
205 Medical Sensors

206 Biomedical Informatics 
Liver (See color insert.) 
Bile duct 
EB Inc. 
The Liver is in the right upper abdomen. The liver
serves many functions, including the detoxification
of substances delivered from the intestines, and
 
the synthesis of many proteins.
 Liver 
The largest gland in the body, a spongy mass of wedge-
shaped lobes that has many metabolic and secretory
 Gallbladder 
functions. The liver secretes bile, a digestive fluid;
metabolizes proteins, carbohydrates, and fats; stores
 Bile duct 
glycogen, vitamins, and other substances; synthesizes
blood-clotting factors; removes wastes and toxic matter
from the blood
 
A liver transplant may be recommended for:
liver damage due to:
 
alcoholism (Alcoholic cirrhosis)
 
end-stage liver disease (primary biliary cirrhosis)
 Arteries/Veins/Capillaries inside Liver 
long-term (chronic) active infection (hepatitis)

Inferior liver (hepatic) vein clot (thrombosis)
 vena cava 
birth defects of the liver or bile ducts (biliary
 Hepatic veins 
atresia)
metabolic disorders associated with liver failure Portal veins 
(e.g., Wilson’s disease) Bile duct 
Hepatic artery

Gallbladder 
The Gallbladder is a muscular sac located 
under the liver. It stores and concentrates 
the bile produced in the liver that is not
immediately needed for digestion. Bile is
released from the gallbladder into the
small intestine. 
Liver 
Common hepatic duct 
Cystic duct 
Common bile 
duct 
Pancreas 
Pancreatio duct 
Duodenum portion 
of the small 
intestine 
Major
duodenal 
papills 
Sphincter
of Oddi 
The Digestive System 
Digestion is the process by which the body
converts food into basic substances that can 
either be absorbed in the bloodstream as Liver Esophagus nutrients or passed out of the body as waste. 
This process of breakdown and Gallbladder Stomach 
assimilation occurs within the digestive
tract, a convoluted tube more than 30 feet Pancreas 
long that is lined with a mucous
membrane. 
Other digestive juices required by the small
Large intestine intestine to digest and absorb food, Small intestineparticularly fats and starches, come from the

pancreas, an organ located just behind the
stomach. Rectum 
Whatever substances are not assimilated 
into the bloodstream through the small
intestine move into the large intestine. Within
the large intestine, waste material is
processed into stool (feces), and water and
certain chemicals are absorbed into the 
bloodstream to preserve the body’s fluid
balance. 
Stomach    The digestive track includes the: mouth, esophagus, Largestomach, small intestine and large intestine. Each has a intestine function in the digestive process. The muscles in these
organs move food through the digestive system and
mucus lubricates the tract. The liver, gallbladder and Duodenum 
pancreas are also part of this digestive process.
  The small intestine is where most of the 
digestion and absorption of food occurs. Small Jejunum It is composed of three parts: intestine

The small intestine is where most of the 
digestion and absorption of food occurs. Small Jejunum It is composed of three parts: intestine 
1: Duodenum: It’s the shortest part, Duodenum 4 parts ileumwhere most of the chemical digestion
a: Superior duodenal flexure takes place; iron absorption takes place
here. b: Descending 
2: Jejunum: In this section sugars,
amino acids, and fatty acids are The Large Intestine: primary role is toc: Horizontal absorbed into the bloodstream. (It’s remove water from the body. The
approximately 7 feet long). secondary function via bacteria, break
d: Ascending part down undigested sugars and fibers into3: Ileum: It absorbs vitamin fatty acids. The bacteria has a side affectB12 and bile acids and any other that produces methane, hydrogen sulfideremaining nutrients. (approximately 9 feet and CO

2. A by product of the bacterialong). B12 is an essential nutrient produces vitamin K and biotin that isfor the brain, nervous system and blood reabsorbed back into the body. (5 feet) formation. 
Large intestine 
207 Medical Sensors

208 Biomedical Informatics 
7.9 Part III: Lungs, Immune System, Stroke, Blood Flow, Prostate
 1. Lungs
 2.  Immune  system 
 a.  Bacteria and viruses
 b.  Epidermis  (skin)
 c.  Lymph  system
 d.  Thymus
 e.  Antibodies 
 f.  White blood cells
 g. Leukocytes
 3.  Stroke
 4. Blood flow
 a.  Arteries
 b.  Veins
 c.  Capillaries
 5.  Prostate 
Lungs (See color insert.) 
 
 Primary
bronchus
 
Secondary
bronchusautomatically send signals to the diaphragm and

Secondary
 
Tertiary
bronchus 
Terminal 
bronchiole Alveoli

–
-
 
Lungs (continued) 
When you inhale, the diaphragm and intercostal
muscles (those are the muscles between your ribs)
contract and expand the chest cavity. 
A
 
This expansion lowers the pressure in the chest B 
cavity below the outside air pressure. Air then flows
Cin through the airways (from high pressure to
low pressure) and inflates the lungs.
 
D	 A Nasal cavity
B Pharynx
When you exhale, the diaphragm and intercostal	 C Larynx
muscles relax and the chest cavity gets smaller. E	 D Trachea
 
E Alveoli
 
The decrease in volume of the cavity increases the F F Bronchlai tree 
pressure in the chest cavity above the outside air G Diaphragm 
pressure. Air from the lungs (high pressure) then G 
flows out of the airways to the outside air (low
pressure). The cycle then repeats with each breath. 
E 
© 2000 How Stuff Works 
As you breathe air in through your nose or mouth, it goes past the epiglottis and
into the trachea. It continues down the trachea through your vocal cords in the

larynx until it reaches the bronchi. From the bronchi, air passes into each lung.
The air then follows narrower and narrower bronchioles until it reaches the
 
alveoli.
 
Air	 Plasma 
CO2 CO2 (Dissolved in plasma) 
There within each air sac, the oxygen CO2 CO2 +H 2O CO3 HCO3 +H +H2
concentration is high, so oxygen passes or (Slow)
diffuses across the alveolar membrane into the HCO3
 
pulmonary capillary.
 
HCO3 +H + 
At the beginning of the pulmonary capillary, the
hemoglobin in the red blood cells has carbon
 H2CO3 Carbonic
 
dioxide bound to it and very little oxygen. anhydrase
(Fast) CO2 +H 2O 
The oxygen binds to hemoglobin and the
CO2carbon dioxide is released. Carbon dioxide 
(Carbaminois also released from sodium bicarbonate homoglobin)
dissolved in the blood of the pulmonary HbCO2 
capillary. The concentration of carbon dioxide
is high in the pulmonary capillary, so carbon
CO2 CO2 +H b

CO2 CO2 +H b 
dioxide leaves the blood and passes across
the alveolar membrane into the air sac. This 
O2 O2 +H H b HbO2 +H + 
exchange of gases occurs rapidly (fractions (Oxy-homoglobin) 
of a second). The carbon dioxide then leaves
the alveolus when you exhale and the
O2	 O2 (Dissolved Red 
oxygen-enriched blood returns to the heart	 blood cell in plasma) 
209 Medical Sensors

Anatomy of the Lung 
Alveolus—tiny, thin-walled air sac at the end of the bronchiole branches where gas
exchange occurs (plural-alveoli).
Bronchioles—numerous small tubes that branch from each bronchus into the lungs. They
get smaller and smaller. 
Bronchus—a branch of the trachea that goes from the trachea into the lung (plural-bronchi).
Diaphragm—muscle at the base of the chest cavity that contracts and relaxes during
breathing.
 
Epiglottis—a flap of tissue that closes over the trachea when you swallow so that food does
not enter your airway.
Intercostal muscles—muscles along the rid cage that assist in breathing.
Larynx—voice box where the vocal cords are located.
nasal cavity—chamber in from the nose where air is moistened and warmed.
 
Pleural membranes—thin, membranes that cover the lungs, separate them from other
organs and form a fluid—filled chest cavity.
 
Pulmonary capillaries—small blood vessels that surround each alveolus.

Pulmonary capillaries—small blood vessels that surround each alveolus. 
Trachea—rigid tube that connects the mouth with the bronchi (windpipe). 
Immune System (See color insert.) 
AIDS 
attacks immune system cells. 
collapses and the victim dies of some
wrapped inside a protective shell. An HIV virus

has a diameter of about one 10,000th of a millimeter. 
Photo courtlesy National Institute
HIV. the virus that causes 
out of a human immune 
cell. 
RNA gp41
envelope
protein 
gp120
envelope
protein 
p17
matrix 
proteins 
p24
capsule
proteins 
Reverse 
Lipid
membrane 
210 Biomedical Informatics

Immune System  (continued) 
The immune system is a network of cells, 
tissues, and organs that work together to protect 
the body from infection. (NIH) 
http://www.niaid.nih.gov/topics/immunesystem/Pages/
default.aspx 
1. There are a number of triggers called Danger­
    Associated Molecular Patterns (DAMPs) that can
    differentiate between health and unhealthy cells. 
The innate immune system recognizes molecules
via the innate immune system by pattern
recognition receptors triggered by cell death or
injury. 
DAMPS are often derived from the plasma
membrane, nucleus, endoplasmic reticulum and
cytosol and mitochondria. 
2. Pathogen-associated molecular patterns (PAMPs)
    another set of triggers generated by Bacteria and
    viruses. 
Delivery of PAMPs to their respective receptors
constitute part of the initiated innate immune
control. 
Colds and flu are caused by viruses.
A virus must have a host cell (bacteria, plant or
animal) to make more viruses.

control. 
animal) to make more viruses. 
The epidermis (skin) contains special cells called
Langerhans cells (mixed in with the melanocytes in
the basal layer) that are an important early-warning
component in the immune system. 
The skin also secretes antibacterial 
substances. These substances explain why you
don’t wake up in the morning with a layer of
mold growing on your skin—most bacteria and
spores that land on the skin die quickly. 
it is made up of two main layers: 
The epidermis on the outside and the 
The dermis on the inside. 
The epidermis is the barrier, while the dermis
is the layer containing all the “equipment” –
things like nerve endings, sweat glands,
hair follicles and so on. 
Cancer cells 
DAMPs 
Cytotoxic T cells 
Helper T cells 
DC 
© Copyright Policy - open-access 
Certain chemotherapeutics agents (anthracyclines)
will induce immunogenic apoptosis in cancer cell

DC 
through induction of (DAMPs). 
http://openi.nlm.nih.gov/detailedresult.php?img=2896720 JBB2010­
692097.001&reg=4 
TLR	 Endosome/
Lysosome 
Pathogen Autophagosome 
TLR7 
Inflammasoma 
Afg12-Afg5 RIG-I 
Ipaf Afg16L 
© Copyright Policy - open-access licence 
Some PAMP receptors stimulate macroautophagy 
Skin Anatomy΄ 
΄not to scale 
Stratum 
corneum 
New skin 
layer 
Subcutandeous 
layer 
Fat 
cells Sebaceous 
gland 
Hair 
follicle 
Erector 
muscle 
Sweat 
gland 
Dermis Epidermis 
© 2005 HowStuffWorks 
Sunbum animation 
211 Medical Sensors

Immune Response (white Blood Cells)
 
(white blood cells, another term for immune cells) http://www.niaid.nih.gov/topics/immuneSystem/Pages/overview.aspx
 
1. Skin: The skin is usually the first line of defense against microbes.
   Skin cells produce and secrete important antimicrobial proteins, and Bone anatomy 
   immune cells can be found in specific layers of skin. Spongy bone Blood vessels in (contains red bone marrow 2. Bone marrow: The bone marrow contains stems cells that can	 marrow) Blood stem 
   develop into a variety of cell types. Ex: neutrophils, eosinophils, cell 
   basophils, monocytes, dendritic cells, and macrophages 
3. Lymphocytes: Adaptive immune cells—B cells and T cells are	 Red blood cells 
   responsible for mounting responses to specific microbes based on
   previous encounters (immunological memory). Yellow White blood cells marrow 
4. Thymus: T cells mature in the thymus, a small organ located in the Compact bone
 
   upper chest.

5. The lymphatic system is a network of vessels and tissues composed of
   lymph, an extracellular fluid, and lymphoid organs, such as lymph Platelets 
   nodes. Immune cells are carried through the lymphatic system and
converge in lymph nodes, which are found throughout the body. 
6. The spleen: Immune cells are enriched in specific areas of the spleen,
   and upon recognizing blood-borne pathogens, they will activate. 
212 Biomedical Informatics 
Immune System (continued) 
Lymph System 
• 	 The lymph system, lymph nodes, are just one part of a system that extends throughout your 
body in much the same way your blood vessels do. 
• 	 The main difference bet ween the blood flowing in the circulatory system and the lymph flow­
ing in the lymph system is that blood is pressurized by the heart,  while the lymph  system  
is passive.

is passive. 
• 	 There is no “lymph pump” like there is a “blood pump” (the heart). 
• 	 Instead, fluids  ooze  into  the lymph system and  get  pushed by n ormal b ody and muscle  
motion to  the lymph nodes. 
• 	 Lymph is a clearish liquid that bathes the cells  with water and nutrients.  Lymph is blood 
plasma – the liquid that makes up blood minus the red and white cells . Think about 
it—each cell does not have its o wn private blood vessel feeding it, yet it has to get food, 
water, and oxygen to survive. 
• 	 Blood  transfers  these materials to the  lymph through the  capillary walls, and lymph car­
ries it to the cells. 
• 	 The cells also produce protein s  and  waste  products  and the lymph absorbs these prod­
ucts and carries them away . 
• 	 Any random bacteria that enter the body also find their w ay into this intercell fluid.

• 	 Any random bacteria that enter the body also find their w ay into this intercell fluid. 
• 	 One job of the lymph system is to  drain and filter  these fluids  to  detect  and  remove  the  
bacteria . 
• 	 Small lymph vessels collect the liquid and move it to ward larger vessels so that the fluid 
finally arrives at the lymph nodes for processing. 
All immune  cells  come  from precursors  in the bone marrow  and  develop  into mature  cells 
through a  series  of  changes that can occur  in different parts  of the body

Neutrophils, are a type of white blood cell which travel to infected tissue and
surround bacteria, rendering them harmless to the body. White Blood Cells Lymphocyte (T and B cells):Leukocytes
Lymphocyte    T cells are especially important in cell-mediated immunity, which is the defense
Monocytes against tumor cells and pathogenic organisms inside body cells. They are also
Granulocytes involved in rejection reactions.
B-cells
    B cells, in the presence of an antigen (a substance that stimulates an immune
Plasma cells
 response), secrete large quantities of antibodies
 
T-cells
 
Helper T-cells
 White blood cell distribution White blood cell distribution Killer T-cells chart Suppressor T-cells
White Blood Cell Type Range% 
Basophils
 Natural killer cells
 
Neutrophils
 Neutrophils 50–70 
EosinophilsEosinophils Lymphocytes 15–40 Maximum Basophils Monocytes 
MinimumPhagocytes Monocytes 2–8 Lymphocytes Macrophages
 
Eosinophils 1–4
 Neutrophils

0.00%Basophils 0.4–1.0 20.00% 40.00% 60.00% 80.00%Illustration: Source Wiki books Open source 
213 Medical Sensors 
Antibodies 
• 	 Antibodies (also referred to as immunoglobulins and gammaglobulins) are pro­
duced by white blood cells . 
• 	 They are Y-shaped proteins that each respond to a specific antigen (bacteria, 
virus or toxin). 
• 	 Each antibody has a special section (at the tips of the t wo branches of the Y)  
that is sensitive to a specific antigen and binds to it in some w ay. When an  
antibody binds to a toxin it is called an antitoxin (if the toxin comes from  
some form of venom, it is called an antivenin). The binding generally disables  
the chemical action of the toxin. When an antibody binds to the outer coat  
of a virus particle or the cell  wall of a bacterium it can stop their movement  
through cell  walls. 
 • 	 Antibodies come in five classes:

 • 	 Antibodies come in five classes: 
Immunoglobulin A (IgA)
 
Immunoglobulin D (IgD)
 
Immunoglobulin  E (IgE)
 
Immunoglobulin G (IgG)
 
Immunoglobulin M (IgM)
 
Whenever you see an abbreviation like  IgE in a medical document it’s an antibody 
White blood cells work together to destroy viruses and bacteria. They are
classified into lymphocytes and myeloid leukocytes. Lymphocytes are B cells,
T cells and Killer cells. Myeloid Leukocytes are composed of monocytes,
neutrophils, basophils and eosinophils.

Heart disease
 
  Heart disease describes a number of conditions
 
that affect your heart. They include diseases of
blood vessel diseases, such as coronary artery
disease; heart rhythm problems (arrhythmias); and
heart defects (congenital heart defects). Most
common references refer to coronary heart disease
refer to blocked or narrowing blood vessels.
  Arteriosclerosis is where the walls thicken due to
 
inflammation and the accumulation of plaques that
reduce the elasticity of the walls. (Plaque
 consists of
 
fat, cholesterol, calcium, and other substances found
 
in the blood.)
 
The term angina is defined as: blood flow to your
heart muscle is reduced or blocked, symptoms are
chest pain or discomfort) or a heart attack) 
Atherosclerosis is initiated by
inflammatory processes in the
endothelial cells of the vessel wall 
214 Biomedical Informatics 
Leukocytes 
• 	 All white blood cells are known officially as leukocytes.

• 	 All white blood cells are known officially as leukocytes. 
• 	 White blood cells are not like normal cells in the body—they actually  act like  indepen­
dent, living  single-cell  organisms able to move and capture things on their o wn. 
• 	 White blood cells behave very much like amoeba in their movements and are able to  
engulf other cells and bacteria. Many w hite blood cells cannot divide and reproduce on 
their own, but instead have a factory some where in the body that produces them. That  
factory is the bone marrow . 
Leukocytes are divided into three classes: 
• 	 Granulocytes : Granulocytes make up 50%–60% of all leukocytes. Granulocytes are 
themselves divided into three classes: neutrophils, eosinophils, and basophils. 
Granulocytes get their name because they contain granules, and these granules contain 
different chemicals depending on the type of cell.

different chemicals depending on the type of cell. 
• 	 Lymphocyte : Lymphocytes make up 30%–40% of all leukocytes. Lymphocytes come in  
two classes: B cells (those  that mature  in bone marrow) and  T  cells (those  that mature  in 
the  thymus). 
• 	 Monocyte : Monocytes make up 7% or so of all leukocytes. Monocytes evolve into  
macrophages. 
All  white blood cells start in bone marro w as stem cells. 
7.10 Part IV: Heart Disease, Cancer
 1. Heart disease 
 a. Coronary balloon angioplasty
 b.  Stent placement
 c. Blood types
 2.  Cancer

215 Medical Sensors 
Diagnostic tests 
EKG 
ST segment (the line b etween the QRS complex and the T wave) depression and T wave changes
(usually inversion) are the hallmarks of ischemia. 
However, an EKG in someone with a history of CAD and angina often has a “normal” reading.
If an EKG is done during an episode of angina, sometimes the typical ST segment depression
can be seen. 
Stress Test 
Because a resting EKG often results in a “normal” reading for a person with angina, your
physician may need to have a stress test to evaluate the presence of CAD. As described earlier,
if the characteristic ST segment depression occurs during stress testing, especially if typical chest
pain occurs, the test is considered “positive. ” 
Cardiac Catheterization 
A cardiac catheterization test can be used to determine if CAD is present, how severe it is and
determine if a coronary artery bypass graft is needed. It can definitely exclude CAD if it is not

present. This test is performed for many reasons. It is especially important if: 
During a cardiac catheterization, blockages
are treated as a balloon is blown up inside
the coronary arteries, thereby opening the
 
passage.
 
This procedure is called Percutaneous
Transluminal Coronary Angioplasty
(PTCA) or just plain angioplasty. Here is an
example of how an angioplasty works:
 
Coronary
Artery 
Catheter 
Balloon 
at tip of
Catheter 
Atheroma 
Coronary balloon angioplasty 
The illustration shows a cross-
section of a coronary artery with
plaque buildup. 
The coronary artery is located on
the surface of the heart. 
Figure A shows the deflated balloon
catheter inserted into the narrowed 
coronary artery. 
In Figure B, the balloon is inflated,
compressing the plaque and
restoring the size of the artery. 
Figure C shows normal blood flow
restored in the widened artery.

Blood types
ood carries nutrients and oxygen to the
d waste products away from the cells. Blood is
sed of three types of cells: Red blood cells that
xygen via hemoglobin (a protein). White blood
ght infection and Platelets that clot, stopping
ng. They are all suspended in blood plasma, a liquid
ising 55% of total blood volume. Plasma is
ised of 92% to 95% of water. The rest is composed of
s, glucose, clotting factors, electrolytes and CO2 
a is used to excrete waste: CO2. urea, lactic acid.)
od PH (Potential of Hydrogen) measures
drogen concentration in the blood. It's either acidic
r alkaline (8–14); a PH of 7 is neutral. Normal PH
–7.45) Acid-Base PH disorders caused by diet and
leads to Inflammation which is intern linked to 
, heart disease, and strokes. APH below about 7 or 
.7) can be fatal. (pH is a logarithmic scale:
nce of 1 pH is a 10x difference.)
e blood carries CO2 away in the lungs, the biggest
 of acid elimination in our body. The kidneys

e a secondary protection in urine (but more slowly). 
Hemoglobin molecule 
Heme 
Red blood 
cell 
Red blood
 
cells contain
 
several hundred
 
hemoglobin molecules
 Oxygen binds to heme onwhich transport oxygen the hemoglobin molecule 
Red blood cells 
Acidic Neutral Basic 
0 123456789 1 0 1 1 1 2 1 3 14 
PH range 
        Bl
cells an
compo
carry o
cells fi
bleedi
compr
compr
protein
(Plasm
       Blo
the hy
(0–6) o
is 7.35
stress 
cancer
over 7
differe
      Th
source
provid
 
Stent Placement 
The illustration shows the placement
of a stent in a coronary artery with
The coronary artery is located on the
surface of the heart. 
catheter and closed stent inserted into 
the narrowed coronary artery. 
expanding the stent and compressing

the plaque to restore the size of the 
artery. 
Figure C, shows normal blood flow
restored in the stent-widened artery. 
Angioplasty-Stent Animation 
216 Biomedical Informatics

A blood type(group) is determined by the presence or absence of an inherited antigen, contributed
by both parents, on the surface of red blood cells (antigens cause an immune response). Both the ABO and Rh blood group
(There are over 30 human blood group systems. The ABO and Rh blood systems are the dominant System can affect transfusion
ones.) (The International Society of Blood Transfusions officially recognizes 33 groups as of 2012.) compatibility. 
The four major blood groups are: Type O– universal donor
Group A − has only the A antigen on red cells (and B antibody in the plasma) Type A– can donate to As and ABs
Group B − has only the B antigen on red cells (and A antibody in the plasma) Type B– can donate to B and ABs
Group AB − has both A and B antigens on red cells (but neither A nor B antibody in theplasma) Type AB– donate to ABs but can
Group O − has neither A nor B antigens on red cells (but both A and B antibody are in the plasma) receive from all

Group O − has neither A nor B antigens on red cells (but both A and B antibody are in the plasma) receive from all 
ABO blood group antigens present on red blood cells and IgM
Group A Group B Group AB Group O 
AB– 0.45% 
Red blood 
cell type A B A B O B– 1.39% O+ 36.44% 
A– 3.52% 
Antibodies None 
O– 4.33% 
in plasma 
Anti-B Anti-A Anti-A and Anti-B AB+ 5.06% A+ 28.27% 
Antigens in
red blood 
cell A antigen B antigen A and B 
antigens 
None 
B+ 20.59% 
Percentages in population 
antibodies present in the serum ABO blood system 
Cancer 
Cancer is the uncontrolled growth of abnormal cells
in the body. Cancerous cells are also called malignant
cells. 
DNA with 5T4 gene from TroVax 
Alternative Names: Carcinoma; Malignant 
Antigentumor 
preventing cell 
Tumor cell destroyed Cancer grows out of normal cells in the body. Normal
cells multiply when the body needs them, and die 5T4 antigen
when the body doesn’t. Cancer appears to occur
when the growth of cells in the body is out of control

and cells divide too rapidly. Tumor cell 
There are multiple causes of cancers, including:
Radiation 
Sunlight
Tumor cell 
Tobacco 
Certain viruses 
Benzene 
Anti-5T4 antibodies Anti-5t4 antibodies 
recognize tumor cell 
The three most common cancers in men in the 
United States are prostate cancer , lung cancer,
and colon cancer. In women in the United States, 
the three most frequently occurring cancers are
breast cancer, lung cancer, and colon cancer. 
Cancer Animation 1 
Cancer Treatment Angiogenesis Animation 
217 Medical Sensors

a. 	 What role do you believe they have played in improving medical delivery? 
 2.  Why do you believe it’s important to understand the basics of electrical and chemical conduction  
basics while studying biomedical informatics? 
 a. 	 What are subatomic particles? 
 3. What is Ohm’s law? 
 a.	  Create your own V = I × R example similar to Example 7.1. 
 4. What is electrochemistry? 
 a.	  What role do valence electrons play in electrical conduction? 
 b. 	 Explain the similarities of copper, silver, and gold as relates to their conduction characteris­
tics (Figure 7.6a). 
 5. Explain the general working characteristics of batteries. How do they supply current to an electri­
cal device? 
 a. 	 What are the characteristics of a dead battery? Explain the underlying mechanism. 
 b.	  What is the difference between a lithium and lead–acid battery? Explain some of the operat­
ing characteristics: current, weight, and safety in medical devices.

ing characteristics: current, weight, and safety in medical devices. 
 c.	  Define inductive charging of batteries. When is it useful in medical devices? 
218 Biomedical Informatics 
7.11 Su m m a r y 
This chapter focuses on electrochemistry, electrical and chemical properties, needed to under­
stand, capture, and process medical sensor data. Current, electrons, traveling through computer 
circuitry is essentially the same as signals sent through biological systems except that some of the 
intermediate propagation mechanisms are electrochemical, i.e., positive ions are moved across cell 
membranes to create a voltage and then current flows sending or receiving a sensory signal. The 
propagation speed in electric circuits is much faster, and the theoretical limit is the speed of light 
186,000 miles/s (electromagnetic signal light traveling through empty space; space is not empty but

186,000 miles/s (electromagnetic signal light traveling through empty space; space is not empty but 
close enough), but in reality, the speed is more closer to two-thirds of that due to the limitation of 
traveling through materials, wires. In biological systems, the max speed is about 100 m/s since there 
is not just one wire but countless neurons separated by gaps, synapses, where a sodium–potassium 
pump has to transfer positive ions further slowing conduction speeds. A section on the chemical– 
electrical batteries was included since medical sensors, especially wireless, need to be powered so 
the reader can make informed decisions on embedded power sources, plus the internal chemical– 
electrical properties of batteries complete a student’s understanding of voltage and current flow 
regardless of the source. 
Level II introduces wireless medical devices, since wearable medical sensors will be worn or

Level II introduces wireless medical devices, since wearable medical sensors will be worn or 
implanted in a large percentage of the population in the next decade when preventive medicine will 
then come into its own. It will certainly be cost effective, though I don’t like to focus on that aspect 
since we should expand free healthcare for all as a basic right as is the case in most of the industrial­
ized countries, but since prevention will decrease hospitalizations and reduce overall costs, treating 
a cold is cheaper than pneumonia, and wearable medical devices will be as common as cell phones. 
Level III focuses on intelligent expert systems and data mining since the torrent of data from medi­
cal sensors will provide the opportunity to accelerate medical research expediting the analysis of drug 
effectiveness and treatment, a key component of the BMI discipline. 
Level IV is a basic anatomy and physiology primer for BMI students. 
Questions 
Level I

Questions 
Level I 
1. What is the role of medical sensors in healthcare?

6.  Explain the difference of electrical conduction in wires versus that in a biological organism: for 
example, electrons flowing in a nerve synapse. 
 a.	  What is an action potential? 
 7. Briefly explain the cardiac conduction systems. How do electrical signals coordinate the excita­
tion and contraction of the four chambers of the heart? 
 a. 	 Specifically track the signals from the SA node to the AV node and bundle of His. 
 8.  What role does ATP play in chemical/electrical conduction systems? 
 9. Explain and describe sensors used to measure the following:
 a.	  Blood  pressure
 b.	  Pulse  oximetry
 c. 	 Measuring ABG 
 10. Explain how neurons conduct electrical signals. 
 a.	  What is the sodium–potassium pump? Why is it important in electrical conduction in bio­
logical systems? 
Level II 
 11. What are the advantages of wireless medical monitoring devices? 
 a.	  Explain Bluetooth wireless communications. 
 12. What are body sensor networks?

a.	  Explain Bluetooth wireless communications. 
 12. What are body sensor networks? 
 a.	  In body sensor networks, explain the three types of data capture: structured, nonstructured,  
and loosely structured data capture. 
Level III 
 13. What is an expert system? 
 a.	  What is a cognitive system? 
 b. 	 What are crowd-sourced systems? What advantages do they provide? 
 14. How is data mining used in large data sets in healthcare? 
 15. Summarize Case Study 7.6.1.2 on body sensor networks. 
 16. Research an example of an expert system used in healthcare. 
Level IV 
Answer the following questions after reviewing this section: 
 1.  Neurons send electrical signals across a ___________ by pumping positive ions across.
 a.	  Axon
 b.	  Synapse
 c.	  Voltage
 d.	  Gap 
 e.	  None of the above 
 2.  This process limits the speed of electrical conduction in humans to ____ ft/s. 
 a. 	 Speed of light 
 b. 	 3 × 10
10 m/s
 c.	  50
 d.	  100
 e.	  200

a. 	 Speed of light 
 b. 	 3 × 10
10 m/s
 c.	  50
 d.	  100
 e.	  200 
 3.  The part of the brain that ________ integrates pathways, using the constant feedback on body  
position to fine-tune motor movements (learned-programmed sequences).
 a.	  Frontal  lobe
 b.	  Pons 
219 Medical Sensors

220 Biomedical Informatics
 c.  Cerebellum
 d.  Cerebral  cortex 
 e.  None of the above 
 4.  The _________ motor areas are directly connected to this part of the brain that is connected to  
the nerves of the spinal cord.
 a.  Somatomotor  cortex
 b.  Occipital  lobe
 c.  Temporal  lobe
 d.  Medulla oblongata 
 5.  The _____receptor cells of the eye that translate colors into electrical signals are
 a.  Rods
 b.  Cones
 c.  Co
rnea
 d.  Retina
 e.  Lens 
 6. Link the terms (draw connecting lines) from column one to column two: 
 a. DNA  a. Catalyze biochemical reactions 
 b.  RNA  b. Genetic instructions 
 c.  Proteins   c. Translate genetic information 
 d.  Cell   d. Intracellular energy transfer 
 e.  ATP  e. Structural and function unit 
Glossary 
Arterial blood gases (ABGs)  require drawing blood from an artery, often taken from the radial arter
the wrist or the femoral artery in the groin, but a number of other sites are used. ABG provi

more comprehensive information than pulse oximetry information, which is vital for critic
ill patients in intensive care units. 
Automaticity: AV cells can depolarize by themselves. 
Batteries provide electrical energy from chemical reactions; it incorporates electrochemical cells, wh
allows the flow of ions. 
Blood pressure is the pressure on the walls of blood vessels that is exerted by circulating blood an
measured by the force per unit area. Blood pressure is the brachial arterial pressure usu
measured in the upper arm as blood moves away from the heart. 
The cardiac myocyte is a muscle cell that is 100 μm in length. It is composed of bundles of myofibrils t
contain filaments. The myofibril, tubelike structures, propagates signals inside the muscles
Data mining can be defined as the process of finding previously unknown patterns and trends in da

bases and using that information to build predictive models. 
Depolarization: Muscle cells, cardiac myocytes, are made up of negatively charged cells; when posit
ions are pumped into the cell calcium (Ca
2+), sodium (Na+), and potassium (K +), the polar
of the cell becomes positive and the cell contract (negative to positive membrane potential)
Electrochemistry is “a science that deals with the relation of electricity to chemical changes and with 
y at 
des 
a
lly 
ich 
d is 
ally 
hat 
. 
ta­
ive 
ity 
. 
th
e 
interconversion of chemical and electrical energy.” 
Electrocardiogram measures the electrical activity of the cardiac muscle of the heart. 
Electrotonic spread: A change in membrane potential (e.g., areceptor potentialor synaptic potential) 
originating in one region of a cell (Δ V
0) is associated with local transmembrane currents

0) is associated with local transmembrane currents 
that distribute and flow intracellularly and extracellularly to adjacent membrane regions (at 
distance d), where they in turn cause changes in membrane potential (Δ V(d)). However, the

221 Medical Sensors 
underlying currents get progressively smaller with distance because fractions of them are 
diverted through transmembrane ion leak channels. Thereby, the elicited adjacent membrane 
potential changes (Δ V(d)) are reduced in size and altered in shape (electrotonic decrement) 
(http://www.springerreference.com/docs/html/chapterdbid/116505.html). 
Excitation–contraction coupling (ECC) is the process whereby an action potential triggers a myocyte 
to contract. 
Hemoglobin is an iron-containing protein bound to red blood cells and makes up nearly all the oxygen 
presence: except there is a small amount dissolved in the plasma. It’s a metalloproteinase,a 
generic term for a protein that contains a metal ion cofactor.

Inductive charging is a method by which a magnetic field transfers electricity from an external source 
to a mobile device without the use of standard wiring. It does this by generating a magnetic 
field and creating a current in the receiving device. Electricity can move through the air and 
recharge your device’s battery. 
Beer–Lambert law is the attenuation of light by a material passing through a substance. 
Ohm’s law V = I × R (voltage = current[I] [times] resistance) describes the relationship between voltage, 
also called potential difference, which is the force that moves, or pulls, electrons through the 
wire. 
Oxyhemoglobin (oxygenated hemoglobin [HbO
2]) saturation is the ratio, expressed as a percentage, of 
the amount of oxygen relative to the total amount of hemoglobin in blood. 
Peukert’s law: It is the efficiency factor for discharging a battery. Battery ratings are quantified by the

Peukert’s law: It is the efficiency factor for discharging a battery. Battery ratings are quantified by the 
relationship between capacity, current, and discharge time. Qp = capacity when discharged at 
1 amp/h, I = amount of current drawn, and k is a constant around 1.3: t = Qp/Ik 
Pulse oximetry is noninvasive method of monitoring oxygen saturation of a patient’s hemoglobin, the 
protein in blood that carries oxygen. 
SA node is located in the right atrium where the superior vena cava joins the atrial tissue; the SA node 
acts as the main pacemaker in the heart. 
metal post a few thousand times. The equation relates the voltage between the first, primary 
coil, to the secondary coil: Vp /Vs = Np/Ns. 
V e n o u s  o x y g e n  s a t u r a t i o n  ( S v O
2): (Range 65%–75%) Percentage of oxygen bound to hemoglobin in 
blood returning to the right side of the heart.

blood returning to the right side of the heart. 
Wireless medical devices are defined as “any medical monitoring technology, worn or implanted, that 
gathers physiological information.” 
 1. Brachman, R. and Lemnios, Z. (2002). DARPA’s cognitive systems vision. Computing Research  
News, 14, 1. 
 2. Crookshank, E. (1888). The history of the germ theory. The British Medical Journal , 1(1415), 312. 
 3. Dignan, L. (February 1, 2011). Cisco predicts mobile data traffic explosion, http://seekingalpha. 
com/article/250005-cisco-predicts-mobile-data-traffic-explosion., Editor ZDNet. 
 4. Klabunde, R. (2007). Excitation contraction coupling, http://www.cvphysiology.com/Cardiac%20 
Function/CF022.htm. 
 5. Englebardt, S. P. and Nelson, R. (2002). The role of expert systems. In: Nursing and Medicine. Anti 
Essays. Retrieved: November 18, 2012, from the World Wide Web: http://www.antiessays.com/

Essays. Retrieved: November 18, 2012, from the World Wide Web: http://www.antiessays.com/ 
free-essays/185731.htmlp. p. 137 . 
 6. Geller, M. J. (2010). 	 Ancient Babylonian Medicine: Theory and Practice . Chichester, U.K.: 
 Wiley-Blackwell. ISBN 978-1-4051-2652-6.

222 Biomedical Informatics 
7. Gopakumar, T. G. (June 2012). Switchable nano magnets may revolutionize data storage: Magnetism  
of individual molecules switched, http://www.sciencedaily.com/releases/2012/06/120614131049.htm. 
8. Master list of Government Funded R&D Centers, Government Publications: IEEE, HHS.gov,  
House.gov NSF.gov. 
9. Heckerman, D. and Shortliffe, E. (1992). From certainty factors to belief networks. 	 Artificial 
Intelligence in Medicine , 4(1), 35–52. doi:10.1016/0933–3657(92)90036-O, http://research.microsoft. 
com/en-us/um/people/heckerman/HS91aim.pdf.
10. IEEE. (2012). Medical Interoperability Standards , http://www.IEEE.org/standards. 
11. Kincade, K. (1998). Data mining: Digging for healthcare gold. Insurance & Technology , 23(2), 
IM2–IM7 . 
12. Kusnetzky, D. What is big data, ZDNet. 
13. Langley, P. (2012). The cognitive systems paradigm, CogSys.org., Advances in Cognitive Systems , 
1(20), 3–13.

1(20), 3–13. 
14. Mahn, T. (2010). Wireless medical technologies: Navigating government regulation in the new 
MedicalTechnologies.pdf. 
15. Ross, P.E. (December 2004). Managing care through the air, IEEE Spectrum , 41(12), 14–19. 
16. Matzat, U. and Snijders, C. (2010). Does the online collection of ego-centered network data reduce  
data quality? An experimental comparison. Social Networks , 32(2), 105–111.

Level I: Core Concepts .................................................................................224
 
8.1 	 Introduction ......................................................................................224
 
8.2 	 Medical Imaging Formats ...............................................................224
 
DICOM • NIfTI Data Format • Analyze Data Format • Additional 
Data Formats 
8.3 	 Medical Imaging Technologies.......................................................235
 
X-Rays • Computed Tomography • MRI • Functional 
MRI • SPECT Imaging • Ultrasound • Positron Emission 
Tomography • Digital Radiography/Computed Radiography
 
Level II: Implementing and Integrating Imaging Data ...........................242
 
8.4 	 Picture Archiving and Communication System .........................242
 
8.5 	 Teleradiology .................................................................................... 244

8.6 	 CLEF ................................................................................................. 244
 
ImageCLEF Tools
 
Level III: Advanced Topics ..........................................................................247
 
8.7 	 Radio Pharmacology ........................................................................247
 
8.8 	 Digital Imaging Analysis .................................................................247
 
8.9 Summary ............................................................................................249
 
Questions .......................................................................................................249
 
Glossary .........................................................................................................250

References ......................................................................................................250
 
8 
Imaging
 
223

224 Biomedical Informatics 
8.1 Introduction
 
Medical imaging is a broad field that encompasses three core components: (1) the imaging devices and 
the complex physics and algorithms involved in analyzing these data, (2) the standards used for trans­
mitting and visualizing these images in Digital Imaging and Communications in Medicine (DICOM), 
which is the de facto standard, and (3) the system for storage and retrieval of images in a Picture Archiving 
and Communication System (PACS). Imaging informatics is more narrowly defined because once 
the image is captured, it interprets the image and manages all imaging standards such because DICOM. 
The Society for Imaging Informatics in Medicine (SIIM) defines imaging informatics as: 
image creation and acquisition, image distribution and management, image storage and retrieval, 
image processing, analysis and understanding, image visualization and data navigation; image

image processing, analysis and understanding, image visualization and data navigation; image 
interpretation, reporting, and communications. (www.siim.org ) 
Medical imaging is one of the top developments that “changed the face of clinical medicine” during 
the last millennium. (New England Journal of Medicine) 
This chapter begins with the de facto imaging standard DICOM used by over 90% of imaging 
practitioners. The next section describes each of the imaging technologies with its basic underlying 
operational physics. Level II introduces the PACS used to store and process images, teleradiology, and 
the Cross Language Evaluation Forum (CLEF), which provides multilingual conversion capabilities.  
Le
vel III discusses the advanced topics in radio pharmacology, the science of radio isotopes used to  
enhance images and advanced techniques used for automated image analysis (Figure 8.1). 
8.2 Medical Imaging Formats 
8.2.1 DICOM 
DICOM Standards Organizations 
Acronyms

Acronyms
 1.  ACR:  American College of Radiology (www.acr.org)
 2.  ANSI: American National Standards Institute
 3.  CEN TC251: Comite Europeen de Normalization Technical Committee 251
 4. DICOM: Digital Imaging and Communications in Medicine (dicom.nema.org)
 5.	  HISPP:  Healthcare Informatics Standards Planning Panel —sponsored by the American National  
Standards Institute 
 6.  NEMA: National Electrical Manufacturers Association (www.nema.org) 
 a.  MITA: Medical Imaging & Technology Alliance (www.medicalimaging.org) 
 b.  NEMA documents (http://medical.nema.org/standard.html)
 7.  JIRA: Japan Industries Association of Radiological Systems
 8.  MSDS: Healthcare Message Standard Developers Sub-Committee
 9.  NIST: National Institute of Standards and Technology
 10.  TCP/IP: Transmission Control Protocol/Internet Protocol

9.  NIST: National Institute of Standards and Technology
 10.  TCP/IP: Transmission Control Protocol/Internet Protocol 
A number of preliminary imaging standards were published in 1985 by the American College of 
Radiology (ACR), that is, ACR-NEMA No.300–1985 ver.1. Several iterations were published in the suc­
ceeding years focusing on hardware standards, software, and data formats (http://medical.nema.org/ 
Dicom/2011/11_01pu.doc).

Medical Imaging
Digital Imaging and Communications in Medicine (DICOM)
Medical imaging: hardware, physics, DICOM
and algorithms Picture Archiving System (PACS) standards 
DICOM interfaceMRI scanner PET scanner Object
definitions
Data classes
CT scanner HARDI Storage media and
file service
Gray scale
and storage system
Picture archiving
standards
(PACS) 
Security and
system management
Web access
Radio pharmacology
Isotope examples
(only some isotopes are radioactive)
 Content 
Symbol Neutrons Protons Natural abundance Principal component analysis mapping
Helium-3, He-3 1 2 0.000137% of He Original Principal components Transformations
Radioactive isotope  waveforms reduction Noisy medical image Dimensionality reduction Handling
2 2Helium-4, He-4 99.9998%
Storing
Carbon, 12C 6 6 98.89% 
Printing8 6 0.0000000001%
Carbon-14, 14C, 1 part per trillion
 Communications
or radiocarbon radioactive isotope

Storing
or radiocarbon radioactive isotope 
Imaging 225 
FIGURE 8.1 Medical imaging overview.

DICOM core components 
CommunicationsHandling Storing Printing protocol
picture archiving
and communication 
system (PACS) 
Lubliner: 2015 DICOM Standards 
Introduction: 
Overview, design
principles, defns. 
Part 2: 
Conformance 
Building Blocks
(SOP’s) 
Part 1: 
Part 3: 
Part 4: 
Service classes 
object definition 
Part 5: 
Part 6: 
Data structures 
and handling 
Data dictionary 
Part 7: 
Message Service
Element (DIMSE) 
data service 
Part 8: 
Part 10: 
Part 11: 
Part 12: 
Storage media and
file service 
Media storage 
Media formats and 
Application profiles 
physical media 
Part 14: Part 18: Part 20:Part 15: Part 16: 
Grayscale Security and system Content mapping Web access DICOM DICOM to HL7 
standards management resource persistent objects transformation 
 
226 Biomedical Informatics 
DICOM evolved out of these earlier efforts and was officially introduced in 1993 specifying standards

DICOM evolved out of these earlier efforts and was officially introduced in 1993 specifying standards 
for transmitting images, storing images, and finally processing those images. It is an international stan­
dard developed in conjunction with the International Organization for Standardization (ISO) 12052 
(see ISO, Chapter 4). These standards are maintained by the Medical Imaging & Technology Alliance 
(MITA), which is part of NEMA (http://www.medicalimaging.org/). MITA also provides standards for 
radiation therapy for cancer. The National Cancer Institute defines radiation therapy as “Radiation ther­
apy that utilizes high-energy radiation to kill cancer cells by damaging their DNA” (Figure 8.2) , http:// 
www.cancer.gov/cancertopics/factsheet/Therapy/radiation . 
DICOM Imaging Standards, Parts 1–20 
This section summarizes, in a few pages, the thousands of pages of imaging documentation provided by

This section summarizes, in a few pages, the thousands of pages of imaging documentation provided by 
MITA a division of the National Electrical Manufacturers Association (NEMA), which collectively is 
referred to as DICOM. Not every document is addressed, but the core concepts are summarized so the 
reader can gain an appreciation of the scope of these imaging standards. At the beginning of each sec­
tion, a link is provided to the source standards documentation. All items taken directly from the NEMA 
documents are in italics . 
8.2.1.1 Part 1: DICOM Introduction and Overview 
With the advent of advanced imaging technology, computed tomography (CT), magnetic resonance 
imaging (MRI) in the 1970s and 1980s, advanced computer processing, that is, the first PC’s that 
arrived in 1980’s and the World Wide Web (www), Internet, one of whose creators was Tim Berners-

Lee in the early 1990s; it was an opportune time to create industry standards for medical imaging and 
Digital Imaging and Communications in Medicine (DICOM) 
National Electronics Manufacturers Association (NEMA) maintain Standards
ISO standard 12052:2006 Health Informatics-Medical Imaging
(the origin of the part number are from the NEMA standards documents numbers)
(http://medical.nema.org/standard.html)
 
FIGURE 8.2 DICOM architecture.

Attribute A property of an information object. An attribute has a name and a value that are 
independent of any encoding scheme. 
Command A request to operate on information across a network. 
Command element An encoding of a parameter of a command that conveys this parameter’s value. 
Command stream The result of encoding a set of DICOM command elements using the DICOM encoding 
scheme. 
Conformance statement A formal statement that describes a specific product implementation that uses the DICOM 
standard. It specifies the service classes, information objects, and communication protocols 
supported by the implementation. 
Data dictionary A registry of DICOM data elements that assigns a unique tag, a name, value characteristics, 
and semantics to each data element. 
Data element A unit of information as defined by a single entry in the data dictionary. 
Data set	 Exchanged information consisting of

Data set	 Exchanged information consisting of 
Data stream The result of encoding a data set using the DICOM encoding scheme (data element numbers 
and representations as specified by the data dictionary). 
Information object An abstraction of a real information entity (e.g., CT image and structured report) that is 
acted upon by one or more DICOM commands. 
Information object class A formal description of an information object that includes a description of its purpose and 
the attributes it possesses. It does not include values for these attributes. 
Information object instance A representation of an occurrence of a real-world entity, which includes values for the 
attributes of the information object class to which the entity belongs. 
Message A data unit of the Message Exchange Protocol exchanged between two cooperating DICOM

Message A data unit of the Message Exchange Protocol exchanged between two cooperating DICOM 
applications. A message is composed of a command stream followed by an optional data 
stream. 
Service class A structured description of a service that is supported by cooperating DICOM applications 
using specific DICOM commands acting on a specific class of information object. 
Imaging	 227 
TABLE 8.1 DICOM Terms 
Definitions (Used throughout the DICOM Documents) 
communications, which currently are used by 90% of imaging practitioners and manufacturers. This 
comprehensive standard is also used by dentists, pathologists, cardiologists, etc., for handling and 
manipulating medical images (Table 8.1) . 
The DICOM standard facilitates interoperability of medical imaging equipment by specifying 
• 	 For network communications, a set of protocols to be followed by devices claiming conformance to 
the standard

the standard 
• 	 The syntax and semantics of commands and associated information that can be exchanged using 
these protocols 
• 	 For media communication, a set of media storage services to be followed by devices claiming confor­
mance to the standard, as well as a file format and a medical directory structure to facilitate access 
to the images and related information stored on interchange media 
• 	 Information that must be supplied with an implementation for which conformance to the standard 
is claimed 
8.2.1.2 DICOM Part 2: Conformance 
Conformance refers to a set of guidelines and principles that all manufacturers and practitioners should 
adhere to ensure interoperability, that is, standards which imaging systems would utilize to guarantee 
accurate communication and transmission of data (Table 8.2).

accurate communication and transmission of data (Table 8.2). 
Data flow diagrams in the document correlate real-world entities to DICOM application entities fol­
lowing data flow diagram conventions (Figure 8.3).

Application Data Flow Diagram Conventions (DICOM) 
1.	 2. 4. Network Associations: An association between a local
Application Real-World Application Entity and a remote Application Entity_over
Entity Activity a network supporting a remote Real-World Activity 
3.	 Local Local Remote 
Local Real-World Application Real-WorldApplicationReal-World	 Activity Entity ActivityEntityActivity 
The dashed line represents the DICOMDICOM Standard Interface between Standardthe local Application Entities Interface 
5. Media Storage File-set Access 
- Application Entities exchanging information on media use the DICOM File Service
- Access to, or creation of, File-sets 
- Support three basic roles, which are File-set Creator (FSC), File-set Reader (FSR), and File-set Updater (FSU) 
File-set Creator (FSC), denoted by 
Local Local	 File-set Reader (FSR), denoted by 
Real-World Application DICOM File-set Updater (FSU), denoted by
Activity Entity Storage Physical movement of the medium, denoted byMedium

Activity Entity Storage Physical movement of the medium, denoted byMedium 
 
228 Biomedical Informatics 
TABLE 8.2 Conforms to the Following Syntaxes and Vocabularies 
Conformance (to the ISO and DICOM Standards) 
Reference Model Presentation Service DICOM Introduction DICOM Service DICOM Data 
Definitions ISO 
7498–1 
8822 
and Overview 
Definitions 
Class Specification 
Structure and 
Encoding Definitions 
Application entity Abstract syntax Information object Real-world activity DICOM defined UID 
Application entity title Abstract syntax IOD Service class Privately defined UID 
name 
Protocol data unit Presentation 
context 
Service class user Transfer syntax 
(standard and 
private) 
Transfer syntax Transfer syntax Service class provider UID 
Transfer syntax 
name 
Service object 
pair (SOP) 
Meta SOP class 
FIGURE 8.3 DICOM application data flow diagram conventions.

name 
pair (SOP) 
FIGURE 8.3 DICOM application data flow diagram conventions. 
8.2.1.3 DICOM Parts 3 and 4: Information Object Definitions and Service Classes 
DICOM Part 3 describes object-oriented data models and service classes used to communicate and 
interface medical images with external systems. An “object” is an instance of class. That means that we 
define generic computer code called a class. This class might be used to process some part of an image. 
Generic code means the class is designed to process a number of different images but is without specific 
form. An example would be a car class. It is used to describe certain general attributes of any car class: 
that is, it has wheels, a motor, steering wheel, etc. We then want to describe a specific car such as a Ford 
Mustang. Then a second car, a Nissan Altima, would be an another instance of the class that contain

Mustang. Then a second car, a Nissan Altima, would be an another instance of the class that contain 
details of each car, or in this case various medical images (Figure 8.4).

Generic car class 
Attributes (wheels, motor, color, engine) 
wheels =  ; 
motor =  ; 
color =  ; 
engine =  ; 
Ford mustang Nissan altima 
Two instances of the CAR class 
Attributes (wheels, motor, color, engine) Attributes (wheels, motor, color, engine) One copy has details about a
wheels= ; wheels =  ;FORD MUSTANG motor= ; motor =  ;Second has details about the color = red ; color = silver ;
NISSAN ALTIMA engine = 8 cylinder  ; engine = 4 cylinder  ; 
Service Class Definitions which 
Relationship Between Other DICOM Standards provide an abstract definition of real-
world activities applicable to
communication of digital medical
Part 3: information 
Information OBJECT Definitions Semantic descriptions
Notifications 
Service-Object Pair (SOP) Classes
Part 7:-Semantic
 Descriptions Message Exchange The relationship of each Service-
Protocol
Part 4: Object to applicable Information Object
-Relationships Service CLASSES Definitions 
-Attributes Data Structure and Semantics

Protocol
-Attributes Data Structure and Semantics 
Lubliner 2015 The standard the structure and 
encoding of the Data Set is specified-Defines the data
Part 5: Data set is that portion of a DICOMencoding in the DIMSE Data Structure and Semantics message that conveys informationmessage encoding about real-world objects being
managed over the network-Defines all the data
Part 6: Data Dictionarytags in the elements: Data Dictionary contains the registry of all DICOM Dataexample (0008, 0105) Elements and all DICOM Unique
Identifiers that are defined within the 
Imaging 229 
FIGURE 8.4 Generic example of classes and instances of a class. 
The DICOM Part 3 document describes various Information Object Definitions (IODs), which  
describe an object-oriented abstract data model used to specify information about real-world objects.

describe an object-oriented abstract data model used to specify information about real-world objects.  
The definitions depict generic classes of real-world objects that share similar properties, just like the  
car example (Figure 8.4). There are standards group image classes that have the same general proper­
ties (Figure 8.5). 
The following are IOD object types: 
 1.  An IOD is used to represent a single class of real-world objects is called a normalized information  
object. 
 2.  An IOD that includes information about related real-world Objects is called a composite informa­
tion object. 
The relationship between object models and the other DICOM standards are depicted in (Figure 8.5). 
The relationship between the Object Models and the other DICOM standards are: DICOM Standard 
FIGURE 8.5 Relationship between DICOM standards relating to objects and classes.

Description Tag # 
Value (optional) Value Value Name of physician(s) reading study (0008, 1060) Tag representation length field
 
Admitting diagnoses description (0008, 1080)
 
Referenced study sequence (0008, 1110) 
>Referenced SOP class UID (0008, 1150) Image descriptors
(for each 2D picture slice)
 >Referenced SOP instance UID (0008, 1155) 
Patient’s age (0010, 1010 Type of (0040,E020) DICOM, CDA
 
Patient’s size (0010, 1020) instances
 
Patient’s weight (0010, 1030) Referenced (0008, 1160) Required if the
Occupation (0010, 2180) Frame referenced SOP instance 
Additional patient history (0010, 21B0) Number is a multi-frame image 
Other study numbers (0020, 1070) Referenced (0062, 000B) Identifies the segment
Number of study related series (0020, 1206) Segment number to which the
 
Number reference applies.
 Number of study related instances (0020, 1208) 
k 
i 
j 
S z x P L 
Ry A
 
I
 
230 Biomedical Informatics

k 
i 
j 
S z x P L 
Ry A
 
I
 
230 Biomedical Informatics 
8.2.1.2.1 Multidimensional Definitions: Orientation in 3D Space (Sec 3.17 in Part 3) 
• 	 Reference Coordinate System (RCS): The RCS is the spatial coordinate system in a DICOM frame of 
reference. It is the chosen origin, orientation, and spatial scale of an image IE in a Cartesian space.  
The RCS is a right-handed Cartesian coordinate system, that is, the vector cross product of a unit 
vector along the positive x-axis and a unit vector along the positive y-axis is equal to a unit vector 
along the positive z-axis. The unit length is 1 mm. 
• 	 Fiducial: A fiducial is some unique feature or landmark suitable as a spatial reference or correlation 
between similar objects. The fiducial may contribute to the definition of the origin and orientation 
of a chosen coordinate system. Identifying fiducials in different data sets is a common means to

of a chosen coordinate system. Identifying fiducials in different data sets is a common means to 
establish the spatial relationship between similar objects. 
• 	 Fiducial point: A fiducial point defines a specific location of a fiducial. A fiducial point is relative to 
an image or to an RCS (Figure 8.6). 
Individual image data elements, described in more detail in Part 7, contain tag, value, value length, and 
value fields to represent distinct image information. Figure 8.7 lists some of those reference tag numbers.  
Some of those tags that define image metadata, that is, data that describe the patient’s age, weight, etc., 
are illustrated in Figure 8.7. 
FIGURE 8.6 (See color insert.) Reference coordinate system diagrams relating scanners and individual 2D 
slices. (Source: Image from http://www.slicer.org/slicerWiki/index.php/Coordinate_systems) 
FIGURE 8.7 Image  Metadata

Value (optional) Value Value Tag Value fields can be nested representation length field(s) 
Data Data 
element element Data element value 
tag length 
First item Second item Third item 
(gggg,
eeee) with
VR of SQ 
00000F0 
0H 
Item Item Item Item Item Item Item Item Item 
tag length value tag length value tag length value 
(FFFE,
E000) 
0000 
04F8H 
Data 
Set 
(FFFE,
E000) 
0000 
04F8H 
Data 
Set 
(FFFE,
E000) 
0000 
04F8H 
Data 
Set 
4 4 4 4 04F8H 4 4 04F8H 4 4 04F8H 
bytes bytes bytes bytes bytes bytes bytes bytes bytes bytes bytes 
Imaging	 231 
8.2.1.4 DICOM Part 5: Data Structures and Encoding 
DICOM Part 5 standard describes the interchange of information between digital imaging systems; it 
covers the protocols and data sets referred to as “application entities.” 
These include (http://medical.nema.org/Dicom/2011/11_05pu.doc)
 1.  Encoding of values 
 2. Structure and usage of a data set
 3.  Data element usage and relationships to other elements

1.  Encoding of values 
 3.  Data element usage and relationships to other elements 
 4. Construction and usage of nested data sets 
 5. Construction and usage of data sets containing pixel data
 6.  Uniquely  identify information 
 7. Specification of the standard DICOM transfer syntaxes 
Here are the definitions of the aforementioned entities:
 1.  A  data set is constructed of data elements.
 2.  A  data element is uniquely identified by a data element tag (Figure 8.8).
 a.	  Standard data  elements have an even group number that is not (0000,eeee), (0002,eeee),  
(0004,eeee), or (0006,eeee).
 b.	  Private data  elements have an odd group number that is not (0001,eeee), (0003,eeee),  
(0005,eeee), (0007,eeee), or (FFFF,eeee). 
Nested value elements  provide an encoding scheme that can be used for structures of repeating sets of  
data elements or more complex IODs often called folders. Data elements can also be used recursively to

data elements or more complex IODs often called folders. Data elements can also be used recursively to 
contain multilevel nested structures (Figure 8.8). 
 3. Pixel and overlay data and related data elements 
  The pixel data element (7FE0,0010) and overlay data element (60xx,3000) can be used for the 
exchange of encoded graphical image data.
 
  Encoded pixel data of various bit depths shall be accommodated. The following three data elements
  
define the pixel structure:
 a.	  Bits allocated (0028,0100)
 b.	  Bits stored (0028,0101)
 c.	  High bit (0028,0102) 
FIGURE 8.8 Nested value filed.

4. Overlay data encoding of related data elements 
  Encoded overlay planes always have a bit depth of 1 and are encoded separately from the pixel data  
in overlay data (60xx,3000). The following two data elements define the overlay plane structure:
 a.  Overlay bit allocated (60xx,0100)
 b.  Overlay bit position (60xx,0102) 
This standards document focuses on specifying data structures and data elements and the tag elements. 
Complex nested data elements are used to specify layers of each image in a concise hierarchical structure. 
8.2.1.5 DICOM Part 6: Data Dictionary 
This standard provides definitions for data tags, structured elements, and color palettes used for defin­
ing data sets. A representative group is included to illustrate this data dictionary.
 
Tag:  Tag is a unique identifier (UID) for an element of information composed of an ordered pair of 
numbers (a group number followed by an element number), which is used to identify attributes and 
corresponding data elements.

•	  A data element tag is represented as (gggg,eeee), where gggg equates to the group number and  
eeee equates to the element number within that group. (Table 8.3) 
TABLE 8.3 Representative Data Element Examples 
Identifying Information 
Tag Name 
(0008,1060) Name of physician(s) reading the study 
(0008,1070) Operator’s name 
(0008,1080) Admitting diagnosis description 
Manufacturer and Contrast Dye Information 
(0008,1090) Manufacturer’s model name 
(0008,2259)	 Anatomic Location Of Examining Instrument Code 
Sequence (Trial) 
(0008,9209) Acquisition contrast 
(0018,1044) Contrast/bolus total dose 
(0018,1043) Contrast/bolus start time 
(0018,1043) Contrast/bolus stop time 
Image Coordinate System 
(0014,0023) CAD file format 
(0014,2208) Coordinate system, data set mapping 
(0018,0015) Body part examined 
(0018,0087) Magnetic field strength

(0018,0087) Magnetic field strength 
(0018,1405) Relative x-ray exposure 
(0018,9325) CT x-ray detail sequence 
(0018,9732) PET frame acquisition sequence 
(0028,0040)	 Image format 
(0046,0012)	 Lens description 
(0046,0014) Right lens sequence 
(0046,0015) Left lens sequence 
(0046,0040) Optical transmittance 
(0048,0000)	 Imaged volume width 
(0048,0001) Imaged volume width 
(0048,0002) Imaged volume height 
(0048,0003) Imaged volume depth 
232 Biomedical Informatics

Data Set (DICOM) 
Data element Data element	 Data element 
Tag Value (optional) Value Value field 
(pair of 16 bit representation length (even number of bytes containing)
un-signed numbers) (two byte char string) (16 or 32 bit) the value of the data element 
Example:
 
(0004,0010) US 2 [YBR_Full 123]
 
Imaging	 233 
8.2.1.6  	DICOM Part 7: Message Service Elements (http:// 
medical.nema.org/Dicom/2011/11_05pu.pdf) 
The DICOM Part 7 standards illustrate the transmission of images, using DICOM Message Service 
Elements (DIMSEs). The tags in the data sets describe categories of information in particular data set  
fields accompanying the image. 
Some of those standards include the following: 
 1. Data elements and field structures
 a.	  Data  types
 b.	  Data elements 
 i.  A data element is uniquely represented by a data element tag (Figure 8.9). 
 ii. Standard data elements have tags that have even group numbers. 
 iii. 	Private data elements have odd group numbers.

ii. Standard data elements have tags that have even group numbers. 
 c.	  Value  representation 
 d. 	 Each of these tags has a unique meaning: that is, it explains the context of the subsequent data 
fields. Some examples are:
 i.  (0008,0105)  DCMR  = DICOM Content Mapping Resource 
 ii. (0008,2228) Primary Anatomic Structure Sequence 
 iii. 	(0018,0029) Intervention Drug Code Sequence 
 iv. 	(0040,0300) Total duration of x-ray exposure (in seconds) 
 I.  (0018,1110) distance in mm from source detector (SID) 
 II. 	(0040,0303) dimension of exposed area at the detector plane 
 III. 	(0040,0301) total number of exposures (CT scan multiple slices) 
 2.  Encoding of pixel, overlay, and waveform data
 3.  UIDs 
 4. Transfer Syntax (encoding rules for the data set) 
 a. 	 Transfer Syntax for Lossless JPEG Compression 
 b.	  Transfer Syntax for Run Length Encoding (RLE)  Compression

a. 	 Transfer Syntax for Lossless JPEG Compression 
 b.	  Transfer Syntax for Run Length Encoding (RLE)  Compression 
 c.	  Transfer Syntax for MPEG2 MP@ML Image Compression 
 d. 	 Transfer Syntax for MPEG-4 AVC/H.264 Image Compression 
8.2.2 NIfTI Data Format 
Neuroimaging Informatics Technology Initiative (NIfTI) is an initiative of the National Institute of 
Health (NIH) and the National Institute of Neurological Disorders and Stroke to spur research into 
FIGURE 8.9 Data element example.

Objectives of NIfTI Operating Principles of NIfTI Significance of NIfTI 
1. Enhancement of existing informatics 
tools used widely in neuroimaging 
research 
2. Diss
emination of neuroimaging 
informatics tools and information 
about them 
3. Community-based approaches to 
solving common problems, such as lack 
of interoperability of tools and data 
4. Unique training activities and research 
career development opportunities to 
those in the tool-user and tool-
developer communities 
5. Research and development of the next 
generation of neuroimaging 
informatics tools 
1. Guidance through close and ongoing 
communication with the tool-user 
and tool-developer communities 
2. Intellectual property rights and 
credit for tools to remain with 
original authors 
3. Coordination within NIfTI and 
across other related programs and 
activities 
4. Optimal mechanism to be used for 
each activity, drawing from both 
intramural and extramural resources 
5. Involvement of multiple institutes at

5. Involvement of multiple institutes at 
NIH 
1. More useful and useable 
neuroimaging informatics tools 
2. One-stop resource for 
and information about them 
3. Environment to facilitate 
convergence on common 
solutions to widespread problems 
4. Maximize scientific opportunities 
from neuroimaging research 
Source: NIfTI (http://nifti.nimh.nih.gov/). 
TABLE 8.5 Structure of the Analyze Data Format 
234 Biomedical Informatics 
TABLE 8.4 Neuroimaging Informatics Technology Initiative Charter 
neuroimaging tools. This effort has focused initially with the functional MRI (fMRI), that measures  
brain activity and cerebral blood flow. The organization efforts include standardizing fMRI data for­
mats that vary widely (Table 8.4). 
8.2.3 Analyze Data Format

8.2.3 Analyze Data Format 
The Analyze-7.5 fMRI imaging format stores imaging data in a volume and pixel (voxel) format 
(Figure 8.10); its position is defined relative to other 3D elements and is specifically suited to represent­
ing elements with empty space that are not uniformly spaced (Table 8.5). 
Voxels: defined by
relative positions 
Consists of two data items Analyze software:
A = read (”neuro1MRI”); 
    the binary picture data B = Analyze(”neuro1MRI.hdr)
1. Name.IMG contains
”convert to DICOM files
 
header and file
2. Name.hdr has the y 
x dicomwrite(A, map, neuro1MRI)
 information has the
z Metadata = dicominfo (A, neuro1MRI.dcm) 
    voxel size 
FIGURE 8.10  Voxel fMRI image elements. An individual voxel element is highlighted. 
Analyze Format 
Header files.HDR Image type, size, and attributes 
File.IMG Raw data file 
Extension.lkup Color lookup file 
Voxel formats 8 bit unassigned 
16 bit signed 
24 bit RGB

24 bit RGB 
32 bit signed integers or floating point

X-ray 1895–1903 CT(contrast)1972–1980 MRI (1946–1977) fMRI 1990s Whole body scans 21st (HARDI) High Angular
Resolution Diffusion Imaging 
Hold 
head 
stable 
 
Imaging 235 
8.2.4 Additional Data Formats 
• Network Common Data Form (NetCDF) supports array-oriented scientific data. 
• Hierarchical Data Format (HDF4 or HDF5) stores large numerical data sets. 
• Image Cytometry Standard (ICS) is used in microscopy. 
• Layered Image File Format (LIFF) is a file format microscope image processing. 
• Adobe (PSD) file images with unlimited amount of colors. 
8.3 Medical Imaging Technologies 
This section describes a number of imaging technologies: x-rays (2D), CT scanner (multiple 2D x-rays 
merged into 3D view ), MRI ( soft tissue visualized in 3D that uses a superconducting magnet ), fMRI  
(measures brain activity), and more recent whole body scans for pre-screening and security applications 
(Figure 8.11). 
8.3.1 X-Rays

8.3.1 X-Rays 
X-rays, the first noninvasive medical imaging technology, which creates a 2D image, were discovered by 
Wilhelm Röntgen in 1895 for which he later won the Nobel Prize. W. D. Coolidge created the x-ray tube  
in 1903 that made x-ray use in medical devices practical. X-rays have a shorter wavelength and higher 
energy than visible light that makes them capable of passing through soft tissue. X-rays are absorbed 
by denser structures, such as calcium in the bones (white areas are places X-rays blocked ) (Figure 8.12). 
8.3.2 Computed Tomography 
CT or computed axial tomography (CAT) was invented in 1972 in England by Godfrey Hounsfield who 
later received the Nobel Prize. Alan Cormack, a South African, is also credited with its CT invention. It uses

later received the Nobel Prize. Alan Cormack, a South African, is also credited with its CT invention. It uses 
numerous 2D x-ray slices, to create a 3D view of the body (also referred to as CAT scan) (see Figure 8.12). 
Most scans are taken with contrast dye to enhance the image such as an iodine-based dye that is injected or 
a barium sulfate to image the digestive system. Contrast dyes change the magnetic properties of tissues by 
highlighting soft tissue [1]. The dye absorbs photons and blocks them from being detected by the CT scan­
ner. Ionizing radiation can cause cancer and damage DNA. Since CT scans take numerous 2D x-ray slices 
to form a 3D image, it subjects a patient to 100 to 5000 times more radiation than standard x-rays, but it is 
believed that the benefits outweigh the risks. A Scientific American article in 2013 estimates from 2007 to 
2013 “29,000 future cancers will develop from the 72 million CT scans performed,” that is, approximately

2013 “29,000 future cancers will develop from the 72 million CT scans performed,” that is, approximately 
1 chance of developing future cancers in every 50,000 CT scans (http://www.scientificamerican.com/article/ 
how-much-ct-scans-increase-risk-cancer/). Manufacturers continue to try to reduce radiation exposures. 
Magnetic resonance imagers do not produce ionizing radiations, but just strong magnetic fields, which at 
present don’t have similar side effects and appear to be inherently safer (Figure 8.13). 
In order to reconstruct or assemble multiple 2D slices, the exact position of the beam must be relative 
to the isocenter, that is, the center of the beam on the patient; it is essential to the final reconstruction of 
FIGURE 8.11 (See color insert.) Evolution in medical imaging technology.

X-rays are 1,000 times
smaller than visible light X-ray Visible light 
and higher energy that (high energy) (lower energy level) 
allows them to penetrate
soft tissue. Calcium in 
bones absorbs more x-
rays than soft tissue.
Photoelectric absorption Smaller wavelengthis the method used by Longer wavelength 
medical x-rays (Compton 0.01 nm–10 nm 400–700 nm (nanometer)
scattering the other). 
(4) Photon given off (3) Electron returns to
lower shell 
(2) Electron move to the
next shell (quantum level)
 
Photosensitive material(1) X-ray photon collides
with electron 
Photons are given off when: electrons are excited, electrons move
to the next quantum level, electrons return to their original state
they then give off 1 photon of energy 
3D computed tomography (CT) scan 
2D x-ray 
Individual 2D 
Essentially slices taken then 
X-ray creates 2D assembled into 
tube shadow 3D picture Rotating X-ray 2D X-ray slice source

2D x-ray 
tube shadow 3D picture Rotating X-ray 2D X-ray slice source 
Calcium in bones absorbs X-rays, soft tissues X-rays pass through 
The contrast dyes, iodine and barium sulfate, absorb
x-ray photons: highlight and change magnetic
 Isocenter properties of the different layers of tissue. 
236 Biomedical Informatics 
FIGURE 8.12  X-ray imaging and photoelectric absorption. 
FIGURE 8.13  CT scan and 3D scan created by assembling numerous 2D images. 
the 3D image. The DICOM tag, in Section 2.2.1 for the isocenter, is (0018,9402) and the isocenter primary 
angle tag is (0018,9463) of the X-ray beam (Figure 8.14). 
8.3.3 MRI 
Magnetic Resonance Imaging (MRI) or nuclear MRI was shortened to address the worries of individu­
als regarding the term nuclear. In 1946, Edward Purcell and Felix Bloch discovered magnetic resonance

als regarding the term nuclear. In 1946, Edward Purcell and Felix Bloch discovered magnetic resonance 
of atoms and received the Nobel Prize in 1952. The first commercial machines appeared in the late 1970s.

Superconducting MRI components 
magnet 1. Magnets 
a. Superconducting magnet (in liquid helium at –452 deg.
fahrenheit) At 20,000 gauss (earth magnetic field is 0.05 gauss)
Radio frequency b. Resistive magnets few: (non superconducting)Gradient magnets (RF) coils c. Gradient magnets around patient to scan different body parts
2. Radio frequency coils transmitted into the patient
3. Computer processing system
4. Positioning system (patient moved to the isocenter of the magnetic field ) 
Isocenter of MRI 
MRI atomic spin (hydrogen atoms)
X 
5. Magnetic field activated, random spin atoms align either north or southDetectors: when 6. Radio frequency (RF) turned on and atoms spin in reverse directionhydrogen atoms 7. When RF turned off and atoms return to previous spin they give offreturn to original spin  energy picked up by a detectorstate: give off energy ©Lubliner 2013 
N5. Atoms N Atom 6. Atoms 7. Atoms return N Atom2 Atom 
2 Atomalign Atom reverse spin Atom previous state 2

2 Atomalign Atom reverse spin Atom previous state 2 
magnet on release energy 11 RF on 1 
S 
E E 
 
Gravity
Plane 
Gravity
(downward) 
+X 
+Y 
Isocenter coordinate system 
1. Origin O 0, is the origin of the Isocenter coordinate system O
2. X 0 axis is parallel to the horizontal scan-lines of the detector
(rows). Positive direction from left to right of the detector
plane looking towards the source.
3. Z 0 axis is parallel to the vertical scan-lines of the detector
(columns). Positive direction from bottom to top of the
detector plane looking towards the source.
4. Y
0 is the axis from the isocenter to the X-ray source.
The positioner coordinate system (O0, X0, Y0, Z0) is defined as
follows: 
+Z 
+Z 
O 
Yp 
Isocenter 
X-ray source 
X-ray 
+X 
+Y 
O 
Isocenter secondary = 0 
Isocenter 
primary = +90Isocenter 
secondary = +90 
Ap3 
Ap2 Ap1 
center 
beam 
Isocenter primary = 0

X-ray 
+X 
+Y 
O 
Isocenter 
Ap3 
Ap2 Ap1 
center 
beam 
Isocenter primary = 0 
Isocenter angles	 Positive direction from the Isocenter to the X-ray source.
This axis is so-called the X-ray center beam.
Source: DICOM Part 3 “Information Object Definitions 
Imaging	 237 
FIGURE 8.14  Determination of the isocenter of x-ray beam for CT scanner. ( Source: DICOM whitepaper Part 3.) 
FIGURE 8.15  Magnetic resonance imaging progression. 
An MRI produces a magnetic field that excites hydrogen atoms’ electrons; that is, electrons are in 
fixed orbits but when excited, they move to a higher shell. When they return to their original shells, 
energy is given off. MRIs utilize nonionizing absorption and emission in the radio frequencies and are 
best suited for noncalcified tissues, that is, soft tissues (Figure 8.15). 
In order to reconstruct or assemble multiple 2D slices, the exact position of the beam must be relative

to the isocenter, that is, the center of the beam on the patient; it is essential to the final reconstruction 
of the 3D image. 
Magnetic gradients are generated by three orthogonal coils, oriented in the x, y, and z directions of 
the scanner. These are usually resistive electromagnets powered by amplifiers that permit rapid and pre­
cise adjustments to their field strength and direction. The straightness of flux lines within the isocenter 
of the magnet needs to be almost perfect. In 1983, Ljunggren [8] and Tweig [9] independently introduced

∫ 
� 
3 � � 
d x ρ ( x ) ⋅e 2π�kt() ⋅x
MRI is essentially the manipulation of spins  within a strong magnetic field, which then return to 
an equilibrium state and give off energy that can be detected. Particle spin is a mathematical descrip­
tion of the quantum mechanical state of the atom. A positively charged sphere, the proton, of radius  
~10–14  m, mass ~10–27 kg, and a net electric charge ~10–19  C spins and possesses a magnetic dipole moment 
(Figure 8.16). 
8.3.4 Functional  MRI 
In the 1990s, the fMRI measures brain and neural activities by alterations in blood flow. The core mech­
anism measures variations in oxygen level in the blood by color coding results over a short period that 
is usually in seconds. These measurements are taken in parallel with electroencephalography and other 
various measurement techniques such as near-infrared spectroscopy that dynamically measures hemo­
globin levels. It most often used in research settings. 
8.3.5 SPECT Imaging

8.3.5 SPECT Imaging 
Single-Photon Emission Computed Tomography (SPECT) imaging technique uses ionizing radiation, 
gamma rays, a radioisotope tracer, and blood flow measuring in capillaries. It is similar to a positron 
emission tomography (PET) scanner that allows functional studies over time. The radionuclide tracer 
technetium-99m (
99mTc) tetrofosmin is used to visualize cardiac blood flow over a 10–20 s time period. It 
is used with an EKG to trigger SPECT imaging: that is, if there were electrical abnormalities, the SPECT 
could calculate the ejection fraction of the ventricles, that is, the efficiency of the ventricles. 
The advantages of SPECT are that it can be used to observe biochemical and  physiological  
processes as well as size and volume of the organ (http://www.nlm.nih.gov/cgi/mesh/2011/ 
MB_cgi?mode=&term=SPECT).

Imaging 239 
8.3.6 Ultrasound 
Ultrasound uses sound waves to visualize soft tissue. The high-frequency waves can track movement in 
real time by measuring the amplitude and frequency of the returning sound waves utilizing the Doppler 
effect, that is, the positive frequency shift if the object is moving toward you and the reduction in fre­
quency as the object moves away. The Doppler effect works in other mediums besides sound, light,  
and water. In light, a blueshift is observed, if an object moves closer, and a redshift is moving away 
(Figure  8.17): 
V Object moving toward you f ′= × fVV− s
V Object moving away from yoy u f ′= × f
 VV+ s
where 
V is the velocity of sound 
Vs is the velocity of source 
f is the real frequency 
f’ is the apparent frequency 
8.3.7 Positron Emission Tomography 
PET is a nuclear medicine medical imaging technique that produces a 3D image or map of func­

tional processes or metabolic activities in the body. To conduct the scan, a short-lived radioactive  
tracer   isotope , which decays by emitting a positron which also has been chemically incorporated into  
a metabolically active molecule, is injected into the living subject (usually into blood  circulation)  
(Figure  8.18). The data set collected in PET has a lower resolution than CT, so reconstruction 
techniques are more difficult. 
8.3.8 Digital Radiography/Computed Radiography 
Digital radiography replaces photographic film with x-ray sensors. It is used primarily by dentists but is 
also used by conventional x-rays and its advantages are fourfold. 
1. Less radiation is needed then by a comparable film-based system. Depending on the technology, 
50%–90% less radiation is needed than standard analog x-rays. Flat panel detectors (FPDs) using

50%–90% less radiation is needed than standard analog x-rays. Flat panel detectors (FPDs) using 
amorphous silicon, primarily, convert images in a digital format. Radiation dose per person from 
medical x-rays has decreased almost 500% since 1982. 
Car moving away Car moving toward you
wavelength longer wavelength shorter 
Wavelength 
Amplitude' 
FIGURE 8.17 Example of the Doppler effect.

240 Biomedical Informatics 
Coincidence 
processing unit Photomultiplier 
Scintillator 
crystals 
Sinogram/ Detectorlistmode data 
rings 
Detector block 
Annihilation Image reconstruction 
FIGURE 8.18  PET scan. (Source: Images from the Max Planck Institute for Neurological Research, http://www. 
nf.mpg.de/index.php?id=78&L=1;   http://en.wikipedia.org/wiki/Position_emission_tomograph#/media/File:PET­
schema.png.) 
The unit of measurement for an effective radiation dose is the millisievert (mSv). The average   person in  
the United States receives a dose of about 3 mSv per year from naturally occurring radiation. (http:// 
www.webmd.com/fda/reducing-radiation-from-medical-xrays) (digital dental x-ray 0.005 mSv.)
 a.	  The small risk of cancer depends on several factors (webmd.com): 
 i.	  The lifetime risk of cancer increases as a person undergoes more x-ray exams and the 
accumulated radiation dose gets higher.

i.	  The lifetime risk of cancer increases as a person undergoes more x-ray exams and the 
accumulated radiation dose gets higher. 
 ii. 	 The lifetime risk is higher for a person who received x-rays at a younger age than for 
someone who receives them at an older age. 
 iii. 	 Women are at a somewhat higher lifetime risk than men for developing cancer from  
radiation after receiving the same exposures at the same ages. 
 b. 	 A typical x-ray produces 2–3 mrem (a millirem is 1/1000 of a rem) 
 c.	  The National Council on Radiation Protection estimates we receive 360 mrem every year  
from background radiation (Figure 8.19). 
 2. Second speed results can be instantly obtained. 
 3.  For electronic health records (EHRs), once in a digital format, they can be incorporated in EHRs  
and billing expedited. 
 4. In image processing, digital images have a wider range of values and can be dynamically enhanced  
to visualize disease. 
8.3.8.1 Digital Panoramic X-Rays

8.3.8.1 Digital Panoramic X-Rays 
A digital panoramic x-ray, which is most often used by dentists but is also utilized in security scanners, 
provides a broad view of teeth and mandible (jaw) in one 120°–180° sweep (.03 mSv) (Figure 8.20). A 
rotating x-ray camera produces numerous images, from individual 2D slices, similar to a CT scan. 
The advantages include a broad view of entire mouth, bones, and teeth, without inserting dental  
film, which is a diagnostic technique for facial trauma, cancer detection, and pain causality such as  
temporomandibular joint dysfunction and orthodontic assessment. The disadvantages include poorer  
resolution, overlapped teeth, and distortions due to changing focal lengths during exposure. It does  
not provide detailed information about the soft tissues and muscles; a MRI scan would be required.

Space
(background)Internal (5%) (background)
(5%)
Random and thoron
(background)
(37%)
Reprinted with permission of the National 
Council on Radiation Protection and 
Measurements, http://NCRPonline.org 
Temestrial
(3%)
Computed
tomography
(medical)
(24%)
Nuclear medicine
(medical) (12%) 
Industrial (< 0.1%)
Occupational (<0.1%)
Consumer (2%)
Conversional 
radiography fluoroscopy 
(medical) (5%)Interventional
fluoroscopy
(medical) (7%)
Sources of Radiation Exposure
From: NCRP Report No. 160
Figure Reprinted with permission of the National Council on Radiation Protection and Measurements. 
Radiation doses from imaging technologies
(American College of Radiology ACR.org)
Scales:
(milliSievert)
mRem = 1/1000 Rem
mSv = 1/1000 Sievert (Sv) 
Conversion 1 Sv = 100Rem 
1mSv = 100mRem ©Lubliner 2013
Average Annual Dose (ACR.org)
(daily exposure environment)
6.2 mSv 620 mRem/year 
X-ray 0.02 mSv 2–3 mRem
CT (multiple 2D x-rays) body 10 mSv 1000 mRem

CT (multiple 2D x-rays) chest 8 mSv 800 mRem
Mammography 0.7 mSv 70 mRem
 FIGURE 8.19 Ye arly radiation dosages and a comparison of ionizing radiation dosages from diff erent imaging systems. 
Imaging 241

242 Biomedical Informatics 
http://www.dentalcare.com/enUS/dentaleducation/continuingedu
cation/ce71/ce71.aspx?ModuleName=coursecontent&PartID=4
&SectionID=0
 
Wikipedia commons 
FIGURE 8.20  Panoramic x-rays, process schematic, and then representative image. 
Level II: Implementing and Integrating Imaging Data 
8.4 Picture Archiving and Communication System
 
Picture Archiving and Communication System (PACS) is a storage and retrieval system for medical 
images. A PACS system is used for transmitting, accessing, and displaying medical images. 
DICOM is the standards format for PACS. It defines communications, messaging and data elements, 
and the data dictionary. Databases such as Oracle and DB2 have embedded translational tables to incor­
porate DICOM queries and management. The DICOM tags (0010,0011), for example, can be queried via 
C-Find and C-Move scripts. 
An example of an IBM (WebSphere) DB2 query illustrates their find/move commands (Figure 8.21):

An example of an IBM (WebSphere) DB2 query illustrates their find/move commands (Figure 8.21): 
• Search parameters are patient name tag (0010,0010) → followed by the element value. 
• Access number tag (0008,0050) → followed by the element value. 
DB2 Web Sphere DICOM query code taken from http://pic.dhe.ibm.com/infocenter/wmbhelp/v8r0m0/ 
index.jsp?topic=%2Fcom.ibm.healthcare.pattern.DICOM.doc%2Fpattern%2Fexamples.htm 
The Oracle architecture utilized the DICOM standards to first create a data dictionary, all stan­
dards tag   names (xxxx, yyyy), making elements that include values associated with these example tags  
[(0010,0014),US,2, YBR_Full123] and then converted into the SQL query code for each database (Figure 8.22). 
example shows an XML query message with two search tags of 00100010 
(PatientName) and 00080050 (AccessionNumber), and an additional return tag 
configured of 00080054 (RetrieveAETitle):

<DICOM:FindMove xmlns:DICOM="http://com.ibm.healthcare/DICOM">
 <QueryRoot>STUDY</QueryRoot>
 <QueryLevel>STUDY</QueryLevel>
 <Match>
 <Attribute Tag="00100010">FEROVIX</Attribute>
 <Attribute Tag="00080050">1210490</Attribute>
 </Match>
 <Return>
 <Attribute Tag=“00080054”/>
 </Return>
 
</DICOM:FindMove>
 
FIGURE 8.21  XML query code example.

Oracle Database
JVM
DICOM Repository
DICOM DICOM ImageDICOM XML conformance processorparser validatorencoder JAI 
X-ray 
JPEG
thumbnail 
Table 
US 
XMLMR metadata
<XML>
http://docs.oracle.com/cd/E11882_01/appdev.112/e10778/c
h_cncpt.htm#IMDCM13322 
DICOM Interface 
Data Mapping
Dictionary Element
 
DICOM data element
Element Element Element
(0010,0010) PN 25 Sue Smith 
(0010,0040) CS 2 F 
XMLParser encoder
(PACS) 
XML Metadata
Schema
XML Validate
<DICOM>
<Patient>
<Name> Sue Smith
</Name>
<Sex> F </Sex>
</DICOM> 
. pt nc c _ h c 8/ 7 7 0 e1 / 2 1 1 . v e d app / 1 _0 82 18 1 E / d c / om .c le c a or . s c o d / / : p t t e h id  Gu r e lop ve e M D O C I le D c a r e O h : From tce r u So. ( le c a r n O g a n i z i l i S ut C A
) 5
P22  
332 1
.
M
 8
C D
E R
M
U
I #
G
m
FI
ht
Imaging 243

244 Biomedical Informatics 
The Health Insurance Portability and Accountability Act (HIPAA) created a PACS standard for 
insuring the security of PACS images. The standard is independent of an individual PACS system. The 
HIPAA specification defines an action layer, notification layer, and audit and record layer illustrated in 
Figure 8.23:
 1. The first layer (the lowest layer) is the record layer, consisting of various logs within PACS compo­
nents. By logically separating PACS logs from other logs and layers, independence from PACS and 
portability can be achieved.
 2. The second layer is the audit layer, which includes a centralized auditing database and other audit 
data analysis and interpretation tools. HIPAA-compliant audit trails can be generated based on the 
auditing database. This layer also enables us to automatically monitor the data flow of PACS, which 
greatly assists PACS management.

 3.	 The third layer is the notification layer, which has a notification component sending warning or alert 
messages of abnormal events to end users, such as PACS administrators.
 4. In the fourth layer, end users can decide to take certain actions against these abnormal events. 
8.5 Teleradiology 
Teleradiology is defined as the process of sharing and analyzing imaging data from a distant location 
from the original imaging data capture. Medicare and Medicaid require all teleradiology activities be 
conducted in the United States for reimbursement. The systems that transmit and receive these images 
must be HIPAA Type II compliant, especially regarding the security of the images. This allows special­
ists in subfields to provide expert opinions 24 hours a day. Teleradiology spawned a number of radiology

ists in subfields to provide expert opinions 24 hours a day. Teleradiology spawned a number of radiology 
consulting groups as a way of outsourcing imaging analysis. These radiology consulting groups are bil­
lion dollar businesses. The Radiology Business Journal  (http://www.desertradiology.com/files/dec_2013. 
pdf) in December 2013 ranked the top 100 firms containing board certified radiologists totaling over 
5,000 just in this top 100 ranking group. There seems to be an effort to consolidate and its estimated 
groups of 250 radiologists will appear in the near future. The chart (Figure 8.24) lists the top 10 radiology 
groups as of December 2013. 
8.6 CLEF 
The Conference and Labs of the Evaluation Forum (CLEF) focuses on how to facilitate systems that can 
annotate and access imaging data in multiple languages, focusing on European Languages. ImageCLEF 
(http://imageclef.org/) is a forum that specifically focuses on imaging data cross language and indepen­

dent contexts. (It was previously named the Cross Language Evaluation Forum). 
8.6.1 ImageCLEF Tools
 1. The GNU Image-Finding Tool is an open framework system. Gnu’s Not Unix, a UNIX-like operat­
ing system, incorporates tools to query images (http://www.gnu.org/software/gift/). It allows you 
to create your own index of images (Figure 8.25). 
a. 	 It incorporates content-based image retrieval, using a computer vision paradigm that searches 
for shapes, colors, etc., as opposed to specific tags or text data. It provides a library to facilitate 
searching parameters. It also has a distance measure tool, that is, how close the image is to 
some standard image provided. For example, color proportion, shape, or texture can be used. 
Skin cancer shades and irregularity of borders can be an indicator of a malignant tumor.

Skin cancer shades and irregularity of borders can be an indicator of a malignant tumor. 
2. Lucene Image Retrieval (LIRE) are open-source image retrieval libraries that create an index of 
medical images based on visual features such as color and texture.

Action layer Event Patient
PK Event No
Action 
PK Patient_No PK 
0..n 0.1 0.1 0..nEvent_Type Patient_Name
Event_Location Patient_IDNotification layer Event_Time Patient_Sex
Event_Status Patient_Age FK1 Event_User
FK1 Patient_No 
Notification 
Audit layer Monitor tool
Role-based Policy-based PACS Simulator w/ Audit Log Implemented
policy decision tree 
AcquisitionDisaster DICOMModalty PACS Controllerpolicy Simulator Gateway 
Audit analysis tool Audit log Audit logNormal Audit logcollector collectorpolicy collectorIntrusion detection
Auditing
database H-CAS 
Log data
normalizer
Syslong server
Audit log
collector 
Record layer
PACS App. PACS user Image integrity Computer
logs login logs log system logs
 
Study
Study_No
Study_InstancelUID
Accession_Number
Meddlity
Patient_no
Viewing W.S.
Audit log
collector
GUI
 FIGURE 8.23 HIP AA PACS security standard document at link. (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3045193/) 
Imaging 245

2013 
rank Practice Location CEO Lead physician Lead nonphysician 
2013 FTE 
radiologists 
1 Radiology Associates of North Texas PA Fort Wo rth, TX Mark J. Kleinschmidt David Phelps, MD Mark J. Kleinschmidt 124 
2 Advanced Radiology Services PC Grand Rapids, MI Richard Moed Steven Waslawski, MD 111 
3 Integra Imaging PS Spokane, WA Steve Duvolsin Jayson Brower and Kristin Manning Steve Duvolsin 97 
4 Radia Medical Imaging Everett, WA Bart Keogh, MD, PhD Bart Keogh, MD, PhD 97 
5 Advanced Radiology PA Baltimore, MD David Saff erman, MD Kenneth E. Ames 94.25 
6 Austin Radiological Association Austin, TX Doyle W. Rabe Gregory C Karnaze, MD Doyle W. Rabe 86.05 
7 Charlotte Radiology Charlotte, NC Mark Jensen Robert Mittl Jr, MD Mark Jensen 84.5 
8 University Radiology Group East Brunswick, NJ Thomas Dunlap Robert E. Epst ein, MD Thomas Dunlap 83 
9 Radiology Imaging Consultants SC Harvey, IL Jay Bronner, MD Ja y Bronner, MD, and Perry Gilbert, MD Tara McKennie and Kyle 
Dwolchak 
82

Dwolchak 
82 
10 Fairfax Radiological Consultants PC Fairfax, VA Marshall C. Mintz, MD Lynn Elliott, MBA, CPA 81 
246 Biomedical Informatics 
.) l a n ur o  J s s sine  Bu y og diol a R: The ce r u So. ( 3 1 0 s of 2 s a oup r g g n i t l u s n o l c a ic g iolo d a 0 r op 1 T4  2 .  8 E R U G FI

Isotope Examples (only some isotopes are radioactive, the process by which atoms loose energy by ionizing radiation) 
Symbol Neutrons Protons Natural Abundance on Earth 
Helium-3, He-3 1 2 0.000137% of He Radioactive isotope
 
Helium-4, He-4 2 2 99.9998%
 
Carbon, 12C 6 6 98.89%
 
Carbon-14, 14C, or radiocarbon 8 6 0.0000000001% Radioactive (used for carbon
 
1 part per trillion dating) 
Imaging 247 
FIGURE 8.25  (See color insert.)  Indexing images, ImageCLEF tools by shape, color, or texture. 
8.7 Radio Pharmacology
 
Radio pharmacology is the field of study focusing on radio isotopes used in medical imaging. Many 
radiopharmaceuticals incorporate radioactive isotopes; isotopes have the same number of protons in 
each atom but they have a different number of neutrons. The atomic number is the number of protons 
of an atom, which determines the position in the periodic table, so isotopes maintain their same posi­

tion in the Table 8.6 (i.e., the number of protons and electrons in an atom is equal to maintain a zero net 
charge). On the other hand, the mass number incorporates neutrons so mass numbers of isotopes vary 
for elements. Examples are Helium-3 (He-3) nonradioactive isotope with two protons and one neutron. 
Specific radioisotopes are used as tracers to diagnosis [7]. The factors that determine specific radio­
isotopes are such as adsorption, distribution, metabolism, and excretion of various 
99mTc complexes: 
“Technetium-99m is the most widely used radioisotope in diagnostic nuclear medicine; it is being  estimated 
that over 80% of the nearly 25 million diagnostic nuclear medicine studies carried out annually are done 
with this single isotope” (Table 8.7) (http://www.iaea.org/About/Policy/GC/GC51/GC51InfDocuments/ 
English/gc51inf-3-att2_en.pdf). 
8.8 Digital Imaging Analysis

8.8 Digital Imaging Analysis 
Digital medical image processing uses algorithms to analyze and interpret medical images. Newer soft­
ware is also available to highlight and enhance anomalies, masses, or tumors, which might be too small 
or difficult to visualize (Figure 8.26). 
The term feature extraction is used to extract or highlight anomalous elements of the image. One 
technique used for feature extraction is the principal component analysis. 
a. It uses orthogonal transformations, i.e., orthogonals are square matrices are used to convert cor­
related variables. A correlation example is a child–parent relationship, into principal components, 
referred to as linearly uncorrelated variables. This principal component has a large variance, that 
TABLE 8.6 Examples of Radioisotopes, Rare Form of Elements

Bone marrow diseases	 1. Sodium chromate
 2. Cr 51 
99mTc albumin colloid
 3. 99mTc sulfur colloid 
Brain diseases and tumors 1. Fludeoxyglucose F 18 
2. Indium In 111 pentetreotide 
3. Iofetamine I 123
 4. Sodium pertechnetate 99mTc
 5. 99mTc exametazime
 6. 99mTc gluceptate
 7. 99mTc pentetate 
Cancers, tumors 1. Fludeoxyglucose F 18 
2. Gallium citrate Ga 67 
3. Indium In 111 pentetreotide 
4. Methionine C 11
 5. Radioiodinated iobenguane 
6. Sodium fluoride F 18 
Colorectal disease 1. 99mTc arcitumomab 
Heart muscle damage (infarct) 2. Ammonia N 13 
3. Fludeoxyglucose F 18 
4. Rubidium Rb 82
 5. 99mTc pyrophosphate
 6. 99mTc (pyro and trimeta) phosphates
 7. 99mTc sestamibi,
 8. 99mTc teboroxime
 9. 99mTc tetrofosmin 
10. Thallous chloride Tl 201 
248 Biomedical Informatics 
TABLE 8.7 Radioisotopes Used for Specific Diagnoses 
Sour
ce: http://www.drugs.com/cons/radiopharmaceutical.html. 
Original waveforms reduction Noisy medical image Dimensionality reduction

Potential 
turnor 
FIGURE 8.26  (See color insert.)  Digital image processing architecture. ( Source: From http://www.ncbi.nlm.nih. 
gov/pmc/articles/PMC3701154/figure/F1/) 
is variables are spread out; a variance of zero means all values are identical. This principal compo­
nent should be responsible for most of the variance in the equation or system.
 b.	  Dimensionality reduction maps a vector from a correlated space to an uncorrelated. We keep only  
those principal component vectors, that is, reduced matrix called dimensionality reduction that is  
also referred to as a high dimensionality data set with high variance. This data set contains clusters  
that are spread out, and that are high variance, if plotted. Dimensionality reduction is also useful

that are spread out, and that are high variance, if plotted. Dimensionality reduction is also useful  
when there are noisy data and a number of independent variables are removed (Figure 8.27).
 c.  Feature extraction: process by which image features are analyzed to determine unique patterns or 
features
 i.	  Corner detection : a feature or endpoint determined by a curvature, that is, any point where a 
figure is no longer flat defined by a radius of curvature or curvature vector that determines 
the change in direction or some arbitrary angle

Digital imaging processing (DIP) 
Web server User interface 
Imaging Database ImageData sets Mobile UIprocessing (pgAdmin) (querying) 
Data handling Pre-tiling Web-based UI 
Direct tiling 
 
Imaging 249 
FIGURE 8.27 Example of dimensionality reduction in signals in mapping. 
 ii. Edge detection: a point, layer, or boundary between two figures, shades, or gradients
 iii. Data mining: determining patterns in large data sets 
8.9 Summary 
Medical imaging and Image analysis algorithms are rapidly evolving, the objective is to provide better 
methods to visualize and extract salient features of images that might not always be caught by radiolo­
gists. Cutting edge research has shown that new cancers can form capillaries in fractal patterns that may 
be a way to detect early cancers. In 2015, 3D printers have created accurate heart models from CT scans. 
An Israeli company, Zebra Medical Vision, in 2015, created a database of 10 million medical images

An Israeli company, Zebra Medical Vision, in 2015, created a database of 10 million medical images 
and new analytical software to compare/contrast this data to new scans, potentially increasing cancer 
detection, advanced visualization software, EchoPixel, was approved by the FDA in 2015 to create holo­
graphic displays of MRI and CT scans. This is a dynamic field that is changing rapidly. 
Questions 
Level I 
 1.  What is DICOM? 
 a.  What critical role does it play in medical imaging? 
 b.  What is DICOM conformance? 
 c.  What are DICOM IODs? 
 d. What are DICOM data structure definitions? 
 e. What is a DICOM data dictionary? 
 f.  What are DIMSEs? 
 i. Deconstruct a DIMSE into its four component tags and value fields. 
 ii. What role do these tags play in imaging information exchange? 
 2. What is a 3D RCS? 
 a.  What role does an RCS play in medical imaging? 
 3. What is an fMRI? 
 a.  What is the NIfTI data format?

2. What is a 3D RCS? 
 a.  What is the NIfTI data format? 
 4. Briefly explain the differences of the different imaging technologies. 
 a. Explain technologies such as x-rays, CT, MRI, fMRI, ultrasound, and SPECT.

250 Biomedical Informatics 
b. What are the criteria used to determine which imaging device you would use? 
c. What imaging device(s) would you use for soft tissue? Explain reasoning. 
Level II 
5. What is a picture archiving system (PACS)? 
a. Relate a PACS to storing and retrieving images using DICOM tags. 
6. What is teleradiology? 
a. How has the practice of radiology changed since the adoption of teleradiology? 
Level III 
7. What is radio pharmacology? 
a. What is the selection criteria for radio isotopes for different medical scans? 
8. What imaging analysis techniques are used to final anomalies on medical images? 
a. Explain the principal component analysis used in imaging. 
Glossary 
Computed tomography (CT or CAT)  uses numerous 2D x-rays slices to create a 3D view of the body. 
Digital Imaging and Communications in Medicine (DICOM) (dicom.nema.org). 
Digital radiography replaces photographic film with x-ray sensors. It is used primarily by dentists, but

Digital radiography replaces photographic film with x-ray sensors. It is used primarily by dentists, but 
is also used in conventional x-rays. 
The  functional magnetic resonance imager (fMRI) ,  in the 1990s, measures brain and neural activities, 
by alterations in blood flow. 
The  GNU Image-Finding Tool is an open framework system  (http://www.gnu.org/software/gift/ GNU). 
Gnu’s Not Unix, a UNIX-like operating system, incorporates tools to query images. It allows 
you to create your own index of images. 
Magnetic resonance image (MRI) or nuclear MRI. MRIs utilize nonionizing absorption and emission 
in the radio frequency and are best suited for noncalcified tissues, that is, soft tissues.
 
Picture archiving and communication system (PACS) is a storage and retrieval system for medical images.
 
Positron emission tomography (PET) is a nuclear medicine medical imaging technique that produces  
a 3D image or map of functional processes or metabolic activities in the body.

a 3D image or map of functional processes or metabolic activities in the body. 
Reference coordinate system (RCS) is the spatial coordinate system in a DICOM frame of reference. 
 1. Intro to CT scanning, (2010). http://www.maximintegrated.com/app-notes/index.mvp/id/4682 
 2. Acharya,	  R. et   al. Biomedical Imaging Modalities, http://www.dtic.upf.edu/~afrangi/ibi/ 
ReviewBiomedicalImaging.pdf. 
 3. Costa, C. et al. Dicoogle - (2010). An Open Source Peer-to-Peer PACS. DICOM open source tools,  
http://www.dicoogle.com/4 
 4. Andriole, K.P. (2006). Overview of medical imaging informatics. In  Advances in Medical Physics . 
A.B. Wolbarst and R. Zamenholf, eds. Madison, WI: Medical Physics Publishing, pp. 201–227.
 5. The Journal of Digital Imaging (JDI) is the official peer-reviewed journal of the Society for Imaging 
Informatics in Medicine (SIIM). 
 6. Imaging formats white paper, http://download.springer.com/static/pdf/546/art%253A10.1007%

 6. Imaging formats white paper, http://download.springer.com/static/pdf/546/art%253A10.1007% 
252Fs10278–013–9657–9.pdf?auth66=1396636285_bcfe1d2e96d08ce02b790afdf3d30c95&ext=.pdf 
 7. The National Isotope Development Center (NIDC). http://isotopes.gov/notice.html 
 8. Ljunggren, S. (1983). Journal of Magnetic Resonance  54, 338–343. 
 9. Tweig, D. The k-trajectory formulation of the NMR imaging process with applications in analysis  
and synthesis of imaging methods.  Med Phys. 1983; 10:610–621.

9 
Ethics
 
Level I: Core Concepts .................................................................................252
 
9.1 	 Introduction ......................................................................................252
 
9.2 	 Hippocratic Oath ..............................................................................252
 
9.3 	 American Medical Association Ethics Groups ............................254
 
Council on Ethical and Judicial Affairs
 
9.4 ANA Code of Ethics .........................................................................256
 
Level II: Medical Ethics Scenarios ..............................................................257
 
9.5 	 Ethical Medical Situations ..............................................................257
 
Reporting Impaired Drivers • Medical Students Performing 
Procedures on Fellow Students • Surgical Placebo • Gifts to 
Physicians from Industry • How to Refer to Medical Students

Physicians from Industry • How to Refer to Medical Students 
in a Clinical Setting • Should Medical Trainees Perform 
Procedures • Resident Questions Order of Attending Physician
 
Level III: Advanced Topics ......................................................................... 264
 
9.6 	 Clinical Decision Support Systems ............................................... 264
 
Neural Networks
 
9.7 Summary ........................................................................................... 266
 
Questions .......................................................................................................267
 
Glossary .........................................................................................................268
 
References ......................................................................................................268
 
251

Medical ethics 
Hippocratic Oath American Medical Association American Nurses Association Ethical case 
(original and revised) (AMA) ethics groups (ANA) ethics group studies 
252 Biomedical Informatics 
9.1 Introduction
 
Ethics defined by the Merriam-Webster dictionary is “A theory or system of moral values” or profes­
sional ethics as “the principles of conduct governing an individual or a group.” Who decides what is  
moral: religions, philosophers, general consensus, or a panel of their peers? Is there an absolute truth? 
Most humans believe it’s ethical to help out one’s fellow individuals without consideration of social sta­
tus, ethnicity, or  cost. The recent supreme court decision King vs. Burwell 2015 indicates we are moving 
toward the ethical and moral high-ground of universal medical coverage for all 
The U.S. Constitution does not specifically enumerate healthcare coverage, but the Supreme Court

The U.S. Constitution does not specifically enumerate healthcare coverage, but the Supreme Court 
decision that upheld the Affordable Care Act (ACA) “National Federation of Independent Business v.  
Sebelius” (2012) sites the Constitution, Article I, Section 8, clause 1, which states, in part, that “[t]he 
Congress shall have Power to lay and collect Taxes,..to… provide for the… general Welfare of the United 
States.” I. Even though they focused on the tax collecting portion in the decision, how do we ethically 
gauge the clause “provide for the general welfare of our citizens”? It seems the founders were grappling 
with the ethical role of government. Biomedical Informatics professionals need to be not only versed  
technically but also in how medicine is ethically applied fairly to all individuals (Figure 9.1). 
Related decisions include the following: 
• 	 The Supreme Court in the 1937 case dealing with the newly enacted Social Security Act. In Steward

• 	 The Supreme Court in the 1937 case dealing with the newly enacted Social Security Act. In Steward  
Machine Co. v. Davis, the court sustained a tax imposed on employers to provide unemployment 
benefits to individual workers. 
• 	 Title VI of the Civil Rights Act of 1964 that prohibits discrimination under federally funded pro­
grams affects the manner of delivery of medical services under federal grants. 
• 	 Congress enacted the Consolidated Omnibus Budget Reconciliation Act of 1986  (COBRA) that  
directly regulates the healthcare industry by imposing continuing insurance requirements for 
persons who lose employment-related health insurance benefits (Congressional Research Service:  
http://www.fas.org/sgp/crs/misc/R40846.pdf). 
“Ethical” is used to refer to matters  involving  moral principles or practices and matters of social policy

“Ethical” is used to refer to matters  involving  moral principles or practices and matters of social policy  
involving issues of morality in the practice of medicine  (AMA Council on Moral Ethics: https://www. 
ama-assn.org/ama/pub/physician-resources/medical-ethics/code-medical-ethics/opinion101.page?). 
9.2 Hippocratic Oath 
The Hippocratic Oath dates back to the fifth century BC describing the responsibility of physicians to focus  
on the well being of their patients. The Hippocratic Oath was included in the Hippocratic Corpus, a com­
pendium of 60 Greek medical texts published in the third century BC that spanned many years and multiple  
authors. The corpus includes ethical essays, textbooks, and lectures that portrayed opposing points of view. 
FIGURE 9.1 Medical ethics chapter contents.

Modern Version (Written in 1964 by Louis Lasagna) 	 Original Version (Fifth Century BC) 
I swear to fulfill, to the best of my ability and judgment, this 
covenant: 
I will respect the hard-won scientific gains of those 
physicians in whose steps I walk, and gladly share such 
knowledge as is mine with those who are to follow. 
I will apply, for the benefit of the sick, all measures [that] are 
required, avoiding those twin traps of overtreatment and 
therapeutic nihilism. 
I will remember that there is art to medicine as well as 
science, and that warmth, sympathy, and understanding 
may outweigh the surgeon’s knife or the chemist’s drug. 
I will not be ashamed to say “I know not, ” nor will I fail to 
call in my colleagues when the skills of another are needed 
for a patient’s recovery. 
I will respect the privacy of my patients, for their problems 
are not disclosed to me that the world may know. Most 
especially must I tread with care in matters of life and death.

especially must I tread with care in matters of life and death. 
If it is given me to save a life, all thanks. But it may also be 
within my power to take a life; this awesome responsibility 
must be faced with great humbleness and awareness of my 
own frailty. Above all, I must not play at God. 
I will remember that I do not treat a fever chart, a cancerous 
growth, but a sick human being, whose illness may affect 
the person’s family and economic stability. My 
responsibility includes these related problems, if I am to 
care adequately for the sick. 
I will prevent disease whenever I can, for prevention is 
preferable to cure. 
I will remember that I remain a member of society, with 
special obligations to all my fellow human beings, those 
sound of mind and body as well as the infirm. 
If I do not violate this oath, may I enjoy life and art, 
respected while I live and remembered with affection

respected while I live and remembered with affection 
thereafter. May I always act so as to preserve the finest 
traditions of my calling and may I long experience the joy 
of healing those who seek my help. 
I swear by Apollo, the healer, Asclepius, Hygieia and 
Panacea, and, and I take to witness all the gods, all the 
goddesses, to keep according to my ability and my 
judgment, the following Oath and agreement: 
To consider dear to me, as my parents, him who taught me 
this art; to live in common with him and, if necessary, to 
share my goods with him; To look upon his children as my 
own brothers, to teach them this art; and that by my 
teaching, I will impart a knowledge of this art to my own 
sons, and to my teacher’s sons, and to disciples bound by 
an indenture and oath according to the medical laws, and 
no others. 
I will prescribe regimens for the good of my patients

no others. 
I will prescribe regimens for the good of my patients 
according to my ability and my judgment and never do 
harm to anyone. 
I will gi
ve no deadly medicine to any one if asked, nor 
suggest any such counsel; and similarly I will not give a 
woman a pessary to cause an abortion. 
(Rule 2 was changed in 1960) 
But I will preserve the purity of my life and my arts. 
I will not cut for stone, even for patients in whom the 
disease is manifest; I will leave this operation to be 
performed by practitioners, specialists in this art. 
In every house where I come I will enter only for the good 
of my patients, keeping myself far from all intentional 
ill-doing and all seduction and especially from the 
pleasures of love with women or men, be they free or 
slaves. 
All that may come to my knowledge in the exercise of my 
profession or in daily commerce with men, which ought

slaves. 
profession or in daily commerce with men, which ought 
not to be spread abroad, I will keep secret and will never 
reveal. 
If I keep this oath faithfully, may I enjoy my life and practice 
my art, respected by all humanity and in all times; but if I 
swerve from it or violate it, may the reverse be my life. 
• 	 References in Hippocratic Oath 
– Apollo was the god of Greek prophecy and healing. 
– 	Asclepius was a god of medicine and healing in 
ancient Greek religion. 
– Hygieia was the daughter of the god of medicine. 
– Panacea was a goddess of universal remedy. 
Ethics	 253 
Following World War II, the Hippocratic Oath was rewritten to address the horrors of the war, 
called the Declaration of Geneva, focusing on the ethical responsibilities of physicians. One of the 
items was particularly relevant to the aftermath of the war: “I will not use my medical knowledge

items was particularly relevant to the aftermath of the war: “I will not use my medical knowledge 
to violate human rights and civil liberties, even under threat.” In 1960, it was amended to remove 
references to Greek Gods or any deity; it said “utmost respect for human life from its beginning.” 
There are no legal penalties to violating the Hippocratic Oath, but the Department of Justice (DOJ) 
can level fines for violating  Health Insurance Portability and Accountability Act (HIPAA) rules 
(see Table 5.1 in Chapter 5), and the American Medical Association (AMA) Council on Ethical and 
Judicial Affairs (CEJA) (Section 8.3) has judicial functions, i.e., appellate jurisdiction over mem­
bers’ appeals of ethics-related decisions made by state and medical societies that are charged with 
evaluating physicians’ fitness for membership in the AMA (Table 9.1). 
TABLE 9.1 Hippocratic Oath: Original and Modern Version

Ethics group 
(American Medical Association) 
Council on Ethical and Ethics Resource Center Institute for EthicsJudicial Affairs (CEJA) 
Develops ethics policy
 Reports on timely ethical issues
 Added to code of ethics after
 approval by AMA house of delegates
 Appeals of ethics related
decisions 
Educational outreach programs 
Provides medical students, 
residents and physicians with
guidelines for practical solutions 
Continuing medical education
(CME courses) 
Academic and research and 
training center 
Publish peer reviewed paper on
ethical issues 
Serve as policy foundation for
CEJA 
© Lubliner 2013 
Ethical rules 
I II III IV V VI VII VIII IX 
Compassion Honesty Law Privacy Education Choice Public-welfare Patient-welfare Access
 
254	 Biomedical Informatics 
9.3 American Medical Association Ethics Groups 
Medical ethics are standards of conduct, not laws, by which medical personnel follow for the benefit of

Medical ethics are standards of conduct, not laws, by which medical personnel follow for the benefit of 
the patients. Its goals are to improve patient care and promote professionalism. The AMA Ethics Group 
sets guidance for physicians to pursue. The Ethics Group has three parts: the CEJA, Ethics Resource 
Center, and Institute for Ethics (Figure 9.2). 
The AMA publishes the Code of Medical Ethics that is periodically updated, originally published in 
1957 and subsequently updated in 1980 and 2001 (Table 9.2). 
9.3.1 Council on Ethical and Judicial Affairs 
The CEJA focuses on periodic updates of the Code of Medical Ethics and its judicial function, the most 
recent in 2001 (Table 9.2). 
9.3.1.1 Policy Functions 
The CEJA policy functions, first started in 1847, are primarily responsible in updating the “Code of 
Medical Ethics.” The second function is to develop policies on how the healthcare system should be

Medical Ethics.” The second function is to develop policies on how the healthcare system should be 
organized and how it should function, called the “opinions on the code.” It has a search capability called 
“Policy Finder” for specific areas (the online version can be found at http://www.ama-assn. org/ama/ 
pub/about-ama/our-people/house-delegates/policy-finder-online.page?). 
It is divided into three categories: 
1. Health and ethics policies
 2. Governance policies 
3. Directives of the AMA House of Delegates (HOD) 
a.	 The AMA’s HOD meets twice a year (every June and November) to conduct the business of 
the house. The June meetings are referred to as annual meetings and are referenced as “A-” 
followed by the year of the meeting (i.e., A-11 means the 2011 annual meeting). November 
FIGURE 9.2 AMA medical ethics organization.

Ethics	 255 
TABLE 9.2 Principles of Medical Ethics Last Published in 2001 by the American Medical Association (AMA) 
Ethics Groupa 
Category Principles 
1 Compassion A physician shall be dedicated to providing competent medical care, with compassion and respect 
for human dignity and rights. 
2 Honesty A physician shall uphold the standards of professionalism, be honest in all professional 
interactions, and strive to report physicians deficient in character or competence, or engaging in 
fraud or deception, to appropriate entities. 
3 Law A physician shall respect the law and also recognize a responsibility to seek changes in those 
requirements which are contrary to the best interests of the patient. 
4 Privacy A physician shall respect the rights of patients, colleagues, and other health professionals, and 
shall safeguard patient confidences and privacy within the constraints of the law.

shall safeguard patient confidences and privacy within the constraints of the law. 
5 Education A physician shall continue to study, apply, and advance scientific knowledge, maintain a 
commitment to medical education, make relevant information available to patients, colleagues, 
and the public, obtain consultation, and use the talents of other health professionals when 
indicated. 
6 Choice A physician shall, in the provision of appropriate patient care, except in emergencies, be free to 
choose whom to serve, with whom to associate, and the environment in which to provide 
medical care. 
7 Public welfare A physician shall recognize a responsibility to participate in activities contributing to the 
improvement of the community and the betterment of public health. 
8 Patient welfare A physician shall, while caring for a patient, regard responsibility to the patient as paramount. 
9 Access A physician shall support access to medical care for all people.

9 Access A physician shall support access to medical care for all people. 
a https://www.ama-assn.org/ama/pub/physician-resources/medical-ethics.page? 
meetings are interim meetings and are referenced as “I-” followed by the year of the meeting 
(i.e., I-10 means the 2010 interim meeting). 
b. 	 The HOD maintains online archives of these meetings ( http://www.ama-assn.org/ama/pub/ 
about-ama/our-people/house-delegates/meeting-archives.page?). 
9.3.1.2 Judicial Functions 
The CEJA evaluates physicians’ adherence to ethical standards and has disciplinary action to determine 
their fitness for membership in the AMA. The CEJA is initially informed as follows: 
Case
 finding 
• 	 Statements made in the membership application form 
• 	 Reports of disciplinary actions taken by state licensing boards 
• 	 Media reports 
etermination of reasonable cause for a hearing 
• 	 At each of the CEJA meetings, they determine if there is reasonable cause  for a disciplinary  
hearing.

hearing. 
• 	 The CEJA reviews up to 100 cases a year. 
• The AMA’s Office of General Counsel (OGC) reviews an additional 100 cases a year. 
.3.1.2.1 Litigation Center of the AMA 
e Litigation Center of the AMA and State Medical Societies, established in 1995, as part of the AMA 
hysicians’ resource center, provides physicians with legal expertise assistance (http://www.ama-assn. 
rg/ama/pub/physician-resources/legal-topics/litigation-center.page?). 
D
9
Th
p
o

256 Biomedical Informatics 
AMA Litigation Center Cases 
A	 E M R 
Abortions Economic Credentialing Managed care payments Regulatory burdens 
Abortion notification Electronic Medical Managed care tort liability Resident physicians 
Abusive litigation against Records Medicaid Restrictive covenants 
physicians Emergency services Medical education S 
Access to medical facilities Employment Medical society advocacy Screening Panels 
Affidavit of Merit EMTALA Medical staff Scope of Practice 
Americans with Disabilities  Environmental protection Medicare SLAPP laws 
Act ERISA preemption Minors’ rights Stark Laws 
Anti-tobacco Ethics P T 
Antitrust Expert witnesses Patents Taxation of physicians 
Any Willing Provider Laws Patient privacy Termination of employment F 
Arbitration	 Patient rights Termination of physician False Claims Act 
B Patient Safety Act participation in provider Federal Tort Claims Act 
Balanced Billing Payment issues (for patients) networks Food labeling

Balanced Billing Payment issues (for patients) networks Food labeling 
Blood banks Payment issues (for physicians) Tiered and narrowed  Fraud and abuse 
C Peer review ma naged care networks Freedom of Information Act 
Certificate of Merit Physician Advocacy Tor t reform GCertificate of Need	 Physician-Patient  U 
Gay, Lesbian, Bisexual, Christian Science	 communications Unions 
Transsexual Rights Civil Rights	 Physician-Patient relationship Usual customary and 
Clinical Trials	 H Physician participation in   reasonable payments
Confidentiality Health plan coverage capital punishment V 
Corporate Practice of Hospitals Physician safety Vaccine Act 
Medicine I Physician self-referral W 
Criminal Law	 Independent Review Workers’ Compensation Physicians’ privacy rights 
Criminalization of Medical Informed consent Pregnant Women’s Rights 
Judgments Insurance (Liability) Professional liability

Judgments Insurance (Liability) Professional liability 
D Coverage Prompt payment Laws 
Do Not Resuscitate Order L Public Health 
Drug Manufacturers Loss of Chance Public Health Service 
Due Process 
FIGURE 9.3 AMA Litigation Center cases by topic. 
The Litigation Center provides the following: 
 1.  They ensure physicians’ rights are upheld. 
 2. They protect the integrity of hospital medical staffs. 
 3.  Challenging abusive litigation against physicians, many cases have set important legal precedents  
and have broad, practical applications for the medical profession and patients. 
The Litigation Center provides representation for cases in the following areas (Figure 9.3). 
9.4 ANA Code of Ethics 
The American Nurses Association (ANA), similar to the AMA, periodically produces a code of ethics; 
the last was updated in 2001 that certified that nurses have to read, understand, and act upon:

the last was updated in 2001 that certified that nurses have to read, understand, and act upon: 
 1. The nurse, in all professional relationships, practices with compassion and respect for the inher­
ent dignity, worth, and uniqueness of every individual, unrestricted by considerations of social or  
economic status, personal attributes, or the nature of health problems. 
 2. The nurse’s primary commitment is to the patient, whether an individual, family, group, or 
community.

5. The nurse owes the same duties to self as to others, including the responsibility to preserve integ­
rity and safety, to maintain competence, and to continue personal and professional growth. 
 6.  The nurse participates in establishing, maintaining, and improving healthcare environments and  
conditions of employment conducive to the provision of quality healthcare and consistent with  
the values of the profession through individual and collective action. 
 7. The nurse participates in the advancement of the profession through contributions to practice, 
education, administration, and knowledge development. 
 8.  The nurse collaborates with other health professionals and the public in promoting community,  
national, and international efforts to meet health needs. 
 9.  The profession of nursing, as represented by associations and their members, is responsible for 
articulating nursing values, for maintaining the integrity of the profession and its practice, and

articulating nursing values, for maintaining the integrity of the profession and its practice, and 
for shaping social policy. 
The American Association of Critical Care Nurses (AACN; www.aacn.org) is the certifying organiza­
tion for nurses. They publish a series of values that all its members must honor: 
• 	 Ethical accountability and integrity  in relationships, organizational decisions, and stewardship of 
resources 
• 	 Leadership to enable individuals to make their optimal contribution  through lifelong learning, 
critical thinking and inquiry 
• 	 Excellence and innovation  at every level of the organization to advance the profession 
• 	 Collaboration  to ensure quality patient- and family-focused care. 
Level II: Medical Ethics Scenarios 
9.5 Ethical Medical Situations
 
Sources: AMA Code of Medical Ethics 
• 	 Specific practical ethical questions are addressed by the AMA CEJA and in the AMA Journal of

• 	 Specific practical ethical questions are addressed by the AMA CEJA and in the AMA Journal of 
Ethics. A virtual tutor is available at http://virtualmentor.ama-assn.org/site/cases.html where you 
can enter a search parameter. 
The following medical ethical scenarios are taken from the previously mentioned sources: 
This section describes guidance by the AMA regarding the complex ethical situations that medical 
professionals may encounter. A useful class interaction that precedes assigning this reading might be to 
pose these ethical conundrums and engage the class in an interactive debate. 
9.5.1 Reporting Impaired Drivers 
Summary 
• 	 Physicians should use their best judgment when determining when to report impairments that 
could limit a patient’s ability to drive. 
• 	 In situations where there is a strong threat to patient and public safety and where the physician’s

• 	 In situations where there is a strong threat to patient and public safety and where the physician’s 
advice to discontinue driving is ignored, it is desirable and ethical to notify the state’s Department 
of Motor Vehicles. 
Ethics	 257 
3. The nurse promotes, advocates for, and strives to protect the health, safety, and rights of the 
patient. 
4. The nurse is responsible and accountable for individual nursing practice and determines the 
appropriate delegation of tasks consistent with the nurse’s obligation to provide optimum patient 
care.

Driver licensing agency New Jersey Motor Vehicle Commission 609 292-6500 
 contact information PO BOX 160 
Trenton, NJ 08666 
www.state.nj.us/mvs 
Visual acuity Each eye with/without correction 20/50 
Both eyes with/without correction 20/50 
If one eye blind—other with/without correction 20/50 
Absolute visual acuity mimimum 20/50 
Are bioptic telescope allowed? Yes, with acuity of 20/50 
through telescope 
Visual fields Minimum field requirement None 
color vision requirement Color vision is tested in new drives, but licenses 
are not denied based on poor color vision. 
Type of road test Standardized 
Restricted licenses Available 
Licensing Requirement 
 
258 Biomedical Informatics 
9.5.1.1 AMA Impaired Drivers and Their Physicians Case Study 
AMA link: http://virtualmentor.ama-assn.org/2010/12/coet2–1012.html 
The National Highway and Transportation and Safety Reporting laws  for all states link: http://www. 
nhtsa.gov/people/injury/olddrive/olderdriversbook/pages/Chapter8.html

nhtsa.gov/people/injury/olddrive/olderdriversbook/pages/Chapter8.html 
Question: Impaired Drivers and Their Physicians 
Is it the physicians’ responsibility to recognize impairments in patients’ driving ability that pose a 
strong threat to public safety and that ultimately may need to be reported to the Department of Motor 
Vehicles? It does not address the reporting of medical information for the purpose of punishment or 
criminal prosecution (Figure 9.4). 
a . P h y s i c i a n s  s h o ul d  a s s e s s  p a t i e n t s ’  p h y s i c al  o r  m e n t al  i m p a i r m e n t s  th a t  m i g h t  a d v e r s e l y  a ff e c t 
driving abilities. 
b. Each case must be evaluated individually since not all impairments may give rise to an obligation 
on the part of the physician, nor may all physicians be in a position to evaluate the extent or the 
effect of an impairment (e.g., physicians who treat patients on a short-term basis).

effect of an impairment (e.g., physicians who treat patients on a short-term basis). 
c. In making evaluations, physicians should consider the following factors: 
i.	 The physician must be able to identify and document physical or mental impairments that 
clearly relate to the ability to drive. 
ii. 	 The driver must pose a clear risk to public safety. 
d. Before reporting, there are a number of initial steps physicians should take. A tactful but candid 
discussion with the patient and family about the risks of driving is of primary importance. Efforts 
made by physicians to inform patients and their families, advise them of their options, and nego­
tiate a workable plan may render reporting unnecessary. 
i.	 Depending on the patient’s medical condition, the physician may suggest to the patient 
that he or she seek further treatment, such as substance abuse treatment or occupational 
therapy.

therapy. 
ii. 	 Physicians also may encourage  the patient and the family to decide on a restricted driving 
schedule. 
FIGURE 9.4 New Jersey Driver License regulations: typical of state guidelines. (From http://www.nhtsa.gov/ 
people/injury/olddrive/olderdriversbook/pages/NewJersey.html.)

Ethics	 259 
iii. 	 Efforts made by physicians to inform patients and their families, advise them of their options, 
and negotiate a workable plan may render reporting unnecessary. 
e.	 Physicians should use their best judgment when determining when to report impairments that could 
limit a patient’s ability to drive safely. In situations where clear evidence of substantial driving impair­
ment implies a strong threat to patient and public safety and where the physician’s advice to discon­
tinue driving privileges is ignored, it is desirable and ethical to notify the department of motor vehicles. 
f. The physician’s role is to report medical conditions that would impair safe driving as dictated by 
his or her state’s mandatory reporting laws and standards of medical practice. The determination 
of
 the inability to drive safely should be made by the state’s Department of Motor Vehicles. 
 g. Physicians should disclose and explain to their patients this responsibility to report.

g. Physicians should disclose and explain to their patients this responsibility to report. 
 h.	  Physicians should protect patient confidentiality by ensuring that only a minimal amount of infor­
mation is reported and that reasonable security measures are used in handling that information. 
 i.	  Physicians should work with their state medical societies to create statutes that uphold the best interests  
of patients and community and that safeguard physicians from liability when reporting in good faith. 
9.5.2 Medical Students Performing Procedures on Fellow Students 
Summary 
 1. Instructors should explain to students how the procedures will be performed, making certain that 
students are not placed in situations that violate their privacy or sense of propriety. 
 2. Students should be given the choice of whether to participate prior to entering the classroom. 
 3. There should be no requirement that the students provide a reason for their unwillingness to 
participate.

3. There should be no requirement that the students provide a reason for their unwillingness to 
participate. 
 4. Students should not be penalized for refusal to participate. 
9.5.3 Surgical Placebo 
Summary 
Question: Should physicians use surgical “placebo” controls (subjects undergo surgical procedures that 
have the appearance of therapeutic intervention but during which the essential therapeutic maneuver is 
omitted) when assessing the efficacy of a surgical intervention? 
 1.  When a new surgical procedure is developed with the prospect of treating a condition for which 
no known surgical therapy exists, using surgical “placebo” controls may be justified but must be 
evaluated in light of whether the current standard of care includes a nonsurgical treatment and 
the benefits, risks, and side effects of that treatment. 
 2.  During the informed consent process, careful explanation of the risks of the operation must be

2.  During the informed consent process, careful explanation of the risks of the operation must be  
disclosed. Additional safeguards may include using a neutral third party to provide information 
and obtain consent. 
 3. The use of placebo control is not justified when testing a surgical technique that represents a 
minor improvement of an existing surgical procedure. 
9.5.3.1 AMA Placebo Case Study 
Description 
Mr. Marcus is a 70-year-old retiree living on his limited pension. He suffers from advanced osteoarthritis 
(OA) in his knees and would do anything to be able to walk more easily on his own. He says to Dr. Janus, 
“My best friend had this surgery last month, and he’s already getting around the golf course great. He says 
this surgery was the best thing he ever did for himself. I sure would love to be able to keep up with him

260 Biomedical Informatics 
now. What do you say, Doc, can you do this surgery for me?” (http://virtualmentor.ama-assn.org/2012/11/ 
ecas1–1211.html) 
Opinion 
Once one of the most commonly performed of orthopedic procedures, arthroscopic debridement of the 
knee has come under scrutiny in recent years with the publication of two major randomized controlled 
clinical trials that failed to demonstrate benefit to the enrolled patients [2,3]. Even in the current envi­
ronment, with its emphasis on evidence-based medicine, such level I clinical evidence is hard to come 
by, particularly in the context of surgery. Nonetheless, a clinical impression endures to support the use 
of this procedure for OA of the knee, albeit in a more limited, defined subset of patients. 
Recommended course of action 
Based on current standards of practice, he is obligated to first recommend a comprehensive program of

Based on current standards of practice, he is obligated to first recommend a comprehensive program of  
nonsurgical management. Numerous nonoperative treatment options are available to treat patients with OA  
of the knee. These include activity modification, physical therapy, nonsteroidal anti-inflammatory agents,  
and intra-articular injections (corticosteroid or hyaluronate). All patients with symptomatic OA of the knee  
should be treated according to these tenets before more aggressive (surgical) methods are employed. Only for  
some of those who do not respond should the surgical option be considered: patients with radiographic mild  
arthritis or near-normal alignment but not patients with valgus configurations or arthritis in both knees. 
So what should Dr. Janus recommend to Mr. Marcus and how should he convey it? 
Although the risks of this surgery are typically small, available evidence suggests that the benefit of such

Although the risks of this surgery are typically small, available evidence suggests that the benefit of such 
surgery is likely to be low; indeed clinical experience suggests such intervention may in some instances 
exacerbate the symptoms and accelerate joint deterioration. Therefore, though for some patients (such 
as Mr. Marcus’ friend) the procedure may prove beneficial, for Mr. Marcus himself, this is unlikely to be 
the case. Given the low likelihood of success, indeed the potential for making his condition worse, Dr. 
Janus should advise against surgery and advocate for a more conservative therapeutic strategy. It is criti­
cal for Dr. Janus to explain the reasoning and justification for his advice and to ensure that Mr. Marcus 
comprehends the explanation and, ultimately, finds it satisfactory. 
9.5.4 Gifts to Physicians from Industry 
Summary 
Question: Is it ethically permissible to accept gifts from pharmaceutical representatives?

Summary 
Question: Is it ethically permissible to accept gifts from pharmaceutical representatives? 
• 	 Any gift accepted by a physician should primarily entail a benefit to patients and should not be of  
substantial value. 
• 	 Individual gifts of minimal value are permissible as long as they relate to the physician’s work. 
AMA Opinion 8.061 
The AMA Code of Medical Ethics’ Opinions on Physicians’ Relationships with Drug Companies and Duty  
to Assist in Containing Drug Costs. Link: http://virtualmentor.ama-assn.org/2014/04/coet2–1404.html 
9.5.4.1 Opinion 8.061: Gifts to Physicians from Industry 
Many gifts given to physicians by companies in the pharmaceutical, device, and medical equipment 
industries serve an important and socially beneficial function. For example, companies have long pro­
vided funds for educational seminars and conferences. However, there has been growing concern about

vided funds for educational seminars and conferences. However, there has been growing concern about 
certain gifts from industry to physicians. Some gifts that reflect customary practices of industry may 
not be consistent with the Principles of Medical Ethics. To avoid the acceptance of inappropriate gifts, 
physicians should observe the following guidelines: 
 1 .  A n y  g i ft s  a c c e p t e d  b y  p h y s i c i a n s  i n d i v i d u a l l y  s h o u l d	  primarily entail a benefit to patients  
and should not be of substantial value . Accordingly, textbooks, modest meals, and other gifts  
are appropriate if they serve a genuine educational function. Cash payments should not be

Ethics 261 
accepted. The use of drug samples for personal or family use is permissible as long as these  
practices do not interfere with patient access to drug samples. It would not be acceptable  
for nonretired physicians to request free pharmaceuticals for personal use or use by family  
members. 
 2.  Individual gifts of minimal value are permissible as long as the gifts are related to the physician’s 
work (e.g., pens and notepads). 
 3 .  Th e  C E J A  d e fin e s  a  l e gi ti m a t e  “ c o n f e r e n c e ”  o r  “ m e e ti n g ”  a s  an y  a c ti vi ty ,  h e l d  a t  an  a p p r o p r i ­
ate location, where (a) the gathering is primarily dedicated, in both time and effort, to pro­
moting objective scientific and educational activities and discourse (one or more educational 
presentation[s] should be the highlight of the gathering) and (b) the main incentive for bringing 
attendees together is to further their knowledge on the topic(s) being presented. An appropriate

attendees together is to further their knowledge on the topic(s) being presented. An appropriate 
disclosure of financial support or conflict of interest should be made. 
 4. Subsidies to underwrite the costs of continuing medical education conferences or professional 
meetings can contribute to the improvement of patient care and therefore are permissible. Since 
the giving of a subsidy directly to a physician by a company’s representative may create a relation­
ship that could influence the use of the company’s products, any subsidy should be accepted by the 
conference’s sponsor who in turn can use the money to reduce the conference’s registration fee.  
Payments to defray the costs of a conference should not be accepted directly from the company by 
the physicians attending the conference. 
 5. Subsidies from industry should not be accepted directly or indirectly to pay for the costs of travel,

 5. Subsidies from industry should not be accepted directly or indirectly to pay for the costs of travel, 
lodging, or other personal expenses of physicians attending conferences or meetings, nor should 
subsidies be accepted to compensate for the physicians’ time. Subsidies for hospitality should not 
be accepted outside of modest meals or social events held as a part of a conference or meeting.  
It is appropriate for faculty at conferences or meetings to accept reasonable honoraria and to 
accept reimbursement for reasonable travel, lodging, and meal expenses. It is also appropriate 
for consultants who provide genuine services to receive reasonable compensation and to accept 
reimbursement for reasonable travel, lodging, and meal expenses. Token consulting or advisory 
arrangements cannot be used to justify the compensation of physicians for their time or their 
travel, lodging, and other out-of-pocket expenses.

travel, lodging, and other out-of-pocket expenses. 
 6. Scholarship or other special funds to permit medical students, residents, and fellows to attend 
carefully selected educational conferences may be permissible as long as the selection of students, 
residents, or fellows who will receive the funds is made by the academic or training institution. 
Carefully selected educational conferences are generally defined as the major educational, scientific, 
or policy-making meetings of national, regional, or specialty medical associations. 
 7.  No gifts should be accepted if there are strings attached. For example, physicians should not 
accept gifts given in relation to the physician’s prescribing practices. In addition, when companies 
underwrite medical conferences or lectures other than their own, responsibility for and control

underwrite medical conferences or lectures other than their own, responsibility for and control 
over the selection of content, faculty, educational methods, and materials should belong to the 
organizers of the conferences or lectures. 
9.5.5 How to Refer to Medical Students in a Clinical Setting 
Summary 
Question:  Is it appropriate to use terms such as “student doctor” to identify medical students who are 
caring for patients? 
 1. Patients should be informed of the training status of individuals involved in their care. 
 2. Terms that may be confusing when describing the training status of students should not be used. 
 3.  Physicians should relate the benefits of student participation to patients and should ensure that 
they are willing to permit such participation .

262 Biomedical Informatics 
9.5.6 Should Medical Trainees Perform Procedures 
Summary 
Question: Should medical trainees perform procedures such as endotracheal intubation on the newly  
deceased patient? 
 1.  In the absence of previously expressed preferences, physicians should request permission from 
the family before performing procedures. 
 2.  Without such permission, physicians should not perform procedures for training purposes on the 
newly deceased patient. 
9.5.6.1 AMA Patient Care and Student Education 
Virtual Mentor. April 2002, Volume 4, Number 4. 
Background 
Mr. H was admitted yesterday to the general medical service of a teaching hospital. This is his third 
admission in 8  months. One prior admission was, like this one, due to exacerbation of long-stand­
ing chronic obstructive pulmonary disease (COPD). The other admission was prompted by dizziness 
and fainting brought on by his poorly controlled diabetes. Mr. H is 57  years old African American.

and fainting brought on by his poorly controlled diabetes. Mr. H is 57  years old African American. 
Management of his health is complicated by obesity and (as he confessed to Miss Rogers, the third-year  
medical student who interviewed him when he arrived on the unit) his continued smoking. 
Dr. G, the senior resident, decides that a subclavian central line should be placed to gain intravenous 
access. Then antibiotics, fluids, and other medications, if needed, can be easily and effectively adminis­
tered without continuing to poke at Mr. H’s peripheral veins. 
Dr. G is supervising two third-year medical students who are in week 6 of their 8-week internal 
medicine rotation. The students are Mr. Crane and the previously mentioned Miss Rogers who has 
interviewed Mr. H. Dr. G has established good working relationships with both students, who are highly 
motivated and competent. Dr. G takes her role as educator seriously and wants to be confident that stu­

dents gain the experience and, to the extent possible, the skills they should while under her supervision. 
Mr. Crane has successfully placed central lines on several occasions during his rotation. Miss Rogers 
has been unsuccessful on two attempts with different patients. 
Mr. H is a good patient for Miss Rogers’ next attempt. His condition is not emergent; he is accustomed  
to the teaching hospital routine and has taken Miss Rogers’ into his confidence. He considers her to be 
“on his side.” On the other hand, his obesity makes the procedure more difficult than usual. Because 
of his multiple health problems and complications, should Miss Rogers puncture his lung would be  
Mr. H is a Medicaid patient, and Dr. G is sensitive to the potential for Medicaid patients to shoulder

Mr. H is a Medicaid patient, and Dr. G is sensitive to the potential for Medicaid patients to shoulder 
more than their share of student and intern “practicing.” Were she acting solely as clinician and not as 
educator, Dr. G would ask Mr. Crane to place the line. 
Miss Rogers has to succeed at placing a central line before completing her internal medicine rotation, 
and time is running out. She is on her way in to inform Mr. H about the procedure and its risks and to 
obtain his consent for it. She identified herself as a student when she first introduced herself and inter­
viewed him. They seem to communicate well. If Dr. G asks her to attempt to place the line, she wonders, 
how much will she have to tell Mr. H about her past attempts? 
Opinion
 
See One, Do One, Teach One.
 
Teaching hospitals serve an important function within our society by offering physicians in training the

Opinion
 
Teaching hospitals serve an important function within our society by offering physicians in training the 
opportunity to learn the skills that they must have to become competent practitioners while attempting 
to provide an exceptional standard of care to individual patients. Society has an interest and investment 
in this process.

Ethics	 263 
Naturally, achieving technical competency among physicians is a gradual process marked by several 
transitions. Medical students begin with lectures and anatomy lab and only after their first years in 
medical school do they move to the clinical setting where they participate directly in patient care. While 
the ratio of 1:1:1 is not steadfast, the transitive nature of education that it reflects is noteworthy. Those  
with less experience first observe a procedure, then perform one, and finally reach a stage of teaching the 
procedure to the next person with less experience as the cycle begins anew. 
Who Is to Attempt Central Line Placement? 
Several factors are important for the team to consider as they make this decision: 
 1. What are the student’s and house officer’s comfort with the student performing the procedure? 
 2. How acutely ill is the patient and how quickly is the procedure required?

2. How acutely ill is the patient and how quickly is the procedure required? 
 3. What are the patient’s and family’s wishes regarding who is to perform the procedure? How tech­
nically difficult is the procedure? 
 4. Finally, what are the likelihood and severity of potential complications and how are these modi­
fied by the greater technical experience of more senior physicians? 
 a.	  While perhaps the least quantifiable, the most important global measure that a senior house 
officer should consider in deciding who is to perform a procedure is his or her own intuition 
as to the appropriateness of the teaching moment. 
What information should Mr. H be told in order to provide an informed consent? 
 1.  Standard components of informed consent, such as the indications, risks, benefits, and alterna­
tives to the procedure, can be discussed. 
 2.  The key question in this setting is how much information Mr. H needs to be provided regarding

 2.  The key question in this setting is how much information Mr. H needs to be provided regarding 
the identity and technical competency of the person who is to perform the procedure. 
 3. Not telling Mr. H about who is to perform the procedure would deny him important information 
that might modify his decision. 
 4. On the other hand, to tell him who is to perform the procedure while denying him knowledge of 
that person’s technical competency seems inadequate. 
 5.  How then would he use the information regarding this person? 
Opinion (Recommendation) 
Rather than discuss Miss Rogers’ prior experience with central line placement, Mr. H should be informed 
of the proposal that Miss Rogers, a medical student, will be the person attempting the procedure under 
the close supervision of Dr. G. 
Additionally, any questions that Mr. H may have about Miss Rogers’ experience should be addressed 
honestly and directly. 
Bottom Line

Bottom Line 
Virtually all senior house officers will be challenged during their training to balance the healthcare 
needs of their patients with the educational needs of their junior colleagues. Sensitivity to the media­
tors of procedural risk, in conjunction with an adequately thorough informed consent, should be the  
trainee’s primary guide in achieving this balance. 
9.5.7 Resident Questions Order of Attending Physician 
Summary 
Question: A resident has concerns that an attending physician’s order is reflective of poor clinical judg­
ment. How should this situation be handled? 
 1.  Trainees may withdraw from the care ordered by the supervisor, provided withdrawal does not 
itself threaten the patient’s immediate welfare. 
 2.  The trainee should communicate his or her concerns to the physician issuing the orders and, if

2.  The trainee should communicate his or her concerns to the physician issuing the orders and, if  
necessary, to the appropriate persons for mediating such disputes.

264 Biomedical Informatics 
3. Third-party mediators of such disputes may include the chief of staff of the involved service, the 
chief resident, a designated member of the institutional grievance committee, or, in large institu­
tions, an institutional ombudsperson largely outside of the hospital staff hierarchy. 
4. Retaliatory or punitive actions against trainees who raise complaints are unethical and are a legit­
imate cause for filing a grievance with the appropriate institutional committee. 
9.6 Clinical Decision Support Systems
 
A clinical decision support system (CDSS) is an expert system, artificial intelligence software, or accu­
mulated medical knowledge used to assist a medical practitioner in diagnosis or treatment. The advan­
tage of a directed knowledge base is the ability to mine large data sets and analyze similarities or more

tage of a directed knowledge base is the ability to mine large data sets and analyze similarities or more 
accurately probabilities that a set of factors indicate a particular disorder, especially if it is a rare disease 
that a medical practitioner might not normally experience. 
Typical expert systems use inference engines that make comparisons on a series of logical sequences 
of events: if a is true, then likely b is the cause, called forward chaining. The following is a classic exam­
ple: you type in a question to an expert system “is Socrates Mortal?” and then the system finds that 
Socrates has been defined as human and somewhere else humans have been defined as mortal so it can 
deduce “Socrates is mortal.” 
9.6.1 Neural Networks 
Neural networks are defined as systems that are modeled after living biological organisms. Complex 
systems are modeled by simulations. 
These systems can be useful but more powerful techniques are under way: Exponential Stability

These systems can be useful but more powerful techniques are under way: Exponential Stability 
Analysis for Neural Networks and Fuzzy networks. Often if the subject area is more narrowly defined, 
the system can be more predictive. They are designed to be capable of learning new relationships and 
are more flexible at recognizing patterns, i.e., pattern recognition. 
They are modeled after human neurons that are analog, a continuously variable quantity, similar to 
data in the real world. The values can take on any value between 0 and 0.999 where the higher values 
or probabilities indicate that the answer is more likely, i.e. there are no yes and no answers or 0 or 1 
responses. Neural networks have adaptive weights and feedback loops that constantly change depending 
on new inputs, so the strengths, 0–0.999, change as new data come in. If you put your hand near a fire

on new inputs, so the strengths, 0–0.999, change as new data come in. If you put your hand near a fire 
or approach sources of high temperature, the adaptive weight would increase the danger component of 
the reasoning system. The second component is nonlinear functions, or some close approximation. A 
nonlinear system is “one that does not satisfy the superposition principle,” or one whose output is not 
directly proportional to its inpu t (Figure 9.5). 
By narrowly defining the area of diagnosis, the feasibility of narrowing in on effective expert systems 
increases: 
1. An example of computer-aided diagnosis is “Computer-aided diagnosis of human brain tumor 
through MRI: A survey and a new algorithm” by El-Sayed A. Dahshan et al. “The technique is 
based on the following computational methods; the feedback pulse-coupled neural network for 
image segmentation, the discrete wavelet transform for features extraction, the principal com­

ponent analysis for reducing the dimensionality of the wavelet coefficients, and the feed forward 
back-propagation neural network to classify inputs into normal or abnormal. The experiments 
were carried out on 101 images consisting of 14 normal and 87 abnormal (malignant and benign 
tumors) from a real human brain MRI dataset. The classification accuracy on both training and 
test images is 99%” (http://www.sciencedirect.com/science/article/pii/S0957417414000426).

Ethics	 265 
The principle of superposition simply states that a set of
quantities can be added as vectors to determine the net of that
quantity at a certain point.
 A nonlinear system: 
whose output is not
directly proportional to
F its input Results in FThe Superposition
principle suggests that the
net response at a given
place and time caused by
 
two or more stimuli is the
 
sum of the responses which
 
would have been caused by
each stimulus individually.
 
X 
tFactor A 
Some 
contributing
factors Factor B ©Lubliner 2013 
FIGURE 9.5 Superposition theory versus a nonlinear system used in neural networks. 
Steps involved in detecting tumor using Boundary Box method are as follows:­
1. Axis of symmetry on an axial MR slice is found which divides brain in two halves left (I) and right (R).
2. One half serves as test Image and the other half supplies as the reference image. 
3.	 Noval score function is used which identify the region of change with two searches — one along the vertical

3.	 Noval score function is used which identify the region of change with two searches — one along the vertical 
direction and other along the horizontal direction.
4.	 Noval score function uses Bhattacharya coefficient to detects a rectangle D which represents the region of
interest between images I and R. 
FIGURE 9.6  NIS database. (From http://www.hcup-us.ahrq.gov/nisoverview.jsp#about.) 
2. Another example is “ An Automated System for Brain Tumor Detection and Segmentation” by 
Rohan Kandwal et al. It consists of three stages to detect and segment brain tumor. In the first 
stage, image preprocessing is done to remove any noise and sharpen image. In the second stage, 
the bounding box method using symmetry is used to automatically detect the location of the 
tumor in any part of the brain. In the third stage, several postprocessing operations are used to 
finally segment the tumor portion from the whole image. Several experiments show that our

finally segment the tumor portion from the whole image. Several experiments show that our 
technique in spite of being completely simple detects tumor correctly ( http://www. academia. 
edu/6815417/An_Automated_System_for_Brain_Tumor_Detection_and_Segmentation) 
(Figure 9.6). 
The Nationwide Inpatient Sample (NIS) database is a federal state industry partnership that has cur­
rently, as of 2014, 40 million inpatient hospital stays. It was funded by a Health and Human Services 
(HHS) grant called Agency for Healthcare Research and Quality (AHRQ) ( http://www.ahrq.gov /). 
The NIS can be used to identify, track, and analyze national trends in healthcare utilization, access,

266 Biomedical Informatics 
charges, quality, and outcomes. NIS data are available from 1988 through 2011, which allow analysis of  
trends over time. The number of states in the NIS has grown from 8 in the first year to 46 at present. 
Key features of the most recent NIS database year (2011) include the following: 
• 	 A sampling frame of hospitals that comprises approximately 97% of all hospital discharges in the 
United States. 
• 	 A large sample size, which enables analyses of rare conditions, such as congenital anomalies;  
uncommon treatments, such as organ transplantation; and special patient populations, such as 
the uninsured. 
• 	 Hospital identifiers for many states that permit linkages to the American Hospital Association 
(AHA) Annual Survey Database (Health Forum, LLC © 2012) and county identifiers that permit 
linkages to the Area Resource File. 
NIS Data Elements 
The NIS contains clinical and resource-use information that is included in a typical discharge abstract,

The NIS contains clinical and resource-use information that is included in a typical discharge abstract,  
with safeguards to protect the privacy of individual patients, physicians, and hospitals (as required by data  
sources). It contains more than 100 clinical and nonclinical data elements for each hospital stay, including 
• 	 Primary and secondary diagnoses and procedures 
• 	 Admission and discharge status 
• 	 Patient demographic characteristics (e.g., sex, age, race, and median household income for ZIP code) 
• 	 Hospital characteristics (e.g., ownership, size, and teaching status) 
• 	 Expected payment source 
• 	 Total charges 
• 	 Discharge status 
• 	 Length of stay 
• Severity and comorbidity measures 
As a uniform, multistate database, the NIS promotes comparative studies of healthcare services: 
• 	 Utilization of health services by special populations 
• 	 Hospital stays for rare conditions 
• 	 Variations in medical practice

• 	 Variations in medical practice 
• 	 Healthcare cost inflation 
• 	 Regional and national analyses 
• 	 Quality of care and patient safety 
• 	 Impact of health policy changes 
• 	 Access to care 
By analyzing data from U.S. hospitals, trends and effectiveness of treatment can be analyzed. An exam­
ple is “Trends and Outcomes of Hospitalized Patients with Gastrointestinal Bleeds in the US: Data from 
N a t i o n w i d e  I n p a t i e n t  S a m p l e  O v e r  t h e  P a s t  D e c a d e  ( 2 0 0 1–2010)” (http://www.eventscribe.com/2012/ 
acg/ajaxcalls/postersinfo.asp?title=6977). 
Conclusion: B y  a n a l y z i n g  U S  d a t a ,  r e s u l t s  f r o m  t h i s  l a r g e ,  n a t i o n a l  d a t a b a s e  s h o w  t h a t  h o s p i t a l  
admissions for all GIB have increased over the last decade (by almost 5%); this is mainly due to a 45%

admissions for all GIB have increased over the last decade (by almost 5%); this is mainly due to a 45% 
increase in admissions due to variceal UGIB. However, despite the increased GIB, mortality and length  
of hospital stay in these patients has significantly decreased over the decade suggesting improved treat­
ment of these patients during their hospital stays (Figure 9.7). 
9.7 Summary 
Medical ethics is a system of moral values and  principles of conduct governing an individual or a group.  In  
the United States, the AMA Ethics Groups publish a Code of Ethics as guidelines for medical personnel.  
The AMA’s CEJA provides for judicial action to sanction medical practitioners who violate the Code of

4.7 
4.6 
4.5 
4.4 
4.3 
4.2 
Ten year trends in GI bleed admissions in US 400,000 
350,000 
300,000 
347,041 340,480 347,796 342,835 351,868 354,485 
374,776 350,739 362,467 
331,541 
Number of admissions
250,000 
200,000 
150,000 
100,000 
50,000 
0 
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 
All GIB 
Variceal UGIB 
Nonvariceal UGIB 
LGIB 
ercentage of all GI bleeds resulting in death
4.1% 
3.9% 
3.7% 
3.5% 
3.3% 
3.1% 
2.9% 
2.7% 
2.5% 
Trends in mortality rate of all GI bleeds 
3.99% 
3.81% P < 0.05 
3.70% 
3.44% 
3.22% 
3.11% 
2.85% 2.93%2.85% 
2.73% 
Length of stay of all GI bleeds 
4.58 4.57 
P < 0.05 
4.51 4.49 4.47 4.44 4.43 
4.38 
4.34 
4.29
Length of stay (in days) 
4.1 
P
Ethics	 267 
FIGURE 9.7  NIS database analysis of GI bleeds from 2001 to 2010. 
Ethics. We aspire to a universal code of ethics that ethically supplies equal medical care for all individu­

als without any qualifications. On that note equal medical care is often difficult to obtain. New tools are 
available such as CDSS and the new generation of expert systems, cell phone based, that may level the 
playing field, i.e., provide equal care regardless of income, a more ethical medical system. 
Questions 
Level I 
 1.  What is medical ethics? 
 2. Explain the Hippocratic Oath. 
 a. 	 What are the differences between the original (fifth century BC) and the modern version in 
1964? 
 3.  The American Medical Association (AMA) periodically updates a code of medical ethics. How is  
that related to the Hippocratic Oath? 
 a.	  Are there any differences? 
 4. What is the role of the AMA Council on Ethical and Judicial Affairs? 
 a.  What areas of medical ethics are they responsible for? 
 b. What enforcement capabilities do they have?

a.  What areas of medical ethics are they responsible for? 
 b. What enforcement capabilities do they have? 
 c.  What role do they play in judicial functions related to breaches in medical ethics? 
 5.  What is the primary focus of the American Nurses Association (ANA) code of ethics? 
 a. How do these differ from the AMA Code of Ethics?

268 Biomedical Informatics 
Level II 
 6 .  Th e  AMA  p r o vi d e s  gui d e l i n e s  an d  c a s e  s t u di e s  u s e d  i n  m e di c al  e d u c a ti o n .  Wh a t  r o l e  d o  y o u  
believe these case studies play in medical education? 
 a. Summarize the case study on “Impaired Drivers.” 
 b.  Summarize the case study on “Gifts to Physicians from Industry.” 
Level III 
 7. What is a clinical decision support system (CDSS)? 
 8.  How are neural networks used to analyze medical data? 
 a.  Explain the superposition theory versus a nonlinear system used in neural networks. 
 9. How is computer-aided diagnosis used to aid physicians in their practice of medicine? 
 10. What is the Nationwide Inpatient Sample (NIS) database? 
 a. How is the NIS used to aid in diagnosis? 
 11. Research a real-world example of a CDSS. 
Glossary 
The American Medical Association (AMA) Ethics Group sets guidance for physicians to pursue. The

Glossary 
The American Medical Association (AMA) Ethics Group sets guidance for physicians to pursue. The 
Ethics Group has three parts: Council on Ethical and Judicial Affairs, Ethics Resource Center, 
and Institute for Ethics. 
The American Nurses Association (ANA),  similar to the AMA, periodically produces a  code of ethics,  
which was last updated in 2001, that certified nurses have to read, understand, and act upon. 
The Hippocratic Oath  dates back to the fifth century BC describing the responsibility of physicians to 
focus on the well being of their patients. 
The Council on Ethical and Judicial Affairs (CEJA)  focuses on periodic updates of the Code of Medical 
Ethics. 
A clinical decision support system (CDSS)  is an expert system, artificial intelligence software, or accu­
mulated medical knowledge to assist a medical practitioner in diagnosis or treatment.

mulated medical knowledge to assist a medical practitioner in diagnosis or treatment. 
Ethics  d e fi n e d  b y  t h e  M e r r i a m - W e b s t e r  d i c t i o n a r y  i s  “ A  t h e o r y  o r  s y s t e m  o f  m o r a l  v a l u e s ”  o r  
 professional ethics as “the principles of conduct governing an individual or a group.” 
Hippocratic Oath, dates back to the fifth century BC describing the responsibility of physicians to focus 
on the well being of their patients. 
The Litigation Center of the American Medical Association  and State Medical Societies, established in  
1995, as part of the AMA physicians’ resource center provides physicians with legal expertise 
assistance. 
The National Inpatient Sample (NIS) Database  is a federal state industry partnership that has cur­
rently, as 2014, 40 million inpatient hospital stays. 
Neural networks  are defined as systems that are modeled after living biological organisms. 

 1. Swendiman, K. (2012). Health care: Constitutional rights and legislative powers, http://www.fas. 
org/sgp/crs/misc/R40846.pdf. 
 2. AMA Medical Ethics, https://www.ama-assn.org/ama/pub/physician-resources/medical-ethics. 
page. 
 3. AMA journal of Ethics virtual tutor, http://virtualmentor.ama-assn.org/site/cases.html. 
 4. Nationwide Inpatient Sample Database, (2012). https://www.hcupus.ahrq.gov/nisoverview.jsp

10.1 	 Introduction ......................................................................................270
 
10.2 	 Episodic versus Dynamic Documentation ...................................272
 
10.3 	 Critical Care Unit .............................................................................272
 
10.4 	 Documentation for the Hospitalized Patient ...............................274
 
Time-Sensitive Documentation • Documenting Medication
 
Administration • Interdisciplinary Plan of Care • Documenting 
Physiologic Parameters • Evolution from Paper to Computers: 
Capturing Nursing Activities • Elements of Nursing 
Documentation • Computer-Based Documentation
 
10.5 	 Nursing Priorities for an Electronic Health Record....................287
 
Data Entry • Reports • Data Retrieval: We have Entered the Data but 
Where Did It Go?
 
10.6 	 Literature Review ..............................................................................292

10.7 	 Implications for Future Research ...................................................295
 
10.8 	 Electronic Documentation: The Good, the Bad,
 
and the Potential ...............................................................................296
 
10.9 	 Critical Care Unit in 2025 ...............................................................299
 
10.10 Summary ............................................................................................303
 
Questions .......................................................................................................304
 
Glossary .........................................................................................................304
 
References ......................................................................................................307 
 
10 
Critical Care Nursing

10 
Critical Care Nursing 
Perspective on the 
Electronic Health Record 
269

270 Biomedical Informatics 
10.1 Introduction
 
The fact that activities relating to nursing care need to be documented is nothing new. From the time 
that Florence Nightingale brought order and science to the nursing profession, there have been written 
records. What has changed, however, is the method and means of documenting, evolving from the sim­
ple paper and a pen to the sophistication of computer-based systems. The content of the documentation 
has also evolved with much of it now mandated by regulatory agencies, third-party payers, and govern­
ment agencies as well as the legal aspect of the record, which is summarized in the adage surrounding 
malpractice lawsuits that admonishes: “If it wasn’t documented, it wasn’t done.” 
Regulatory agencies look to documentation in the medical record to determine if an institution is 
meeting the standard of care for patient safety. These include bodies such as The Joint Commission

meeting the standard of care for patient safety. These include bodies such as The Joint Commission 
(TJC) on Hospital Accreditation and the Departments of Health of varying states. Each year TJC estab­
lishes a list of National Patient Safety Goals (NPSGs) , and the medical record serves as part of the evi­
dence to document that these have been met. For 2014, the safety goals were as follows: identify patients 
correctly; improve staff communication; use medications safely; use alarms safely; prevent infections; 
identify patient safety risks; and prevent mistakes in surgery. 
The reimbursement that a facility receives depends on what is documented in the record. Private 
insurance companies scrutinize the contents of the record to determine whether physician orders for 
treatment reflect the patient’s diagnosis and whether there is documentation that these treatments were 
actually carried out. The Centers for Medicare and Medicaid Services (CMS) also determine the stan­

dard of care that needs to be met for reimbursement. In 2007, CMS implemented a 0% complication 
rate for a number of clinical diagnoses, including a Stage III and IV pressure ulcer acquired during a 
hospital stay. These complications are considered to be both serious and preventable and are considered 
to be “never events.” If there is inadequate documentation that a patient was admitted with the wound, 
CMS will determine that it developed while the patient was hospitalized and reimbursement will be 
denied. Additional days added to the hospital stay relating to the pressure ulcer may be denied as well. 
The purpose is to provide a financial incentive for hospitals to provide the best care possible and to avoid 
complications for patients. The importance of this documentation mandates that entering it correctly 
should be as easy as possible, with ample reminders of omitted data.

should be as easy as possible, with ample reminders of omitted data. 
In 1999, the Institute of Medicine (IOM) published To Err is Human  in which they concluded that 
there were approximately one million preventable hospital deaths in the United States. As a result of 
this, The Committee on Quality of Healthcare in America of the IOM proposed wide-ranging strategies 
that should be implemented to reduce preventable medical errors. One of the prime recommendations 
of the group was the need to implement a computerized health record system to facilitate improvement 
in patient safety. In 2003, they defined a basic electronic health record (EHR) as “a longitudinal col­
lection of electronic health information about a person, or healthcare provided; Immediate electronic 
access to a person or population level information by authorized users; Provision of knowledge and 
decision-support that enhances the quality, safety, and efficiency of patient care; and Support of efficient

decision-support that enhances the quality, safety, and efficiency of patient care; and Support of efficient 
processes for healthcare delivery.” 
The move toward EHRs received a further push forward in February of 2009 when President Barack 
Obama signed the American Recovery and Reinvestment Act, a $787 billion economic stimulus pack­
age that allocated $19 billion as financial incentives for providers to adopt EHR technology. In order to 
obtain financial incentive payments, facilities had to prove that they have achieved a specific level of 
meaningful use  beginning in 2014. 
In 2009, EHRs generated $973.2 million in business, and by 2012, this had grown to $6.5 billion as 
facilities who might otherwise have considered deferring implementation chose to move more quickly 
in order to meet meaningful use for 2014. With this rapid adoption of EHRs, in many settings, the focus 
has been primarily on ensuring that those parts of the record that support meaningful use are the focus.

has been primarily on ensuring that those parts of the record that support meaningful use are the focus. 
While this is a reasonable business decision, it has sometimes been at the expense of not addressing 
other aspects, such as the ease of entering data by the frontline users of the systems.

271 Critical Care Nursing Perspective on the Electronic Health Record 
The transition to computer-based documentation has affected all members of the healthcare team 
in all settings, both inpatient and outpatient. However, the documentation requirements for hospital-
based nurses present challenges that are not experienced by other disciplines. And in the hospital set­
ting, critical care nurses face the most complex documentation challenges because of the quantity of 
information and the speed with which it needs to be recorded, combined with the need to instantly 
access that information to drive patient care decisions. 
The focus of this chapter is to explain the complexity of critical care nursing in the context of the data 
that are generated and the process of recording those data. Documenting patient care activities during 
emergency situations, which occur often in the critical care setting, is particularly challenging because

emergency situations, which occur often in the critical care setting, is particularly challenging because 
many activities are occurring simultaneously. An added dimension to the documentation challenge for 
critical care nurses is that they are typically also providing care for the patient at the same time that they 
are trying to document. This differs from most other disciplines, including physicians, who document 
their care activities after the fact. They are able to provide care to the patient and then enter the details 
about that care into the record. Nurses, on the other hand, not only document the activities that they 
have performed, but they also document the patient’s status through vital signs, systems assessment, 
medications, and events that occur continuously at over a 24 hour period. The needs of critically ill 
patients are complex, and they are always at risk for adverse events. Because nursing is the only disci­

pline to provide continuous care over a 24/7 basis, nursing documentation is key to providing a coherent 
view of the patient’s hospital course (Figure 10.1). 
The quantity of data to be entered in a critical care unit is enormous and includes multiple vital signs 
and hemodynamic parameters as well as data about the settings on multiple devices. The data need to 
be entered not only at frequent intervals but also quickly and accurately and in close proximity to the 
time that the event occurred. Data retrieval is also a challenge because once entered, it needs to be dis­
played in a manner that facilitates making sense of the information, so that sound clinical decisions are 
supported. It is nursing documentation that provides most of the data that are required for meeting the 
requirements of the regulatory agencies and third-party payers.

requirements of the regulatory agencies and third-party payers. 
FIGURE  10.1 (See color insert.) A critical care nurse provides care for a patient in the immediate postoperative 
period after cardiac surgery.

272 Biomedical Informatics 
10.2 Episodic versus Dynamic Documentation 
Documentation patterns differ according to the setting and workflow in that some is episodic, while 
other documentation is dynamic. A physician’s office or a clinic where a patient is seen intermittently 
has a different workflow than a critical care unit in a hospital. The office or clinic visit is episodic in 
nature, whereas the critical care unit has a workflow characterized by continuous ongoing observation 
and interaction with the patient that will continue over a 24 hour period. The events of the office visit 
will be recorded, including the patient’s current vital signs, complaints, or concerns that brought the 
patient into the office for that visit and the plan for follow-up. All documentation that is recorded will be 
a summary of that one visit. There will be no further entries on the patient’s record until the next visit,

a summary of that one visit. There will be no further entries on the patient’s record until the next visit, 
unless it is to record test results or a phone consultation. Trends and changes in the patient’s status will 
reveal themselves over weeks to months depending on the frequency of patient visits. 
In contrast, the documentation requirements for a critically ill patient will be dynamic and con­
tinuous. The volume of data is copious and needs to be entered quickly and at frequent intervals. An 
example of this is the documentation that occurs during a code situation. Some EHR vendors have 
packages for this documentation directly on the computer. Other hospitals have chosen to keep that 
documentation on the paper code sheet, in which case the paper form will become a permanent part of 
the medical record. Alternatively, in some settings, the code data that have been recorded on the paper

the medical record. Alternatively, in some settings, the code data that have been recorded on the paper 
form will be transcribed into the EHR after the fact. This practice requires double charting of the same 
information. 
A t  p r ese n t,  m ost  EHRs  fun cti o n  bette r  in  d ocum e n tin g  sta ti c  an d  ep isodi c  da ta  than  th ey  d o  in 
handling dynamic and continuous data. This is not due to an issue of capability, but in decisions that 
hospitals have made in where to spend their limited dollars to implement the EHR system in time to 
achieve the meaningful use mandates. The technology exists to support easier documentation for criti­
cally ill patients, but it involves an additional financial expenditure to fully utilize the technology that 
enables cardiac monitors and other biomedical devices to communicate with the EHR and directly 
download data. 
10.3 Critical Care Unit

10.3 Critical Care Unit 
The current capability of today’s intensive care units to support critically ill patients is astounding. 
There are numerous monitoring and infusion devices, all of which generate data or alarms that require 
attention. There are biomedical support devices that require close observation and also have settings 
and readings to interpret and record. Depending on the stability of the patient, the vital signs will be 
recorded every 1–2  hour. However, the vital signs that are recorded on a critically ill patient will be 
far more extensive than just the usual temperature, pulse, and respiration . A full set of vital signs will 
often include temperature, heart rate, cardiac rhythm, and blood pressure (systolic/diastolic and mean) 
obtained via arterial line or via cuff, pulmonary artery pressure (PAP) (systolic/diastolic and mean),

obtained via arterial line or via cuff, pulmonary artery pressure (PAP) (systolic/diastolic and mean), 
central venous pressure (CVP), oxygen saturation via pulse oximetry, cardiac output (CO), cardiac 
index (CI), and systemic oxygen consumption percent. If the patient is on a ventilator, as is common 
in someone who is critically ill, the data recorded will also include the airway type (endotracheal tube 
or tracheostomy), the mode of support from the ventilator, the oxygen concentration, the tidal volume, 
the respiratory rate from the ventilator and any breaths that the patient is able to generate, continuous 
positive airway pressure settings, or positive end expiratory pressure (PEEP) levels. A patient who is in 
cardiogenic shock or heart failure may have an intra-aortic balloon pump (IABP) in place, which will 
also generate data to record. This will include the frequency of counterpulsation (1:1, 1:2, 1:2) as well as

also generate data to record. This will include the frequency of counterpulsation (1:1, 1:2, 1:2) as well as 
arterial blood pressure reflecting balloon augmentation: systolic, augmented diastolic, end diastolic, 
and mean arterial pressure (MAP) (Figure 10.2). 
Any medications that the patient is receiving via continuous intravenous (IV) infusion are docu­
mented hourly to include the dose (e.g., mg/min or mcg/kg/min) as well as the hourly volume that is

273 Critical Care Nursing Perspective on the Electronic Health Record 
FIGURE  10.2  (See color insert.) The data that are generated on a critically ill patient often include far more than 
just vital signs. Pictured are the screens from a continuous cardiac output monitor, an intra-aortic balloon pump, a 
continuous renal replacement therapy device, and a ventricular assist device. All of the aforementioned parameters 
and numbers are recorded every hour. 
infused to deliver that dose (mL/h). A patient in a critical care unit might have as many as 9 or 10 con­
tinuous IV infusions, delivered via an infusion pump. All IV fluids are recorded each hour for inclusion 
in the patient’s fluid intake. Besides the IV medications, the patient usually requires multiple additional 
medications to be administered and documented. Some of the medications that the patient requires are 
titrated according to desired effect, for example, to improve blood pressure. If the blood pressure drops

titrated according to desired effect, for example, to improve blood pressure. If the blood pressure drops 
below the specified parameter, the nurse will change the dose and rate of the medication and will docu­
ment this change. 
Administering blood products is considered to be a high-risk process. If the patient requires blood 
products, it is critical that a patient receives the correct blood that is matched according to blood type 
and cross matching in the Blood Bank. To ensure that the correct blood transfusion is administered, two 
nurses check the unit of blood together before it is administered. They will carefully match the patient’s 
name and medical record number on the identification bracelet to the label on the blood product and 
the accompanying slip. Vital sign monitoring will be more frequent, while the blood is infusing to detect 
whether a transfusion reaction occurs. 
Patients in a critical care unit frequently have a catheter in place for urine drainage and accu­

rate o utp ut measuremen t. The vol ume is measured ev ery ho ur . H o w ev er , it is not uncommo n f or 
critically ill patients to experience acute renal failure as a complication of their underlying illness. 
The treatment is to start acute dialysis utilizing a process known as continuous renal replacement 
therapy (CRRT) via a large-bore dual-lumen venous catheter. The nurse manages the CRRT device 
that includes priming the tubing and then monitoring the fluid volume shifts, pressures, and elec­
trolyte changes. The nurse will record the range of pressures hourly that indicate the functioning of 
this device as well as the volume of the various solutions that are utilized to accomplish this form 
of dialysis. 
Patients in acute or end-stage heart failure may have advanced support devices such as an IABP or

Patients in acute or end-stage heart failure may have advanced support devices such as an IABP or 
a ventricular assist device in use, either as a short-term device used while the heart recovers or as a

274 Biomedical Informatics 
long-term implanted device that the patient will go home with. Each of these devices requires expert 
nursing care to ensure that the devices are operating safely and to support and monitor the patient dur­
ing the use of this therapy. In addition, each device generates data that will be recorded hourly. 
However, in any discussion about the environment of a critical care unit, the most important point 
to understand is that patients who are critically ill are more than just a collection of devices and data. 
They are people who are at risk for multiple complications and who are under tremendous stress in 
an alien environment. They require expert medical and nursing care as well as multiple interventions 
to decrease the risk of developing complications such as pneumonia, bloodstream or urinary tract 
infections, pressure ulcers, blood clots, and wound infections. They need to have their pain relieved 
and their fears addressed.

and their fears addressed. 
The family members of critically ill patients also need support and explanations about what is 
happening to their loved one, and they need to have their questions answered. An intensive care unit 
can be an overwhelming place. The monitoring and biomedical support devices that are in use are 
foreign to most people, and family members are often devastated at having their loved one in this 
setting. 
It is the nurse at the bedside who is with the patient and the family 24 hours a day, every single 
day. Many complications and hospital acquired conditions (HACs) can be prevented by attentive 
nursing care. However, documentation is also extremely important. Data need to be entered cor­
rectly in order to be useful and to facilitate making sound decisions about patient care. As EHRs are

rectly in order to be useful and to facilitate making sound decisions about patient care. As EHRs are 
implemented more widely, it is critical that attention is given to the process of entering data to ensure 
that it is intuitive, easy to use, and viewable in a format that supports correct interpretation to drive 
patient care. In looking at the care requirements of a critically ill patient, it is logical to suggest that 
the best use of a nurse’s time is not to be spent typing data into a computer when the technology 
exists that would allow for most of the monitors, infusion pumps, and devices to download their data 
directly into the patient’s EHR. 
10.4 Documentation for the Hospitalized Patient 
There are standard elements of documentation that are included for all hospitalized patients. The admis­
sion data that are collected during an initial encounter with a patient consist of a detailed history and

sion data that are collected during an initial encounter with a patient consist of a detailed history and 
physical examination, including listing all medications that the patient has been taking at home. This 
list is reconciled by the physician with medication orders written on admission to ensure that consid­
eration has been given as to whether these medications will be continued or held while the patient is in 
the hospital. The physician will again reconcile this list on discharge to ensure that home medications 
that were not ordered while the patient was hospitalized are considered for resumption after the patient 
has been discharged. The objective is to avoid missing a medication that the patient needs to be taking 
on a long-term basis. 
Based on the results of the diagnosis and admission history and physical exam, the physician writes 
the initial set of orders for the patient. The admission orders include diet, activity, medications, labora­

tory, and any other diagnostic tests as indicated. Each day, the physician is also required to write a prog­
ress note that documents the current status of the patient. This typically includes the current summary 
of vital signs and lab and other diagnostic test results and concludes with the current impression of the 
patient’s status and the plan for further care. 
Besides the attending physician, many other disciplines document in the medical record of a hospital­
ized patient. This includes physicians who have been called in on consult, fellows, residents, staff nurses 
assigned to care for the patient, nurses called in on consult such as wound care specialists or nurse 
practitioners, physician assistants, respiratory therapists, physical therapists, occupational therapists,

practitioners, physician assistants, respiratory therapists, physical therapists, occupational therapists, 
speech therapists, nutritionists/dieticians, social workers, and case managers. Each discipline docu­
ments somewhat differently depending on the nature of their relationship with the patient and the type 
of care that is rendered.

275 Critical Care Nursing Perspective on the Electronic Health Record 
10.4.1 Time-Sensitive Documentation 
Some forms of documentation are time sensitive , while others are not. For example, in performing 
patient or family education , it is not essential to differentiate whether the nurse taught the newly diag­
nosed diabetic patient to count carbohydrates and administer insulin at 9:30 or 10:30 a.m. Therefore, the 
documentation does not have to be completed at the exact moment that it was done. The critical infor­
mation is the education that occurred, the specific content that was included, and the patient’s response 
to the education and plans for follow-up education. It is not extremely relevant that this information be 
documented at the precise time that it took place. 
In contrast to this, vital signs and hemodynamic parameters are extremely time sensitive. It is as 
important to know precisely when the blood pressure was 74/50 as it is to know that it decreased to that

important to know precisely when the blood pressure was 74/50 as it is to know that it decreased to that 
level. It is also important to know what time the previous blood pressure was recorded to determine 
the span of time that it took for the pressure to fall. In addition, it is also important to know any other 
events that were happening at that time, for example, ventilator settings, as well as any medications or 
volume administered. 
10.4.2 Documenting Medication Administration 
The process of administering medications in the hospital setting bears explaining, in terms of both the 
process and the required documentation. The process is initiated when the physician orders a particular 
medication. With an EHR, the physician does not have to be physically present in the unit to write the 
order. He or she can enter an order from any location. The pharmacist then profiles this medication

order. He or she can enter an order from any location. The pharmacist then profiles this medication 
to cross-check it against documented allergies that the patient has or for any potential interactions 
between other medications that have been prescribed during this visit. A message is then sent to the 
dispensing system (often a computer-based automated system) so that it will recognize the request to 
administer this medication at the scheduled time. If an EHR is in use, the pharmacist will also trigger 
the medication to appear in the electronic medication administration record (eMAR). Along with the 
name of the medication, the information on the eMAR will include the dose, the route (by mouth, by 
injection, etc.), the frequency (once a day, every 6 hours, etc.), and the time that the medication is due to 
be administered. At this point, the nurse will be able to scan the patient’s identification bracelet, scan the

be administered. At this point, the nurse will be able to scan the patient’s identification bracelet, scan the 
medication, and then click to confirm that the medication has been administered (Figure 10.3). 
Prior to the transition to a computer-based system, an order for a medication would be generated by 
the physician by either writing the order or giving the order to the nurse via telephone. Once an order 
was obtained, two things would happen. The actual order would be transcribed onto a paper medication 
administration record (MAR) with the type of medication being differentiated according to how it was 
going to be administered. Options include medications to be administered on a set schedule around the 
clock, medications that were to be given immediately or STAT as a onetime dose, and medications to be 
given as needed based on the patient’s status, such as an analgesic ordered to be given if the patient had

given as needed based on the patient’s status, such as an analgesic ordered to be given if the patient had 
pain. On the MAR, the name of the medication would be transcribed as well as the date and time that it 
was ordered, the date and time that it would expire and would have to be renewed, the dose, and the fre­
quency, and then the specific times that the medication was to be given would be written in. Each MAR 
would have space to write the dates across the top. As the nurse administered a particular medication, 
he or she would initial the space corresponding to the date and time (Figure 10.4). 
When administering medications, nurses adhere to the five rights  in order to avoid a medication 
error. These five rights are the right patient, the right medication, the right dose, the right route, and 
the right time. With a paper record, the method of ensuring that these five components were correct

the right time. With a paper record, the method of ensuring that these five components were correct 
included looking at the patient’s identification bracelet and asking the patient to state his or her name if 
possible and to compare that to the name on the MAR where the medication is listed. To confirm that 
it was the right medication, for the first dose that was administered when a new order was written, the 
nurse would compare the written order in the chart with the details that had been transcribed onto

276 Biomedical Informatics 
Source: http://www.pearsonhighered.com/realehrprep/learn-about/what-is.html 
FIGURE  10.3 An example of an electronic medication administration record. The name of the medication, the 
dose, route of administration, and frequency are in the left column. 
FIGURE  10.4 An example of a paper medication administration record.

277 Critical Care Nursing Perspective on the Electronic Health Record 
the MAR. This would partially verify the name of the medication, the dose, the route that it was to be 
administered, and the frequency and times that it was scheduled. To continue checking the five rights, 
in all instances after the initial administration where the original order would be compared to the MAR, 
the nurse would use the MAR as the standard for comparison. To verify that it is the correct medication, 
route, and dose, the nurse would compare the medication in hand to what was written in the MAR. The 
right time would be verified by comparing the actual time of administration with the scheduled time 
on the MAR. After completing all of these steps, the nurse would proceed and give the medication and 
then initial the MAR to complete the documentation. 
The process of administering medications using a computer-based system is designed to accomplish

The process of administering medications using a computer-based system is designed to accomplish 
all of these safety steps. With an electronic record, the physician enters the order into the computer. The 
physician can select from a menu of order sets and then modify them with drop-down menus. If there 
are orders that a physician uses often, he or she can save them as a favorite, so that they are easier to 
generate in the future. Once the order is electronically generated and signed by the physician, it is visible 
to the nurses who will electronically sign to acknowledge the order. At the same time, any medications 
that are included in the order will be visible to the pharmacist who will profile the medication in com­
parison to the patient’s list of allergies and other medications to check for interactions. When this step 
is complete, the pharmacist will trigger the medication to appear in the electronic MAR. This serves the

is complete, the pharmacist will trigger the medication to appear in the electronic MAR. This serves the 
same purpose as the paper MAR, in that it summarizes all aspects of the order and triggers the nurse 
when it is time to administer the medication. 
At some point, all hospitals using EHRs have introduced or will introduce a method of bar-code scan­
ning for medication administration, as well as for identification with other processes. This is actually 
using the computer to the fullest extent and it changes radically the way that nurses administer medica­
tion. In the previous description of medication administration and the five rights, it was clear that the 
entire burden for verifying that everything was correct was the nurse’s responsibility, in other words, 
relying totally on human factors. When medication errors occurred, they were often due to human error 
if someone administering a medication was interrupted or distracted or if there were issues of legibility

if someone administering a medication was interrupted or distracted or if there were issues of legibility 
in reading the handwriting on the MAR. A bar coding system addresses the five rights and supports the 
process of medication safety. 
With a bar coding capable EHR, the nurse will determine that a medication is due at a particular 
time and will initiate a medication administration window that displays all medications that are due 
to be given at that time. The nurse will remove the medication from the medication dispensing system 
and will bring the medications and the computer to the patient’s bedside. The first step is to scan the bar 
code on the patient’s identification bracelet and then scan the bar code on the medication that is to be 
administered. This step verifies that it is the correct patient and confirms that it is the correct medica­
tion, dose, route, and time. When the nurse has administered the medications, he or she will confirm

tion, dose, route, and time. When the nurse has administered the medications, he or she will confirm 
and electronically sign the medication. 
The previous discussion about the advantages of the electronic record would not be complete without 
the caveat that everything does not always work as designed. Patients inexplicably disappear entirely, 
individual medications disappear from the eMAR without explanation, and entries that a nurse is sure 
that he or she has entered correctly are nowhere to be found. 
10.4.3 Interdisciplinary Plan of Care 
The interdisciplinary plan of care (IPOC) incorporates the planned activities of all disciplines that are 
designed to meet the individualized goals for the patient. Besides serving as a template to guide the 
patient care activities, an appropriate and individualized IPOC is required by most regulatory bodies, 
including CMS and TJC. 
Regulatory agencies require that all members of the healthcare team collaborate on the patient’s plan

Regulatory agencies require that all members of the healthcare team collaborate on the patient’s plan 
of care; hence, it is usually referred to as the IPOC. The IPOC serves as the roadmap to identify the goals 
for the current hospital stay, along with the strategies to meet those goals. Even for critically ill patients,

278 Biomedical Informatics 
this is a form of static rather than dynamic documentation, and it is one form of documentation that 
is more effective on a computer than on paper. Prior to the EHR, hospitals struggled with the IPOC 
when it was a paper-based form. In the 1960s to 1970s, the IPOCs were entirely handwritten, if they were 
done at all. And even if they were written on admission, they were rarely updated. At best, they were 
not comprehensive, since it simply took too long to write everything out. At worst, they were written 
in pencil and were discarded when the patient was discharged. To address these deficiencies, a com­
mon solution was to create a preprinted standard IPOC that was diagnosis based, with predetermined 
goals and interventions. There was space to customize as needed, but these documents were often not 
updated. In addition, with a paper format, most patients had only one IPOC generated, despite having

updated. In addition, with a paper format, most patients had only one IPOC generated, despite having 
multiple problems. It was simply not feasible to add multiple IPOCs for documentation, or to revise 
them as the needs of the patient changed. During visits from TJC or CMS, surveyors expected the IPOC 
to be individualized to the specific patient. On paper, this requirement was often cited as being deficient. 
Computer-based systems have solved most of these problems. For any given diagnosis of the patient, 
there are many IPOCs to choose from. Additionally, based on the diagnosis and problem list that has 
been entered for the patient, the computer will often suggest potential IPOCs. Once an IPOC has been 
selected, the nurse can review the optional interventions and choose those that are most applicable for 
the patient and delete those that are not. This results in an IPOC that is truly individualized for the spe­

cific patient. As part of daily documentation, the nurse can indicate whether each prescribed interven­
tion to meet the goal was done or not done and can sign off on the goals once they are met. 
One aspect of the IPOC that is more problematic in a computer-based system than a paper-based 
system is the issue of access to different parts of the EHR by different disciplines. To maintain pro­
tected health information of individuals, in compliance with the HIPAA requirements, each individ­
ual who documents in the patient record has access to only those parts of the record that are required 
for patient care. This means that different disciplines accessing the record will see different versions 
of it electronically. Unfortunately, this sometimes includes the IPOC, where each discipline sees only

of it electronically. Unfortunately, this sometimes includes the IPOC, where each discipline sees only 
certain IPOCs and documents separately on them, rather than all disciplines seeing the same IPOCs 
regardless of which discipline initiated it. Ironically, in those instances, the IPOC reflects only one 
discipline at a time. U ndoubtedly , this issue will be resolved as EHRs evolve, but at present, it is a 
problem that exists in many institutions. 
10.4.4 Documenting Physiologic Parameters 
Physiologic parameters, such as vital signs, are arguably the most difficult type of data to record because 
of the frequency with which they need to be recorded. Any monitors that have been designed within 
the past 10 years have the capability of communicating with computer-based documentation systems. 
In addition, most of the life-support devices that are used with critically ill patients are already capable

In addition, most of the life-support devices that are used with critically ill patients are already capable 
of downloading data either directly into the EHR or to the monitoring system, which will then down­
load the data to the EHR. Devices that are designed to communicate with the EHR or with the moni­
toring system include ventilators, IABPs, hypothermia devices, smart infusion pumps, and also CRRT 
devices. This form of automatic data entry is in use in some hospitals today, but certainly not in the 
majority. The problem is that this is usually an add-on feature of the EHR vendor and is available at an 
additional charge. Many hospitals opt not to purchase this feature when they initially go live with their 
EHR. The lack of this feature has the greatest impact on the critical care nurse. 
In the absence of communication capability between the monitor and the EHR, vital signs will be

In the absence of communication capability between the monitor and the EHR, vital signs will be 
entered manually. In contrast to information such as a system assessment, which will lend itself to a 
drop-down menu of choices, entering physiologic data does not fall into this category since a patient’s 
vital signs will not conform to a standard set of choices. Vital signs consist of numbers and if those 
numbers are not downloaded directly from the monitor, they must be typed into the electronic record 
by the nurse. In addition, there is a significant difference in frequency; assessments will be performed no 
more frequently than every four hours, but vital signs on a critically ill patient will be recorded at least

279 Critical Care Nursing Perspective on the Electronic Health Record 
every hour and at times even more frequently if the patient is particularly unstable. Going forward, as 
the important milestones of meaningful use benchmarks are successfully achieved, attention will have 
to turn toward improving the process of data entry. 
10.4.5 Evolution from Paper to Computers: Capturing Nursing Activities 
The earliest critical care units were created in the late 1960s and into the 1970s. The most sophisticated 
tools for documenting patient care activities were paper and a pen, and vital signs were documented on 
a graphic sheet. There was an additional document that was called “Nursing Notes,” which was used to 
record the results of the nurse’s assessment of the patient as well as any other noteworthy events that 
occurred during the shift. The format was unstructured and the notes page had the appearance of a

occurred during the shift. The format was unstructured and the notes page had the appearance of a 
sheet of loose-leaf paper. Because it was unstructured, each nurse used a slightly different format, even 
in doing a head-to-toe assessment. The language and abbreviations might vary from nurse to nurse. 
In retrieving the information, it was not always clear where to look, since everyone’s notes differed 
slightly. It was also easy to miss documenting something since there were no triggers to remind the 
nurse of what was missing and still needed to be documented. For newer nurses, there were also no trig­
gers to remind the nurse about the components of the assessment. 
In the 1980s, as the care of critically ill patients became more complex with more data available, the 
paper record began to undergo a change. Vital signs moved to a redesigned flow sheet where all data 
were aligned across the sheet according to the time that they were recorded. These data included the

were aligned across the sheet according to the time that they were recorded. These data included the 
hourly intake and output, laboratory results, and all medications that were being administered by con­
tinuous IV infusion. Most critical care units had some form of a flow sheet at this time. They were often 
foldout–type documents of three or four connected sheets. The flow sheet was efficient because it opened 
up to be able to view multiple hours together with all parameters as well as events. Every item of data that 
the nurse was monitoring hourly on a patient was recorded on this sheet, so it was very easy to ascertain, 
at a glance, how the patient was doing just by looking at this sheet. The flow sheets were typically kept at 
the bedside on a clipboard. Documentation was very easy because there was a space for everything and 
the information was arranged in an organized manner. Assessments were organized on the back with a 
space designated for each system.

space designated for each system. 
With the advent of critical care units, patients who were hospitalized were sicker because newer tech­
nologic advances that could support failing body systems allowed them to survive complications that 
would have previously resulted in death. There were more technologies, treatments, medications, and 
surgical interventions as well as support devices. Patients unable to breathe on their own had breath­
ing tubes placed and were supported by ventilators—machines that delivered oxygenated breaths to 
the patient and allowed the patient to exhale passively. Those whose kidneys were failing were treated 
with hemodialysis or acutely with peritoneal dialysis. Cardiac support devices included the IABP. 
Medication infusion pumps began to replace the original method of counting the drops as a method of

Medication infusion pumps began to replace the original method of counting the drops as a method of 
calculating the dose. More sophisticated methods of monitoring the patient’s status also became avail­
able. Catheters could be placed in an artery to measure blood pressure and in a central vein to measure 
venous pressure. Procedures that once could be conducted only in specially designated cardiac catheter­
ization units could now be performed at the bedside, thus creating new vital signs such as PAPs, CO, CI, 
and SVO2 to reflect systemic oxygen consumption. 
On the flow sheet, items were typically arranged in the order that they appeared on the monitor so that 
the data could be easily entered. Time synchronicity occurred across the flow sheet in that events that 
occurred at the same time were aligned with each other. For example, the vital signs that are recorded at 
a particular time will align with the ventilator settings, fluid volume intake and output, notable events

a particular time will align with the ventilator settings, fluid volume intake and output, notable events 
that have occurred, and the current doses of all medications that are being administered via continu­
ous infusion. Laboratory tests such as arterial blood gas results will also align with the vital signs and 
ventilator settings for more accurate interpretation. The information to be recorded was prompted by 
the column headings and blank spaces. In looking at the data spread across the timeline, the patient’s

280 Biomedical Informatics 
status could be assessed at a glance with all events that occurred at the same time aligned. Moving down 
the sheet, trends were easy to discern by looking at changes in the vital signs and other parameters over 
time. Visually, it was easy to follow the data because the nurse would enter the exact time that the entry 
occurred and could choose to skip a line or not, but there was very little distracting space on the sheet 
(Figure 10.5a and b). 
In addition to recording vital signs and assessment parameters, many flow sheets also had a column 
called “event.” An event could be something as simple as a patient getting out of bed or as complex as 
a patient being extubated and able to breathe independently. There was often another column labeled 
“Stat Medications.” The purpose of this column was to record medications that were given emergently 
as a single dose, often in response to a change in the patient’s condition. These medications were docu­

mented in the MAR but were recorded in this column on the flow sheet so that the medication could be 
correlated with the vital signs and other parameters that reflected the patient’s status. This allowed for a 
complete picture of the patient’s status to be viewed as a snapshot in time (Figure 10.6). 
(a) 
(b) 
FIGURE  10.5 (a) An example of a flow sheet from a cardiothoracic intensive care unit. The vital signs were aligned 
along according to time. Emergency medications could be correlated with the vital signs to present a full picture of 
the patient. (b) In addition to vital signs, the typical critical care flow sheet also continued across the time line with 
space to record intake and output, each hour with a cumulative running total. The preceding example also has space 
to record the ventilator settings and arterial blood gas values.

281 Critical Care Nursing Perspective on the Electronic Health Record 
FIGURE  10.6 The same page of the flow sheet continued across the timeline with an “Events” column for the 
nurse to record anything that was unusual or noteworthy. All of the continuous medication infusions that the 
patient was receiving were also recorded on the flow sheet. With all information aligned according to the time that 
it occurred, it was easy to get an instant snapshot view of the patient’s status. 
With the increase in support devices and patient complexity, the physical assessments that were 
recorded were also more complex. The flow sheets that were designed to handle the vital signs were 
also utilized to organize the assessment data, typically on the back of the sheet. The free-form Nursing 
Notes disappeared and were replaced with designated spaces for the assessment results. Since space 
was limited, the most common solution for documenting assessment data was to create a key of abbre­

viations listing the most common assessment results. The nurse would select the number that cor­
responded to the information that he or she wanted to enter and write that number in the designated 
space. This could be viewed as the precursor to the drop-down  menu of computer-based documenta­
tion (Figure 10.7). 
Using the flow sheet, data retrieval was very easy. Information was organized together and had a logi­
cal flow. Nurses often refer to the patient’s story that is the cumulative events that have occurred during 
the hospital stay. An important component of the patient story is recording the dates and times of all 
procedures that have been performed including those that are formal surgical procedures, performed in 
the operating room (OR), as well as minor procedures that are performed in the unit, such as inserting

the operating room (OR), as well as minor procedures that are performed in the unit, such as inserting 
lines or chest tubes. With paper documentation, the story was easy to follow by reviewing the flow sheets 
to look at the “Events” column or by quickly looking at the boxes where line insertions were recorded 
(Figure 10.8a through c). 
A computer-based system somewhat mimics the advantage of serving as a reminder of assessments 
to be performed, in that all of the systems are listed with space for the specific components of the assess­
ment and a drop-down menu of choices. However, because the screen has a finite size, the nurse needs 
to scroll up or down to find the correct space for data entry or needs to click between screens to enter 
different categories of information. Some computer-based documentation systems have task reminders; 
however, they sometimes display inconsequential tasks or do not remove a task when it has been com­

pleted. This feature should be an advantage with a computer-based system, but there is still work to be 
done to ensure that the triggered tasks are meaningful and easy to view. 
Despite the need to improve on selected aspects, a computer-based system offers definite potential 
advantages. With paper documentation, the medical record of a patient who had been hospitalized for a 
prolonged period of time eventually outgrew the physical space of the binder that constituted the chart. 
In those cases, it would be necessary to thin  the chart simply because there were just too many pages 
to fit in the binder. The thinned chart would be housed elsewhere in the unit. There were guidelines as

282 Biomedical Informatics 
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283 Critical Care Nursing Perspective on the Electronic Health Record 
to which paper forms would be relocated to the thinned chart, but as often happens with human error, 
there would invariably be important documents accidentally relegated to the thinned chart resulting in 
time-consuming searches to retrieve these data. An additional aspect of the thinned chart was the hope 
that the thinned chart did not become misplaced if the patient was transferred from one unit to another 
during the hospital stay. 
All units had a designated space where the paper charts were supposed to be kept. However, because 
the same paper chart was used by every discipline with contact with that patient, the chart was inevita­
bly never where it was supposed to be. Additionally, if one person was using the chart, it was inaccessible 
to another who needed to use it. Lost charts or portions of charts are mostly eliminated as a problem

to another who needed to use it. Lost charts or portions of charts are mostly eliminated as a problem 
with the electronic records. Time is saved looking for misplaced records because one only needs to sign 
on to a computer and any chart that is needed will be instantly accessible. EHR systems in many facili­
ties are still accompanied by a streamlined version of a paper chart, which will contain records that need 
a signature from the patient or family, such as consents. 
(a) 
(b) 
FIGURE  10.8  (a) Assessment results were usually documented on the back of the flow sheet. The aforementioned 
is an example of pain documentation. The spaces are completed using the numbered choices on the bottom and left  
side of the grid. (b) Skin-assessment documentation on a paper flow sheet. There were sections and spaces on the 
back of the flow sheet that corresponded to all body systems. All of the results were visible at the same time, so that

back of the flow sheet that corresponded to all body systems. All of the results were visible at the same time, so that 
it was easy to discern the patient’s story. ( Continued )

284 Biomedical Informatics 
(c) 
FIGURE  10.8 (Continued ) (c)  Pacemaker documentation on a paper flow sheet. 
With paper-based records, additional forms for documentation were developed to handle specific 
pieces of information. Often these forms were designed to meet the documentation requirements of the 
various regulatory bodies. They were a convenient method of collecting all related information together 
in one place. Examples of this documentation included restraint forms, skin assessment/pressure ulcer 
forms, falls risk assessment, and MARs. These additional forms would often be kept on the clipboard 
with the flow sheet. The presence of the forms at the bedside served as a reminder to the nurse that this 
documentation needed to be completed. 
Another form that was typically employed was a cardstock Kardex. A separate form was created for 
each patient on admission with the basic information of name, date of admission, age, and diagnosis.

each patient on admission with the basic information of name, date of admission, age, and diagnosis. 
As diagnostic tests or procedures were ordered and completed, the Kardex would be updated with this 
information. There was space to record all IV lines that the patient had, including when they were 
inserted and removed. Likewise, catheters and any devices were recorded as well as any significant 
events that had occurred. This constituted the patient’s story and at a glance it was easy to see the trajec­
tory of the hospital stay. Many EHRs have a screen that serves a similar function. 
10.4.6 Elements of Nursing Documentation 
Nursing workflow is complex. Nurses get interrupted and have to shift to different tasks. They are 
recording vital signs, assessment data, and events continuously at the same time that they are providing 
care for the patient, interacting with the family, communicating with other disciplines, and making

care for the patient, interacting with the family, communicating with other disciplines, and making 
sense of trends in vital signs and other parameters to determine if the patient is stable. If asked to design 
the ideal computer-based documentation system, most nurses would say that the primary requirement 
is that the system must be very easy to use for inputting large amounts of data frequently and that it 
is visually friendly to enable quick and accurate interpretation of the vital signs trends and other data 
that have been entered. It should not be burdensome to enter information and there should be built-in 
reminders of critical information that has not been documented. 
As described elsewhere in this text, the nursing activities involved with caring for a critically ill patient 
might be compared to the activities of a pilot flying a plane. Both are responsible for lives, whether a

might be compared to the activities of a pilot flying a plane. Both are responsible for lives, whether a 
patient or passengers and both are exposed to large quantities of ever-changing data displayed on moni­
tors. Trends need to be noted with decisions made about air speed and altitude or blood pressure and CI. 
Both the pilot and the nurse are functioning in an environment where focus and critical thinking are

285 Critical Care Nursing Perspective on the Electronic Health Record 
essential. Given this analogy, it should not be surprising that the nursing expression for a patient who 
is deteriorating rapidly is “crashing,” certainly an aviation term for a very undesirable situation as well. 
Knowing that it is also important to record the data accurately while understanding the performance 
level that is expected of the pilot and the nurse, it seems doubtful that anyone would conclude that hav­
ing either of these professionals frantically typing numbers on a keyboard is a viable solution. At the very 
least, the passengers on the plane and the desperately ill patient in the bed and their loved ones would 
want the person in whose hands their well-being rests to be able to focus on the important priorities. 
When the nurse admits a new patient, required documentation includes completing a number of

When the nurse admits a new patient, required documentation includes completing a number of 
screening tools and risk assessments. This includes evaluating the patient’s risk of developing a pressure 
ulcer or of falling. These assessments are performed when the patient is first admitted and will then be 
repeated every shift for critically ill patients. Additionally, there needs to be documentation that complies 
with regulatory bundles for a select group of target conditions, including acute coronary syndrome (ACS), 
stroke bundle, sepsis bundle, heart failure, and venous thromboembolism (VTE) prevention bundle. 
The nursing assessment is a physical examination of a patient and includes all body systems. Many 
nurses organize their assessment as a head-to-toe approach. A complete assessment will be performed 
by the nurse when the patient is first admitted and again at the beginning of every shift. Depending on

by the nurse when the patient is first admitted and again at the beginning of every shift. Depending on 
the stability of the patient and whether the patient is in a critical care unit or a medical-surgical unit, 
this assessment may be repeated every 4 or 6 hours. 
Information entered by nurses into the record contributes to determining whether the evidence-
based core measures have been met for patients with stroke, ACS, certain orthopedic procedures, and 
heart failure. The assessments also include completing standardized tools to determine the patient’s risk 
of developing certain HACs. The Hendricks Tool looks at the patient’s risk of falling—and the Braden 
Scale evaluates the patient’s risk of developing a pressure ulcer. 
N u r s i n g  d o c u m e n t a t i o n  i s  d i ff e r e n t  f r o m  t h a t  o f  o t h e r  d i s c i p l i n e s  i n  t h a t  i t  i s  b o t h  e p i s o d i c  a n d

dynamic. Similar to physicians and other health professionals, nurses perform initial assessments at the 
beginning of a shift according to systems. This is an example of where the documentation is episodic in 
that the nurse will complete the assessment and then record the results. The bigger challenge that nurses 
face in the critical care setting is the need to record vital signs at a very high frequency on a regular 
basis as well as intermittently whenever there is a change in the patient’s status. Most critical care units 
traditionally had a paper flow sheet of some design. While the actual design would vary from hospital 
to hospital, there was a consistent similarity. Many hospitals had columns across the top with spaces 
labeled for the various parameters that were routinely documented as well as blank spaces that can be 
labeled with specific information that needed to be recorded for a specific patient. 
10.4.7 Computer-Based Documentation

10.4.7 Computer-Based Documentation 
All documentation is moving inevitably toward an electronic version, which is a positive evolution. 
However, the objective needs to design an EHR that is as easy to use and view as a paper-based flow 
sheet but that utilizes the full capability of a computer-based record. Many of the issues that need to 
be resolved with computer-based documentation are issues that are inherent to providing safe care to 
patients regardless of the type of medical record that is in use. These issues and problems were solved in 
a particular way when the technology only supported a paper record and the only way to communicate 
from one department to another was telephone, fax, or scanning. The problems have not changed but 
the options for solving them have changed dramatically with the advent of the EHR.

the options for solving them have changed dramatically with the advent of the EHR. 
The greatest challenge in improving the EHR lies in the area of data entry by the frontline profes­
sional. Utilizing the full capability of computer technology should result in data entry that is easier 
and faster and less stressful. However, technology, when used without auto entry of vital sign data, has 
increased the difficulty of documenting and increased the time spent in completing this task. In addi­
tion, the visual appearance of those data once entered needs to be easy to look at. There needs to be a 
priority placed on replicating the advantage that a flow sheet had in pulling all critical data together into

286 Biomedical Informatics 
a useable format. Decisions about patient therapy are made based on the results of these data and it is 
critical that both entry and retrieval are seamless. 
Another challenge to address is entering data in an emergency situation, such as a cardiac arrest or 
code. Even in facilities with auto entry of data into the computer from the monitor, all of the data that 
need to be documented in a code do not originate from the cardiac monitor. As part of the code process, 
emergency medications are given from the ER Cart, based on protocols of advanced cardiac life support 
(ACLS) or verbal orders. There will be other activities that occur, such as starting new IV lines. Some 
EHR systems have code programs available, some of which align with the American Heart Association 
ACLS protocols. However, other EHR systems do not and a facility needs to decide whether to have staff

ACLS protocols. However, other EHR systems do not and a facility needs to decide whether to have staff 
attempt to enter data electronically or to default to a paper-based code sheet. The subsequent decision 
then becomes whether to include the paper code sheet as a permanent part of the record or to consider it 
as an unofficial worksheet and to require the nurse to transfer the data from the code sheet into the EHR. 
The current status is mixed at present, but this is a huge opportunity to improve on the computer-based 
capability of keeping up when data entry is rapid and complex and must be accurately timed. 
Paper records always presented issues of legibility as well as omissions of recording the date and time 
with certain entries. On many occasions, hospitals have been cited by regulatory body surveyors for 
missing dates and times. Conversion to an electronic record instantly eliminates both of these issues

missing dates and times. Conversion to an electronic record instantly eliminates both of these issues 
because all notes are legible with the date and time is automatically entered by the computer. 
One of the current disadvantages of many EHRs is that they do not display the data in a visually 
friendly manner on the screen. It is sometimes necessary to scroll up or down or to click between screens 
to find the desired data. What the nurse needs to see is all assessment and labs in one location without 
having to scroll up or down too excessively or without having to click between screens (Figure 10.9a and b). 
(a) 
FIGURE  10.9 (a)  Vital signs as displayed in one version of an electronic health record. Although each entry 
is tagged by the computer with the exact time that it was entered, the data are displayed in a 1 hour window, for 
example, 10:00–10:59.  (Continued )

287 Critical Care Nursing Perspective on the Electronic Health Record 
(b) 
FIGURE  10.9 (Continued  ) (b) The visual appearance of displaying the physiologic data in the EHR is an impor­
tant factor in being able to quickly ascertain the patient’s status. Having to click between screens and scroll up or 
down to find information makes it difficult to correlate different parameters and events into the same timeframe. 
The goal is to create a user-friendly, functional EHR that employs the best features of a computer, 
while not losing the advantages that worked well with the paper record. It is important to look at the 
goals of the documentation and the requirements and not necessarily try to mimic the paper chart. 
However, a sometimes overlooked priority needs to be the ease of entering data by the frontline profes­
sionals as well as being able to easily look at that data during real time while the patient is hospitalized. 
10.5 Nursing Priorities for an Electronic Health Record

10.5 Nursing Priorities for an Electronic Health Record 
The concern of the critical care nurse, as the frontline user of the electronic medical record, is the ease of 
entering data as well as the ability to quickly retrieve the data so that it are useful for making decisions 
in real time about the patient’s status. Data entry needs to be easy, with the capability of immediate data 
viewing in a visually logical format. 
With a paper system, data entry was relatively easy. The nurse only had to glance up at the monitor 
and quickly write the numbers down on the flow sheet, which was typically organized in such a way that 
the spaces for the numbers followed consecutively in the same order as they appeared on the monitor. 
Performing the same activity, recording vital signs is very different when using a computer. Every entry 
has to be typed into the computer. It is often necessary to scroll to a different part of the screen while

has to be typed into the computer. It is often necessary to scroll to a different part of the screen while 
recording the numbers, because unlike paper, the entire form is not visible at the same time. It is often 
necessary to not only scroll but also click through different screens. The action of typing is different from 
the action of writing. Very few people have the ability to easily type numbers without looking at the key­
board. Finding the numbers on the keyboard requires greater attention than finding a space on a flow 
sheet and filling in a number. Since it takes more attention and effort to type in the numbers, it becomes 
necessary for the nurse to look away from the monitor for a longer period of time (Figure 10.10a and b). 
To again use the analogy of a pilot, requiring the nurse to document vital signs by typing every 
number would be the equivalent of requiring a pilot to not only fly the plane but record every setting on

number would be the equivalent of requiring a pilot to not only fly the plane but record every setting on 
every instrument, using a keyboard. This would never be acceptable, certainly not to those who are pas­
sengers on the plane. It should not be acceptable that a nurse who is taking care of a critically ill patient 
is required to type every vital sign, while at the same time continuously observing the patient and also 
providing nursing care.

288 Biomedical Informatics 
(a) 
(b) 
FIGURE  10.10  (a)  Data about the patient’s hemodynamic status are displayed on the cardiac monitor as wave­
forms with numeric values. (b) An electronic health record display of a patient’s hemodynamic parameters. 
The technology for effortless data entry exists. It is reasonable that hospitals, with a finite amount of 
funds to spend, felt some pressure to go live with the basic computer-based capability to meet the require­
ments of meaningful use. There was also a time constraint to accomplish this quickly in order to meet the 
deadlines. But going forward, auto entry of data from monitors and life-sustaining devices directly into 
the EHR needs to be a priority in the next round of decisions. In the long term, the hospital will benefit 
from this wise use of resources. The time that will be gained by the nurse not having to type copious 
amounts of data will help to pull the nurse away from the computer screen and back to the bedside. This

amounts of data will help to pull the nurse away from the computer screen and back to the bedside. This 
will undoubtedly benefit patients and their families, resulting in improved customer satisfaction scores.

289 Critical Care Nursing Perspective on the Electronic Health Record 
Research studies have supported that increased staffing ratios result in fewer HACs and in higher 
satisfaction scores. This translates directly into dollars of reimbursement for the hospital. Implications 
for future research include investigating whether the same benefit occurs when staffing ratios are virtu­
ally increased by decreasing the nonpatient care activities of the nurse by increasing the capability of 
computer documentation. 
10.5.1 Data Entry 
Data entry with a flow sheet involved picking up a pen and writing every single vital sign, assessment, 
or event that occurred with the patient. Recording by hand is a relatively fast and easy way to record 
information. In a critical situation when a patient is crashing and a great deal of information needs to 
be recorded quickly and at very frequent intervals, handwriting is easy. With a computer, data entry in

be recorded quickly and at very frequent intervals, handwriting is easy. With a computer, data entry in 
a critical care setting can be seamless if the data are automatically downloaded from all of the monitors 
and devices that are in use or it can be a nightmare if the nurse has to type every number of every vital 
sign and make sure that it is in the correct space and repeat this every hour at least and more frequently 
if the patient is unstable. To compare typing with writing, undoubtedly typing is faster if one is free­
texting information in a narrative form. However, if the data entry involves looking up at a monitor and 
then down at a computer keyboard for the numbers, writing is faster. Typing in dozens of numbers and 
scrolling to the next empty box take longer. And while the legibility issues that are present with writ­
ing are nonexistent with typing, the flipside is that typographical errors or typos can occur quite easily

ing are nonexistent with typing, the flipside is that typographical errors or typos can occur quite easily 
when trying to type on a keyboard. At best, the nurse realizes the error and has to spend extra time 
backspacing and reentering the numbers, and at worst, the typo will be undetected and the vital sign 
will be erroneous. 
When purchasing decisions are made about the type of EHR to install, hospitals have options as far 
as documentation packages for the critical care units in the facility. One option is to have the EHR as 
a freestanding entity devoid of any connection with the monitors and devices in the room. With this 
disconnected version, all data that are generated must be typed into the computer. The second and far 
better option is to ensure that the cardiac monitors in the rooms are able to communicate with whatever 
EHR system has been selected. This method proves far more accurate than handwriting and is faster and

EHR system has been selected. This method proves far more accurate than handwriting and is faster and 
includes more data points. A frequency is selected and the monitor sends data to the computer at those 
intervals. Any information that is needed immediately or stat can be sent by the nurse activating a but­
ton to send those data to the record in between scheduled downloads. The best systems also allow other 
equipment in use in the patient’s room to be sent to the monitoring system and then sent on to the com­
puter. Current technology for monitors, infusion pumps, and life-support devices almost universally 
supports being integrated with a variety of different EHR systems. The biggest barrier to implementing 
a fully integrated EHR system is usually cost. Some of the cost barrier is related to the pressure behind 
meeting meaningful use targets by the federally mandated deadlines. 
Reimbursement of millions of dollars is dependent on meeting these milestones and hospitals can­

not afford to lag behind. Other documentation-related reimbursement triggers include documentation 
by the nurse and physician on measures to prevent VTE, measures to prevent readmission of patients 
with a diagnosis of heart failure within 30 days of hospital discharge, documentation on the presence 
or absence of a pressure ulcer on admission, and the measures taken to prevent progression to a report­
able stage. Unfortunately, at present, there are no reimbursement bonuses that trigger on the nurse’s 
ease of documenting reams of vital signs. However, it should be considered that malpractice judgments 
for or against a hospital, costing millions in compensation, might well rest on the correct and timely 
documentation of vital signs to support the defense that the patient was being adequately monitored. In

documentation of vital signs to support the defense that the patient was being adequately monitored. In 
addition, it can also be argued that the time that the nurse does not have to spend in recording routine 
physiologic data can be better spent in providing direct care for the patient and family and documenting 
on the bundles that will directly result in reimbursement.

290 Biomedical Informatics 
There are challenges with the visual display of many computer-based systems in that due to the screen 
size and other demographic data that are continuously displayed typically on bands across the top or 
sides of the screen, the area of screen available to display the physiologic parameters is limited. The 
information that is available for viewing at any one time is only a portion of the total data entered. 
With some systems, moving between dates of service in the hospital is cumbersome, with only the most 
recent dates immediately available. It is necessary to enter other search parameters in order to find the 
desired date. Clicking between screens often causes a loss of continuity or train of thought as new data 
are displayed and trigger a response. Font size is important and must be adjustable. What we see affects 
what we think. 
There are some systems where the new orders that are written by the physician need to be viewed and

There are some systems where the new orders that are written by the physician need to be viewed and 
acknowledged by the nurse, prior to implementation. This is analogous to the actions that were previ­
ously required with a paper chart. The physician would write the order and sign it, but the nurse would 
need to review it and transcribe any medications or order lab tests and would then indicate that this had 
been completed by marking a line under the order and signing, dating, and timing when this was done. 
With the EHR, the nurse also needs to review the order and then electronically sign it before it is acti­
vated. However, instead of the order remaining together, as soon as the order has been signed off by the 
nurse, the individual components are reorganized into the categories where they belong. For example, 
lab tests that are ordered move to the lab test section of the orders and medications move to the medica­

tion section of the orders. In some ways, this is very logical because it keeps like information together. 
However, it can be confusing as well since the nurse cannot always see at a glance the most recent orders 
in their entirety. Task reminders usually display as a list, but it is not always accurate or up to date. 
The possibilities for wireless communication are interesting. One current example is the capability of 
smart infusion pumps. These pumps are preprogrammed with a library of medications and include infor­
mation about the usual concentration and dose. When the nurse initiates an infusion of a medication, 
he or she enters the name, concentration, and dose. The pump will confirm that the set parameters are 
within the normal dosing parameters of the particular medication. However, the pumps have the capa­

bility to be even smarter  than this. They are also designed to communicate with the EHR, which would 
enable them to download the data about the medication infusion directly into the EHR. At any time that 
the nurse changes the rate and dose of the medication, this information would also be entered directly 
into the EHR. However, the capability of many pumps goes even further, in that they can communicate 
with the pharmacy through bar coding. With this function operational, once the order has been entered 
into the EHR and communicated to the pharmacy for profiling, prior to administering the medication, 
the nurse scans the patient’s identification bracelet, the bag of medication, and then the particular infu­
sion pump. This will automatically enter the correct dose and rate into the pump, without the nurse enter­

ing those data, and the pump will then communicate with the EHR to download the information. When 
updates are available for the infusion pump library, it is not necessary to program each pump individu­
ally. Instead, this information can be transmitted wirelessly to all pumps in the facility. At present, there 
is varying utilization of the full capability of the smart pumps across different facilities (Figure 10.11). 
10.5.2 Reports 
The ability to run reports was not possible with a paper chart. Previously, with paper, data had to be 
obtained manually, by having an actual human being comb through the chart to find the desired infor­
mation. This was not only laborious, but it also often resulted in missed data items. 
With an electronic record, the number and types of reports that can be run are almost limitless in

With an electronic record, the number and types of reports that can be run are almost limitless in 
both scope and detail. For example, as new initiatives become active, such as the access to the Patient 
Portal, things that have to be documented to show meaningful use  and ensure that reimbursement is 
forthcoming can be easily assessed. Reports can be run to show whether the required documentation for 
required initiatives such as the Patient Portal, the VTE prevention bundle, or the heart failure core mea­
sures has been correctly documented. It is even possible to run reports on the documentation of specific

291 Critical Care Nursing Perspective on the Electronic Health Record 
FIGURE  10.11  (See color insert.) Smart  medication infusion pumps and cardiac monitors are capable of com­
municating directly with the electronic health record (EHR) to download the dose and rate. If this capability is not 
enabled by the system, the nurse is responsible for typing every number into the EHR, usually every hour. 
individuals as a form of performance appraisal. Reports can be run that reflect hospital performance as 
a whole or that reflect a specific unit or even the documentation performance of individual practitioners. 
10.5.3 Data Retrieval: We have Entered the Data but Where Did It Go? 
Once the information has been documented, the next challenge is how to quickly find the informa­
tion when it is needed. One advantage of computer-based technology is the ability to pull data that are 
entered in one screen to populate into another screen, if the same information is applicable to both.

entered in one screen to populate into another screen, if the same information is applicable to both. 
An exam p l e o f this is m edi ca ti o ns tha t ar e administer ed as co n tin uo us IV infusi o ns. The n urse will 
document the dose per minute or per hour and will also document the rate that it is infusing at in mL/h 
to deliver that dose. With most systems, when this is documented in the eMAR, the volume will auto­
matically populate into the intake/output section so that it will be included in the hourly volume totals, 
without the nurse having to manually enter it in that screen. This allows for the dose of the medication 
that is administered to be documented as a medication but also for the volume that it is diluted in and 
administered in to cross-populate into the area for documenting intake. 
One of the most promising aspects of the EHR is the ability to pull data from multiple patients’ charts

One of the most promising aspects of the EHR is the ability to pull data from multiple patients’ charts 
and assemble it into usable reports. This was not possible with a paper chart without exerting a tremen­
dous amount of effort. To accomplish what takes several keystrokes to complete with a computer-based 
system would have taken hours of human labor to pull this same information from the paper-based 
records. It was not feasible to do this with any regularity, and in general, this type of data collection from 
paper-based systems was usually conducted as part of a research project. With the EHR, it is possible 
to look at specific quality indicators to determine if the documentation of care being delivered meets 
the standards specified by the regulatory bodies. Beyond looking at data reflecting groups of patients, 
reports can be generated to look at a specific nurse’s documentation across time. Any quality indicator

reports can be generated to look at a specific nurse’s documentation across time. Any quality indicator 
can be looked at, for example, documenting according to bundles for pressure ulcer prevention or fall

292 Biomedical Informatics 
risk or whether the nurse has been correctly scanning medications and verifying patient identity with 
medication administration. 
Ordinarily, references to data retrieval refer to data that have been collected in the past and are 
retrieved at a later point in time. However, in the critical care setting, data retrieval also refers to the 
immediate need to review related vital sign and physiologic parameters together to detect trends and 
influence decisions about therapy. An effective EHR needs to be equally capable of recording data and 
retrieving it in real time as well as looking at trends for root cause analysis at a later point in time. 
For a specific patient, data retrieval will be used as a means of piecing together the results of tests and 
assessments in coming to a diagnosis. It can also be used to determine what happened in the event of an

assessments in coming to a diagnosis. It can also be used to determine what happened in the event of an 
incident. For groups of patients, data retrieval can be used to determine overall compliance with specific 
documentation requirements such as for the bundles or in meeting the requirements of regulatory agen­
cies. Computerized systems add an interesting possibility to data retrieval in that it is no longer neces­
sary to have direct access to a paper chart to glean information. Instead, patient data can be retrieved 
from a remote location. 
10.6 Literature Review 
Many of the research studies on computer-based documentation and EHRs are relatively recent, coin­
ciding with the increased adoption of this technology in response to government incentives. This is new 
area of study for nurse researchers as well as a lively topic for editorial commentaries in the journals. 
Several studies have looked at the issue of standardizing nursing terminology and data entries in order

Several studies have looked at the issue of standardizing nursing terminology and data entries in order 
to be able to include information documented by nurses in big data. Other studies have addressed the 
role that user acceptance of an EHR plays in the success of implementation. Several studies also looked 
at whether adopting an EHR would result in improved documentation of content that is required by 
regulatory agencies. 
“Big data” refers to a large complex data set that yields substantially more information when analyzed 
as compared to the information achieved with smaller sets of the same data that are not integrated. In 
the Online Journal of Nursing Informatics , Keenan (2014) made the point that little to none of the data 
that nurses currently enter into EHRs can be used in big data analysis, due to the fact that nursing data 
are not standardized and therefore not interoperable. Interoperable data contain data elements that

are not standardized and therefore not interoperable. Interoperable data contain data elements that 
are defined, measured, and retrievable in the exact same format. In contrast, EHRs across different 
organizations have been assembled and tailored to meet the unique needs of each organization. While 
there might be good reasons for this in terms of making an EHR work for a particular organization, it 
compromises the ability to compare data across organizations, which is necessary for big data. 
Englebright et al. (2013) also looked at the importance of standardization in order for nursing activi­
ties to be available for retrieval and inclusion in big data. They wrote that it is necessary that terminology 
needs to be standardized and to that end, they looked at developing a definition of basic nursing care 
for the hospitalized adult patient. They identified nine basic activities that were then incorporated into

for the hospitalized adult patient. They identified nine basic activities that were then incorporated into 
the EHR. Their conclusion was that this project represents a first step in capturing meaningful data ele­
ments that are specific to nursing. 
Keenan et al. (2012) tested the hypothesis that Hands-on Automated Nursing Data System, which 
provides a big picture summary , could be implemented uniformly across diverse settings and result in 
positive plan of care data outcomes across time. They concluded that it is possible to effectively stan­
dardize the capture and visualization of useful big picture healthcare information across diverse set­
tings. They identified that there is a lack of plan of care tools, based on standardized terminologies 
and processes, in today’s EHRs. They also stated that a review of eight of the best EHRs in the country 
showed that individual clinicians spend too much time sifting through raw data getting a true picture of

showed that individual clinicians spend too much time sifting through raw data getting a true picture of 
the patient’s situation. Their conclusion was that this sifting wastes clinicians’ cognitive resources and 
makes it difficult to see higher-order issues. Completing forms is a burden rather than a useful tool that 
will result in better patient care.

293 Critical Care Nursing Perspective on the Electronic Health Record 
Scherb  et al. (June 2013) have described what EHR meaningful use requirements mean for nursing 
clinical information system (CIS) development. They discussed that the CIS in many hospitals has a 
number of critical design inadequacies that constrain the meaningful use of nursing data to ensure 
quality outcomes for patients and data-based maturing of the nursing profession. They point out that to 
address this shortcoming, interoperable clinical nursing data must be documented in a properly inte­
grated and operational CIS and must be retrievable and stored in data repositories for analysis and 
reports. In their opinion, an unintended consequence of the rush to develop, market, and adopt software 
and CISs that are compliant with meaningful use requirements may actually obstruct the development 
or refinement of a fully integrated and effective hospital CIS, resulting in less effective systems. The focus

or refinement of a fully integrated and effective hospital CIS, resulting in less effective systems. The focus 
on meaningful use underscores that improved healthcare is more than just adopting technology . It is 
also the adoption of technology for use and sharing of information to support quality clinical decisions 
and outcomes. In the absence of standardized nursing nomenclature, nursing data that are important 
for the evaluation of quality and effectiveness will be precluded from analysis by local clinicians and 
administrators and from inclusion in large national EHR data sets. They conclude by observing that 
nurses document the implementation of physician orders, actions for which there is a charge to the 
consumer, and other externally mandated data, while limiting and compromising the documentation 
of nursing care data. In many settings, nursing electronic documentation does not represent the knowl­
edge-based nursing care that contributes to the quality of healthcare.

edge-based nursing care that contributes to the quality of healthcare. 
A survey was conducted by Estrada and Dunn (2012) to obtain feedback from registered nurses as 
end users of standardized nursing terminology for care planning in an EHR. Revisions to the care plan 
terminology were completed as part of an evidence-based project by nurses at one facility. The premise 
is that the plan of care in the electronic record is expected to offer nurses the ability to communicate 
the needs of the patient and assess outcomes of care. However, the survey findings indicated weaknesses 
warranting further exploration to identify changes needed to improve care planning documentation. 
In a study published in 2013, Hamad and Cline explored acceptance factors and barriers associated 
with providers’ intentions to adopt EHRs by provider type. Perceived management support, provider 
involvement, and adequate training were identified by participants as being acceptance facilitators.

involvement, and adequate training were identified by participants as being acceptance facilitators. 
Perceived lack of usefulness and provider autonomy were seen as barriers. 
In a study published in 2014, Don O’Mahony et al. explored South African nurses’ knowledge, atti­
tudes, and perceptions regarding information and communication technology (ICT) to inform the 
fu tur e  im p l e m e n ta ti o n  o f  e l e ctr o ni c  m e di cal  r e c o r d  sys t e m s.  Th e ir  p r e mis e  w as  th a t  in di vi d ual  us e r 
acceptance is a crucial factor in successful ICT implementation. In this study, the nurses identified many 
challenges with the current recording methods; however, they were supportive of installing an EMR in 
the community health setting. They concluded that the nurses’ knowledge about EMR, positive attitudes 
to ICT, and personal use of ICT devices increase the likelihood of successful EMR implementation.

to ICT, and personal use of ICT devices increase the likelihood of successful EMR implementation. 
Documenting specific aspects of care, especially relating to mandates from regulatory agencies or to 
reimbursement issues, such as CMS list of never events , has always been a challenge with paper docu­
mentation. Li and Korniewicz (2013) tracked the EHR documentation of pressure ulcers on a medical-
surgical unit and compared it to the written medical record. They found that documentation of pressure 
ulcers was incomplete or inaccurate in both the EHR and the written record. They concluded that the 
actual use of an EHR was more important for improving quality than its presence alone and that adopt­
ing an EHR without determining the correct use of it is insufficient to improve quality. 
In a 2011 letter to the editor, published in Critical Care Nurse, Patricia Kelly commented on whether

In a 2011 letter to the editor, published in Critical Care Nurse, Patricia Kelly commented on whether 
the EHR could foster better documentation of family history as an inexpensive and often underutilized 
genetic tool. With paper documentation, this was identified as being a long-standing problem and the hope 
was that the EHR would facilitate assessment and documentation. However, her observation was that for 
many health systems, this has not been a reality and that many EHR systems actually interfere with assess­
ments. Her recommendation was that there should be red flags to cue important aspects of documentation. 
Fowler et al. (2014) created two tools to achieve the goals of providing physicians with a way to 
review alternative diagnoses and improve access to relevant evidence-based library resources without

294 Biomedical Informatics 
disrupting established workflows. One of the tools lifted terms from standard, coded fields in the EHR 
and then produced a list of possible diagnoses. The physicians chose their diagnosis and were then pre­
sented with the “knowledge page,” which is a collection of evidence-based library resources, which was 
automatically populated with search results based on the chosen diagnosis. In this study, the physicians 
responded positively to having access to the knowledge page. 
The details of operating within an EHR were raised in the June 2011 issue of Critical Care Nurse, where 
Harrington and associates posed the question of attributing authorship of EHR data by persons other 
than the actual individual providing the care. This question addresses whether documentation is the 
sole responsibility of the person who provided the care or whether attestation is an acceptable solution 
to clinical situations where direct authorship is not possible.

to clinical situations where direct authorship is not possible. 
Pasek et al. (2009) utilized the EHR at Children’s Hospital of Pittsburgh to address the challenge of 
describing the role of the advanced practice nurses (APNs), in particular, the clinical nurse specialists 
(CNSs) in the hospital setting. They identified that evidence is necessary to support the value of the 
APN and the sustainability of the role and that documentation in the medical record is an important 
way to capture their contribution to patient care. They also identified that in their institution, virtually 
all disciplines had a designated space in the EHR except the APNs. They utilized the technology of the 
EHR to address this gap. 
In the July 1, 2011, “Crucial Conversations about Optimal Design” column of the Online Journal of 
Nursing Informatics , Nancy Staggers discussed the details of the April 2011 hearing concerning the

Nursing Informatics , Nancy Staggers discussed the details of the April 2011 hearing concerning the 
usability of EHRs. Nurses generally view EHRs as superior to paper-based systems but consider usabil­
ity a significant challenge. For example, finding pertinent data in the sea of available electronic informa­
tion can be a challenge. The questions that clinicians need to be able to answer include the following:
 1. What has changed on this patient over the last 2, 4, 8, 12, 24, or 48 hours?
 2. Are these patients’ vital signs/lab values trending up or down over time?
 3. How has the change in medication affected the patient’s blood pressure or pain scale rating?
 4. What is the set of combined social, financial, and functional status information that will impact the 
decision to place a patient into an independent living versus a skilled nursing facility? 
The authors noted that users currently have to flip through screen after screen to find data of interest.

The authors noted that users currently have to flip through screen after screen to find data of interest. 
Nurses are patient advocates coordinating care activities across the team of providers, but data for this 
coordination are often assembled via memory or on paper or contained in a separate note within a set of 
hundreds of other documentation entries in an EHR. This process is not only time consuming but it is 
also highly prone to error. An interesting quote that the author attributed to a clinician referred to this 
process as “death by keystroke.” 
Fleming et al. (February 2014) looked at a commercially available ambulatory EHR’s impact on work­
flow and financial measures. They concluded that expenses increased and productivity decreased fol­
lowing EHR implementation, but it was not as much or as persistently as they had expected. Staffing and 
practice expenses increased following the EHR implementation. Productivity, volume, and net income

practice expenses increased following the EHR implementation. Productivity, volume, and net income 
decreased initially but recovered to close to preimplementation levels after 12 months. They recommend 
that longer-term effects still need to be examined. 
An interesting study by Penoyer et al. (2014) examined what information is used by clinicians, how this 
information is used for patient care, and the amount of time clinicians perceive they review and docu­
ment information in the EHR. A survey administered at a large, multisite healthcare system was used to 
gather this information. Findings showed that diagnostic results and physician documents are viewed 
more often than documentation by nurses and ancillary caregivers. Most clinicians use the information 
in the EHR to understand the patient’s overall condition, make clinical decisions, and communicate with 
other caregivers. The majority of respondents reported they spend 1 to 2 hours per day reviewing infor­

mation and 2 to 4 hours documenting in the EHR. In contrast to this, bedside nurses spend 4 hours per 
day documenting, with much of this time spent completing detailed forms seldom viewed by others. The 
aim of this study was to determine what information from the EHR is viewed and how that information

295 Critical Care Nursing Perspective on the Electronic Health Record 
is used by different types of clinicians. They concluded that it is essential to engage clinical practitioners 
with the designers of these documents to meet clinicians’ need as consumers. Creating views of data that 
are concise, relevant, and meaningful for clinicians may augment their ability to make clinical decisions. 
As facilities scramble to demonstrate that they are meeting the key components of meaningful use, 
an  arti cl e  b y  Galb rai th  ( 20 13 )  q u esti o n ed  th e  im po rtan ce  o f  wha t  co nsti tu tes  m eaningful  use.  As  an 
example, he cited the Patient Portal, which is intended to increase patients’ participation in their own 
care. One core objective of stage 1 meaningful use involves healthcare providers being able to “provide 
patients with an electronic copy of their health information.” But he points out that this doesn’t take into

patients with an electronic copy of their health information.” But he points out that this doesn’t take into 
account the digital divide between those with and without internet access. The same people caught in 
this digital divide are the same ones most likely to suffer from limited healthcare access and poor health 
outcomes. Thus, those populations who would benefit most from learning more about their health are 
also least likely to have access to that information, at least through the electronic format. 
In the “Research with Information Technology” column in the Online Journal of Nursing Informatics, 
Topaz and Bowles (February, 2012) reviewed the mandate that by the end of 2015, healthcare providers 
across the United States are expected to prove they are meaningful users of certified EHR technology 
in ways that can be significantly measured in quality and in quantity or else they would be financially

in ways that can be significantly measured in quality and in quantity or else they would be financially 
penalized when providing services for Medicare and Medicaid clients. This mandate is based on the 
assumption that EHRs will improve caregivers’ decisions and patient outcomes. The editorial reviewed 
some of the shortcomings in the emerging body of research evaluating the impact of EHRs on the qual­
ity of ambulatory care. 
Silver and Straub (January, 2014) in Contemporary OB/GYN  state that it is time to insist that elec­
tronic medical records are assiduously created and carefully maintained so that they are more than just 
expensive versions of their paper ancestors. They suggest that caregivers need to conceptualize data 
entered on behalf of patients as of the highest value to their current and future health status, making 
accurate completion of the EHR an act of professionalism.

accurate completion of the EHR an act of professionalism. 
In an editorial in the November 2013 issue of the American Journal of Critical Care,  Richard H. Savel 
and Cindy L. Munro commented on the “Promise and Pitfalls of the Electronic Health Record.” They 
commented that many of the problems facing bedside critical care practitioners who worked with EHRs 
in the mid-1990s remain largely unchanged today. Their conclusion is that interfaces between systems 
should be enhanced to decrease the amount of data bedside nurses need to enter into the computer. 
Bedside monitors should interface directly with EHRs and smart pumps should enter data in a similar 
fashion allowing bedside nurses to do what they do best: provide care to patients. Finally, they make the 
salient observation that systems whose poor design and flaws are obvious to the bedside nurse may seem 
to work perfectly from the perspective of hospital leaders. 
10.7 Implications for Future Research

10.7 Implications for Future Research 
Based on the results of current research studies as well as information about challenges that have been 
observed in the various types of EHRs, several topics seem to lend themselves to requiring further study. 
From a critical care perspective, the question of optimum methods of data entry, particularly in 
situations of patient instability, is of paramount importance. The technology exists to allow for many 
devices to communicate with the EHR and download data directly into the record. However, since this 
is a relatively expensive addition to the computer-based system, ease of data entry is often not one of 
the most obvious priorities to hospital administrators. Therefore, research is needed to determine the 
impact that data entry options have on other aspects of patient care, especially those that have a positive

impact that data entry options have on other aspects of patient care, especially those that have a positive 
financial benefit, such as patient satisfaction scores and documentation that reflects compliance with 
regulatory standards. 
Studies looking at data entry options could also tie into the existing research that has demon­
strated that documentation relating to content required by regulatory bodies for reimbursement, such 
as pressure ulcer prevention, has not shown the compliance that was originally expected with EHR

296 Biomedical Informatics 
implementation. There have always been issues with this documentation on paper , but it was hoped 
that adherence to the standards would improve with an electronic system of documentation. However, 
it would be intriguing to look at whether the poor performance in documenting on the standards was 
related to the style of data entry for vital signs and other physiologic parameters. It would be interest­
ing to see if there is any correlation between manual data entry via keyboard versus auto data entry on 
the compliance with other aspects of documentation. This would then tie back to looking again at ease 
of data entry as being a crucial component for all other potentially advantageous pieces of electronic 
documentation to fall into place. 
An informal observation that has been made in many institutions after they have gone live with their 
electronic documentation system is that the nurses are suddenly spending less time interacting directly

electronic documentation system is that the nurses are suddenly spending less time interacting directly 
with their patients and more time staring at the computer screen. The contention is that the computer 
demands more attention than was necessary with paper-based documentation. It has been stated that 
the nurse is more likely to continue looking at the screen or the keyboard while talking to the patient 
as opposed to maintaining eye contact and just glancing briefly at the paper record to make the entry. 
Anecdotally, many nurses have commented on the fact that they feel that the computer pulls them away 
from their patients. There is an opportunity here for research studies to determine whether this is actu­
ally the case or just a perception. Based on the results, follow-up studies would be indicated to look at the 
specific barriers and evaluate which methods are the most effective in addressing these issues.

specific barriers and evaluate which methods are the most effective in addressing these issues. 
Research studies on nurse–patient ratios have demonstrated that increased staffing ratios result in 
fewer HACs such as infections or falls and in higher satisfaction scores, all of which translates directly 
into dollars of reimbursement for the facility. An interesting topic to investigate is whether the same 
benefit occurs when staffing ratios are virtually increased by reducing the nonpatient care–related activ­
ities of the nurse. This would also include looking at strategies that improve the user interface capabili­
ties of the EHR to make the data entry easier and less time consuming for the nurse. 
As the technology advances and improvements are made in the design of the EHRs, attention needs 
to be paid to the appearance of the screens and the different ways that data can be displayed. Research is

to be paid to the appearance of the screens and the different ways that data can be displayed. Research is 
needed to determine the best visual cues for observing and processing information. This research could 
correlate the way that the brain processes information with the optimum appearance of the computer 
screen 
10.8 Electronic Documentation: The Good, 
the Bad, and the Potential 
Going forward, the potential for computer-based documentation and a truly electronic system are 
virtually limitless. Creative thinking and an understanding of patient needs and the workflow of the 
healthcare system can create an EHR that fully uses all of the capabilities that a computer can offer. 
In much the same way that the use of paper and pen for critical care documentation evolved through 
many different iterations, from the earliest versions on unstructured loose-leaf-type paper to a flow 
sheet with choices and an incorporated assessment, computer-based documentation is also evolving.

sheet with choices and an incorporated assessment, computer-based documentation is also evolving. 
The systems that will be in use 10 years from now will probably look very different from the current sys­
tems that are in use today. To use an analogy that relates the current state of electronic documentation 
to the evolution of phone technology, we have definitely moved beyond the era of a rotary dial telephone 
but are at best at the level of a flip phone with a built-in camera. At the very least, we should be able to 
anticipate that something as critically important as an EHR will be able to achieve the same level of user-
friendly technology as a Smart phone. 
In creating a wish list for the ideal EHR, the main objective would be to ensure that computer-based 
technology is utilized to the fullest extent of its capability, so that the EHR can be integrated seamlessly 
into patient care activities in such a way that it is not a barrier to providing care but, instead, facilitates

into patient care activities in such a way that it is not a barrier to providing care but, instead, facilitates 
and enhances this process. The move to the next version of the EHR should emulate the change that

297 Critical Care Nursing Perspective on the Electronic Health Record 
occurred when nurses first stopped documenting on loose-leaf paper and moved to a flow sheet that 
efficiently allowed them to document vital signs and assessments in one place and combined the best 
features of ease of data entry with meaningful display of data. 
The current state of computer-based documentation has been driven, in large measure, by the incen­
tive of obtaining funding for achieving a particular level of meaningful use  from the federal govern­
ment. The good news is that this has spurred many hospitals to implement a system of computerized 
documentation much sooner than they might otherwise have intended. The bad news is that many of 
the systems that have been implemented, while being successful at achieving meaningful use levels 
in the mandated areas, have been less developed and in fact have proven to be a barrier to delivery of

in the mandated areas, have been less developed and in fact have proven to be a barrier to delivery of 
patient care in other areas. Facilities have chosen different go-live options with implementing their EHR 
systems. Some hospitals went live with the entire facility at the same time, while others introduced the 
EHR, department by department. Some hospitals chose the most sophisticated system that would be 
able to do everything  including communication between monitors, physiologic devices, and the EHR 
for automatic downloading of data, while others began only with the bare bones. Some facilities chose 
commercial products, while others chose to implement their own version. Based on an observation 
of how other cutting-edge industries evolved, it might be expected that over the next few years, there 
might be mergers and takeovers with the major computer-based technology providers so that there will

might be mergers and takeovers with the major computer-based technology providers so that there will 
emerge only two or three major providers. The advantage of this, overlooking the financial disarray of 
the companies that will be acquired or taken over, is that it should enhance the ability of EHRs in differ­
ent settings to communicate more seamlessly with each other than is currently the case. 
The wish list for the ideal EHR is long. But it is hard to miss the observation that other industries have 
applied computer-based technology in present day use that are already far beyond the capability of many 
of the bare-bones EHR systems in place. For example, many supermarkets have bar-code scanners that 
customers can use to directly scan products while shopping. On entering the store, the customer scans 
his or her loyalty card that is then matched to a particular scanner. While shopping, the customer

his or her loyalty card that is then matched to a particular scanner. While shopping, the customer 
scans each product selected and places it directly in the shopping bag in the cart. When the customer has 
finished shopping, he or she goes to one of several self-checkout registers and scans a bar code over the 
register screen and his or her customer card. The order items are displayed on the screen for review and 
the customer can pay by any means desired: cash, credit, or debit. There is no need to take the items out 
of the cart, place them on the belt, and then bag the order, because this has already been done while shop­
ping. Meanwhile, the store knows exactly which items were purchased and need to be replenished on the 
shelves. Undoubtedly , many nurses would appreciate it if the bar-coding system implemented in many 
hospitals for medication administration worked as well as the system in place for buying baked beans.

hospitals for medication administration worked as well as the system in place for buying baked beans. 
An interesting conflict exists between the desire and need to customize an EHR to the needs of a par­
ticular facility and the need for at least some degree of standardization so that data can be retrieved. This 
was a theme of several research studies that concluded that some of the issues with nursing documenta­
tion not being available for inclusion into big data are based on the problem that much of the informa­
tion that nurses document does not use standardized terminology. On the other hand, many facilities 
also look at the EHR and insist that the data collected and the appearance be customized to meet the 
needs of that particular facility. Going forward, however, it might be suspected that large-scale col­
laboration, as well as multisite research studies to identify the ideal components of the EHR, would be

laboration, as well as multisite research studies to identify the ideal components of the EHR, would be 
indicated to address this issue. And if, as expected, the commercial providers of EHR systems will begin 
to merge at some point, it would be a step in the direction of promoting some degree of standardization. 
The information that is documented in the EHR can be viewed as constituting raw data. This includes 
items such as vital signs, assessment results, and narrative descriptions that the nurse enters into a free-
text nursing progress note. The computer needs to be able to organize raw data more effectively so that 
meaningful reports and compilations of aggregate data can be obtained. It needs to not only be able to 
search for items that have been documented in the expected location using standardized terminology 
but also be able to search the entire record for key words and phrases. No areas of the electronic record 
should be unavailable for retrieval.

298 Biomedical Informatics 
If everything on the wish list  were ranked in order of importance, most critical care nurses would 
probably request that any feature that makes the EHR easier to use, so that the nurse is able to spend 
more time doing actual nursing care for patients, would be at the top of the list. To that end, the request 
for the EHR to communicate with all of the devices that have been designed to do so would be a prior­
ity. Not only does this feature decrease the workload and the frustration level of the nurse, but it also 
increases patient safety—smart pumps for medications, bar coding for medications, and blood products 
all decrease the potential for errors by adding an extra layer of patient identification and dose verifica­
tion. Some facilities incorporated the device–EHR communication feature from the very beginning, 
while other systems did not. The result is that for critical care nurses practicing without the capability of

while other systems did not. The result is that for critical care nurses practicing without the capability of 
auto entry of vital sign data, the task of entering vital signs is accomplished by typing numbers into the 
EHR. This is a particularly onerous process in critical care simply because of the volume and frequency 
o f  da ta  th a t  n eeds  t o  be  e n t e r ed.  Th e  b ur d e n  o f  this  cann o t  be  o v e r e m p h as ized.  H o w ev e r ,  r eco gniz ­
ing the challenges that currently exist, yet ceding to the temptation to truly look at the possibilities of 
computer-based technology, most critical care nurses would assume that when the dust settles, device/ 
EHR communication will be a basic minimum level of performance for any computer-based system. 
And to push the envelope a little further, it would not be surprising if critical care nurses choose to move 
beyond monitor–device–EHR synchronicity and suggest that voice recognition would not be a bad next

beyond monitor–device–EHR synchronicity and suggest that voice recognition would not be a bad next 
step. Based on the impact that meaningful use financial incentives have had on the rapid adoption of 
computer-based documentation, perhaps the next step would be to choose data entry or issues relating 
to ease of use as the next target for meaningful use incentives. 
Assuming that we will get to a point where data entry in a critical care unit is no longer an issue in 
that all monitors and life-support devices will communicate directly with the EHR, the next important 
item on the wish list would be related to the manner of displaying the data that have been entered. 
To touch back on a paper flow sheet for a moment, the advantage was that it was a very efficient tool 
for easy entry of data as well as for viewing that data in a logical, easy-to-view format. Currently, with 
many EHRs, most of the vital sign data are difficult to look at, no matter how it was entered: whether by

many EHRs, most of the vital sign data are difficult to look at, no matter how it was entered: whether by 
laborious typing by an irritated critical care nurse or via reasonably effortless entry directly from the 
monitor and devices in the room. All of this translates into the next objective, that is, the EHR should 
provide a view of all critically important data, including vital signs, hemodynamic parameters, critical 
lab values, medications delivered via continuous IV infusion, important events that have occurred lab 
values, medications delivered via continuous IV infusion, and important events that have occurred and 
are easy to look at and interpret. Data should be grouped with time synchronicity so that data pertaining 
to the same time period are displayed together. 
A feature that computers are particularly adept at accomplishing is the ability to track required tasks 
that need to be completed and to identify those that have not been completed by the target deadline.

that need to be completed and to identify those that have not been completed by the target deadline. 
Many EHRs have this feature already, but it is not always as well developed as it could be. The tasks that 
are displayed are not always accurate or useful and they do not always disappear when the activity has 
been co m p leted. So metimes, the same task is listed m ul ti p le times. In addi tio n, not all activi ties are 
included in the task list. Therefore, added to the wish list would be the requirement that an accurate and 
useful task list needs to be incorporated into the EHR. This would be a task list that contains appropriate 
activities that are important and meaningful to the nurse and that disappears appropriately when the 
task has been completed. 
During the era of paper-based documentation, there were additional forms that would be used for 
high-acuity situations, with one example being the code sheets that were used during emergencies, such

high-acuity situations, with one example being the code sheets that were used during emergencies, such 
as a cardiac arrest. With computer-based systems, documenting in these situations remains a challenge 
even with data auto entry systems. For some facilities, the decision is to convert to the original paper 
form during a code. Looking toward the future goal of having all documentation easily and appro­
priately entered into the EHR, it would be interesting to apply creative problem-solving strategies to 
address this issue. With current technology, there are defibrillators already on the market that will give 
voice prompts about the quality of cardiac compressions during a code, by interpreting data collected

299 Critical Care Nursing Perspective on the Electronic Health Record 
from the chest electrodes to sense chest movement of the patient during compressions. The defibrillator 
is able to instruct the rescuer to compress deeper or faster. Perhaps the EHR of the future could be trig­
gered into a code mode and present a touch screen view similar to the original code sheets. The format 
could be modeled on the Basic Life Support and ACLS algorithms of the American Heart Association. 
Similar to designing a code screen for a cardiac arrest, other scenarios could also have a specific 
screen designed for the data that are typically collected in such a situation. Examples of these types of 
scenarios could include an emergency department admission of a trauma patient, a burn unit admis­
sion of a critically burned patient, or an intensive care unit admission of a patient directly from the OR 
following customarily open heart surgery. By triggering an icon, the EHR would immediately present

following customarily open heart surgery. By triggering an icon, the EHR would immediately present 
the screens for documenting these data. Data that could be automatically downloaded would begin to 
do so at the desired preset time interval. Assessments that need to be entered by the nurse would appear 
as a list of tasks visible on the side of the screen. Medications that are customarily administered would 
appear in a special location on the task bar so that the nurse would be reminded to go to the eMAR to 
see which medications were due or to document medications that had been given stat . 
Improving communication between geographically separated care settings should be another pri­
ority. There should be a smooth transfer of information between the hospital, the physician or APN’s 
office, the rehabilitation or long-term acute care centers, and home care services. The movement of a

office, the rehabilitation or long-term acute care centers, and home care services. The movement of a 
patient between the different settings should be seamless with the flow of information going easily from 
one location to another. Care should be taken so that the information is clearly delineated according to 
the setting where it is applicable, including separating different hospital admissions so that the informa­
tion provided does not become overwhelming or confusing as to what is a current problem and what 
might have occurred and been treated and resolved on a previous hospital stay. However, in contrast, 
there should be a crossover feature that would allow any new information that is entered into the EHR, 
pertaining to the current hospital stay to trigger anything that is related in any of the communicating 
records from any other setting. This feature would address the issue of medication reconciliation, the

records from any other setting. This feature would address the issue of medication reconciliation, the 
challenge of keeping track of the medications that the patient was taking at home when being admitted 
to the hospital. Current practice is that the information on the medications that the patient is taking at 
home comes directly from the patient or family member when the patient is admitted to the hospital. 
It would be an added safety feature if this information could come directly from the EHR in the physi­
cian’s office communicating with the EHR in the hospital. 
The results of several studies support collaboration between designers and clinicians as being essen­
tial to creating the best EHR. But the best method to accomplish this goal has not been described. The 
question is raised as to whether discussion alone can accomplish this collaboration or whether more in-
depth knowledge on the part of each discipline is required. Does there need to be more focus on nurses

depth knowledge on the part of each discipline is required. Does there need to be more focus on nurses 
gaining a background in informatics and computer design so that they can communic ate more clearly 
in the language that the coders will understand exactly what their priorities are, with a full understand­
ing of what the capabilities of the hardware and software are and what it would take to take to program 
the desired options? Or should it be a requirement that anyone who will be involved in the design of an 
EHR in the application for hospital-based nursing practice or critical care nursing should spend time in 
an intensive care unit observing critical care nurses? 
10.9 Critical Care Unit in 2025 
If we fast forward to the year 2025 and take a look at the admission of an unstable, critically ill patient 
who has just undergone open heart surgery, it will be interesting to see how that scenario might unfold

who has just undergone open heart surgery, it will be interesting to see how that scenario might unfold 
if all of the items on the wish list for the ideal EHR have been implemented. 
The room in the cardiothoracic intensive care unit (CTICU) is ready for the patient who has already 
been placed on the bed in the OR. The patient will be transported to the unit by several members of the 
OR team, including the anesthesiologist, the nurse, the technician, and the surgeon. The CTICU nurse, 
who will be his primary nurse, received a report on the patient’s status and the surgical procedure via

300 Biomedical Informatics 
her smart tablet, as well as a verbal confirmation from the OR nurse several minutes prior to the patient’s 
arrival. In the room, all of the equipment that will be needed when the patient arrives is in place includ­
ing the ventilator, the monitor for displaying his cardiac rhythm and pressure waves and pulse oximetry, 
SVO2, CO, and CI and core temperature. The portable computer is also in the room, and as the bed is 
being wheeled into the room by the OR team, the nurse scans the patient’s ID bracelet, which activates 
the patient’s EHR. He or she also scans his or her ID badge bar code, to indicate that he or she will be 
documenting on the patient and that the entries into the record are no longer taking place in the OR. 
The nurse’s ID badge is matched to the CTICU and this will also trigger the time that the patient has 
arrived in the unit. The nurse also quickly scans the bar code on the ventilator and the monitor which

arrived in the unit. The nurse also quickly scans the bar code on the ventilator and the monitor which 
will match them to the patient’s EHR for wireless downloading of data. 
In transit from the OR to the CTICU, the patient’s ECG rhythm and arterial blood pressure were 
monitored via a transport monitor, which stored these data until the patient arrived in the unit and was 
in the proximity of the computer to transmit the data wirelessly for inclusion in the record as the final 
vital signs from the OR team. Once the patient’s bed is in the room, the primary nurse begins to change 
the patient’s ECG cable over from the transport monitor to the monitor in the room. When he or she 
has finished transferring all of the data cables to the monitor, the display will include a waveform of the 
ECG and a digital readout of the heart rate, an arterial waveform with a digital readout of the systolic

ECG and a digital readout of the heart rate, an arterial waveform with a digital readout of the systolic 
pressure/diastolic pressure/MAP, a pulmonary artery waveform with a digital readout of the systolic 
pressure/diastolic pressure/mean PAPs, an SVO2, a CO, a CI, and a core temperature. 
The nurse will also assess all aspects of the patient’s status, utilizing a head-to-toe, system-by-system 
process. To enter these data into the EHR, the nurse has two choices. He or she can utilize the smart 
tablet where each system is displayed as part of a task list. Touching the system name will open a window 
with choices. The nurse will document the results of his or her assessment by touching as many of the 
descriptors that apply. He or she also has the ability to free-text if there is any information that he or she 
wants to add that does not fit into any of the available choices. 
The other option for entering these data is to use the voice-recognition feature. There is a tiny, yet sen­

sitive microphone embedded in the ID badge, with an icon that the nurse will touch to activate. As the 
nurse completes the assessment, he or she can simply speak the results aloud and it will be entered into 
the EHR. If he or she needs to begin another conversation, he or she can deactivate the microphone 
by again touching the icon. The microphone, while sensitive so that the nurse does not have to speak 
loudly, also has a very limited range, so as not to pick up room conversations. However, to also address 
this, as soon as the nurse is finished with his or her entry, he or she can quickly review the content for 
any extraneous items that were picked up but should not be included in the record. These can be deleted 
before being added as part of the permanent record. 
The patient is also receiving four medications via continuous IV infusion. To document these

The patient is also receiving four medications via continuous IV infusion. To document these 
medications in the EHR, the nurse scans the patient’s ID, the bags, and the pumps which not only 
matches all of them to the orders in the electronic record to ensure that the correct medications are 
infusing but also signals the same information to the pharmacy for profiling and refilling purposes. 
By scanning, all of the medications populate into the eMAR and are already documented as being 
administered by the CTICU nurse. Each hour, the infusion pump will update the EHR with the dose 
as well as the volume being administered. The volume infused will also populate into the intake and 
output section of the EHR to be included with all other fluid that the patient has received that hour. If 
the nurse changes the dose and hourly rate of a particular medication, the pump will send the updated

the nurse changes the dose and hourly rate of a particular medication, the pump will send the updated 
information to the EHR, so that it is documented at the time that it occurred. If the medication was 
changed because of a change in the patient’s vital signs, the nurse needs to only touch an icon on the 
screen and the full data set will be sent to the EHR. This will allow for all aspects of the patient’s sta­
tus to be available for review and will make it possible to correlate any medication changes with the 
patient’s physiological status at the time. 
An unexpected, but very welcome, benefit is that since implementing the fully integrated EHR with 
complete bar-code scanning of the medications as well as the infusion pumps, with direct download,

301 Critical Care Nursing Perspective on the Electronic Health Record 
there has not been a single medication error involving a continuous IV infusion. The hospital’s risk 
management department estimated that this has saved the hospital close to one million dollars, which 
justifies the initial financial investment that was required to implement this system. 
For the first hour after the patient’s arrival, the vital signs will be recorded every 15 min. The computer 
and the monitor have already been programmed with this frequency and will automatically download 
into the EHR at the specified interval. If the nurse notices something on the monitor that is unusual 
between these programmed downloads, he or she will touch an icon on the monitor screen and all data 
displayed at that moment will be downloaded. After an hour the monitor is programmed to decrease the 
downloading frequency to once every hour. The nurse confirms that the patient is stable enough for this

downloading frequency to once every hour. The nurse confirms that the patient is stable enough for this 
by again touching an icon on the screen to reset the downloading interval to every hour. If the patient 
had been unstable and the nurse wished to continue recording the vital signs more frequently, he or she 
would have selected this frequency when the initial hour was over. 
As the patient was being settled in the unit, there was a question about whether the patient was on 
medication for a thyroid condition prior to this hospitalization. It was not included in the admission 
assessment but one of the physicians thought that the patient might have been taking this medication 
at home. On the home screen of the EHR, there is an icon in the corner labeled, “Other Care Settings.” 
T o u c h in g  i t  o p e n e d  a  l i s t  th a t  in c l u d e d  o th e r  h o s p i t al  s t a y s  a s  w e ll  a s  th e  p h y s i c i an ’ s  o ffi c e  r e c o r d s .

Entering that portal and navigating to the section detailing the medication that had been prescribed for 
the patient, it was easily determined that the patient was in fact receiving thyroid replacement medica­
tion at home. This medication was then added to the medications that he or she would be receiving in 
the hospital. The entire process to obtain this information about the medications that he or she was on 
at home took a little less than 2 minutes. 
Once the patient is settled, the nurse invites the patient’s husband or wife and son or daughter to 
come and visit. This is the first time that they will be seeing the patient during the postoperative period 
and they are understandably anxious. The nurse is still completing the system assessment of his or her 
patient, but he or she is able to sit with the patient’s family at the bedside to reassure them and explain 
what is happening. Since he or she is speaking with the family, he or she is using the smart tablet on

what is happening. Since he or she is speaking with the family, he or she is using the smart tablet on 
his or her lap, rather than the voice recognition. Data entry is easy and the use of the tablet allows for 
more eye contact and a comfortable interaction with the family. The nurse was easily able to enter the 
data while still glancing at the monitor to view the patient’s vital signs, as well as interacting with the 
family members. During the time that he or she was speaking with the family, the patient’s vital signs 
were being entered automatically into the EHR every 15 min. The nurse was continuously watching the 
monitor to ensure that the vital signs were stable, but he or she did not have to record any of the infor­
mation. Prior to the hospital’s addition of the system for the monitor and other devices to communicate 
directly with the EHR, the nurse would have been typing all of the numbers displayed on the screen

directly with the EHR, the nurse would have been typing all of the numbers displayed on the screen 
every 15 min, making a calm conversation with his or her patient’s family virtually impossible. With the 
new system in place, the hospital has also seen HCAAPS scores rise dramatically, which has positively 
impacted Medicare and Medicaid reimbursement, by keeping the facility above all of the benchmarks 
set by CMS. 
On top of the financial savings that occurred with the zero rate of IV medication errors and the 
increased reimbursement related to the higher HCAAPS scores, another benefit was a sharp decrease 
in HACs, such as falls and infections. It was determined that the reason for this was that the time that 
the nurses were not spending trying to document allowed them to spend more time providing high-
quality nursing care for their patients and families. Finally, another benefit was a significant increase

quality nursing care for their patients and families. Finally, another benefit was a significant increase 
in employee satisfaction that resulted in a decreased turnover rate, thus decreasing orientation costs 
dramatically. 
The tablet that the nurse was using, as he or she sat at the patient’s bedside with the family, looked 
somewhat different than the tablets of 2015. It was thinner and, while it was much larger, it was also 
foldable. In its folded form, it fit easily in the pocket of a lab coat or in a side pocket on the computer 
used for the EHR. It could be used either folded or unfolded and will display the same data or allow for

302 Biomedical Informatics 
the same data entry in either state. The primary advantage of unfolding it to its full size is that it will 
display data in a size format that enables multiple categories of data to be displayed on the same sheet. 
This format was specifically designed to utilize the best features that the paper flow sheet had in previ­
ous years, while utilizing technology to take it to a whole new level. If the tablet is fully open, data will 
still be downloaded directly into it and the display will be updated as new data are entered. This design 
format was based on extensive neuroscience research into the optimum visual display of data to enable 
the viewer to accurately absorb complex information and use it to support critical-thinking processes. 
Since the tablet is handled often and by different practitioners, at periodic intervals throughout the 
shift, the nurse places it in a specially designed sanitizing station that cleans it via controlled multispec­

tral radiation. This process successfully eliminates even the superbugs of 2025. The same technology is 
also available as another option for hand hygiene in addition to the traditional soap and water and hand 
sanitizer. In fact, prior to the patient’s admission to the room, the same multispectral radiation was used 
to sweep the room to create a clean environment. 
The patient is also wearing a wristband with radio-frequency identification chips with a full record of 
past history. Any data that have been added during the hospital stay will be available for downloading, 
which includes not only data from the patient’s history but the current data that have been added while 
the patient has been hospitalized. In the unlikely event that an evacuation is necessary if a power failure

the patient has been hospitalized. In the unlikely event that an evacuation is necessary if a power failure 
occurs, the information contained on the wristband is equivalent to having the full medical record. 
By 2025, the storage capability has increased dramatically. 
Due to the patient’s instability in the OR, an IABP was inserted into his or her descending aorta to 
serve as a support to his or her heart. That evening as his or her kidneys failed, the decision was made to 
start the patient on CRRT. At the start of therapy with both of these devices, the nurse scanned the bar 
code of each and scanned the patient’s identification bracelet. This linked both devices with the EHR, 
and data from them were downloaded directly every hour, along with all of the other vital signs. The fact 
that the nurse did not have to type the numerous settings, pressures, alarm values, and parameters into

that the nurse did not have to type the numerous settings, pressures, alarm values, and parameters into 
the EHR meant that he or she was able to concentrate on his or her patient and instead of trying to keep 
up with recording the data, he or she was able to continuously observe and analyze it. 
At 7 p.m., when the full set of vital signs and parameters needs to be entered into the computer, the 
nurse was busy suctioning the patient to maintain patency of his or her endotracheal tube, which had 
a large amount of secretions. He or she was also beginning to recover from the anesthesia and was 
responding to voice and following commands appropriately. The nurse reassured him or her that the 
surgery was over and that he or she would give him or her medication for pain, which he or she did. 
During the time that the nurse was busy with the patient, the following data points were entered into

During the time that the nurse was busy with the patient, the following data points were entered into 
the record: all information displayed on the monitor, including temperature, heart rate, rhythm, arterial 
BP, MAP, CVP, PAP, CO, CI, SVR, and SPO2; all respiratory parameters from the ventilator, including 
mode, set rate, actual rate, FIO2, TV, and PEEP; all IABP settings and pressures including ratio, systolic, 
augmented diastolic, and end diastolic; and all CRRT volumes and pressures including TMP, prefilter 
volume, postfilter volume, and access pressure. 
Because the nurse was not busy typing, he or she was better able to observe and analyze all of the 
numbers and pressure waveforms. He or she was able to detect trends that indicated whether the patient 
was improving or deteriorating. He or she had time to spend with the patient. Part of this time was spent 
explaining to him or her and to his or her family members what was happening, while at the same time

explaining to him or her and to his or her family members what was happening, while at the same time 
continuously observing the patient and all of the data displayed on the monitor and the support devices. 
He or she was also able to turn the patient to assess his or her skin integrity and to institute measures to 
prevent pressure ulcers. The hospital has seen a decrease in the incidence of facility-acquired pressure 
ulcers since implementing the fully integrated EHR system. This has improved reimbursement rates 
since they are in compliance with the CMS zero tolerance for pressure ulcer development. In addition, 
there have been no lawsuits relating to pressure ulcers. Additionally, there has been an improvement in 
other forms of documentation, such as patient and family education and compliance with core measures 
and patient safety goals. All of these have benefitted the hospital financially.

303 Critical Care Nursing Perspective on the Electronic Health Record 
While the nurse is busy suctioning the patient and getting the pain medication, the surgeon comes 
to the bedside to see how the patient is doing. While he or she waits for the nurse to give him or her a 
verbal update on the patient’s condition, he or she takes the tablet and opens it. He or she touches the 
appropriate icon and changes the view of the screen to the flow sheet view setting that displays of all of 
the vital signs along with the doses of all of IV medication infusions that he or she is receiving. This 
gives him or her a snapshot of the patient’s overall condition. After he or she leaves, the nurse touches the 
microphone on his or her ID badge for voice entry and requests events. He or she states that the surgeon 
has just visited and is aware of all current vital signs and lab data. This information will be included in 
the EHR as a timed entry.

the EHR as a timed entry. 
Shortly after the surgeon’s visit, the patient’s cardiologist views the EHR from home. He or she is also 
able to view the real-time data and waveforms on his or her computer screen at home. He or she is con­
cerned about the patient and contacts the nurse via a tablet-to-tablet communication link. The nurse 
responds and in answer to the cardiologist’s request, and he or she brings the tablet to the patient’s bedside. 
It has viewing capability and the cardiologist can directly see the patient. He or she decides to change one 
of the IV medications to a different medication and he or she enters this order from home. Not only is the 
nurse able to see the medication order, but the pharmacist is able to see it too. He or she quickly profiles 
the medication and clears it so that the nurse can obtain it from the dispensing system on the unit. He or

the medication and clears it so that the nurse can obtain it from the dispensing system on the unit. He or 
she scans the patient’s ID band, scans the medication bag, and scans the bar code on the infusion pump. 
Since this is a new medication, the EHR searches for the physician’s order in the record and will compare 
the details of the order to the concentration on the bag as well as cross-referencing this with the settings on 
the infusion pump. This will ensure that all details of the order are correctly carried out. 
As the end of the shift approaches, the nurse quickly reviews the documents. He or she places the 
monitor in full-screen view that now organizes all of the current physiologic data onto the screen, 
arranged according to time. It also adds pertinent data regarding procedures that the patient has had 
done during the shift into a form that will be added to throughout the patient’s hospital stay. With the

done during the shift into a form that will be added to throughout the patient’s hospital stay. With the 
touch of another icon, the data are displayed as a shift report  view. The nursing staff has designed this 
view to use as a communication tool when they endorse to each other at the change of shift. 
The reason that the hospital invested the initial capital to implement a fully functioning EHR system, 
with the ability to communicate with all monitors and devices, was that in 2018 the federal government 
selected data entry as the next meaningful use incentive. Hospitals had the same incentives for meeting 
benchmarks of data entry of physiologic parameters as they had in meeting the original meaningful use 
benchmarks that were the catalyst for the original explosion of EHR implementation. 
10.10 Summary 
If all of the desired features from the wish list of the EHR are incorporated, what will the EHR in a criti­

cal care unit look like in 2025? All devices that are capable of communicating with each other should 
do so. By 2025, there should be a body of research that demonstrates the positive effects of automatic 
data entry on an increased level of customer satisfaction because of the additional time spent by nurses 
with patients. There should also be a body of literature that begins to demonstrate the improved patient 
safety results. Any other data that do not download automatically should be easy to enter perhaps by a 
touch screen or voice recognition. Record retrieval will be easier as well. The research that supported the 
standardization of terminology also revealed that much of the entries that nurses made were into the 
narrative progress notes. The computer should be able to read or recognize certain key words. It should

narrative progress notes. The computer should be able to read or recognize certain key words. It should 
have the capability of looking anywhere in the record that the data are located. And, finally, it should 
be a priority that when hospitals make decisions about implementing and upgrading computer-based 
documentation systems, the frontline nurses have a strong voice in the selection process. The EHR needs 
to be a tool that utilizes the best features of computer-based technology so that it meets the needs of the 
frontline nursing staff, who are then freed up to spend their time doing what they do best, that is, pro­
viding expert care to critically ill patients and their families.

304 Biomedical Informatics 
Questions 
 1.  Discuss the documentation challenges that exist for nurses in the critical care setting. 
 2.  Explain the legal requirements that govern documentation of the hospitalized patient. 
 3.  Discuss three advantages to implementing an EHR that has full communication capability with  
monitors and other biomedical devices in the critical care setting. 
 4. Identify three potential research questions relating to the use of EHRs. 
 5.  Discuss how the most effective qualities of a paper record could be incorporated and improved  
with the technology of a computer-based documentation system. 
Glossary 
Advanced cardiac life support (ACLS): The American Heart Association set of guidelines of clini­
cal interventions for the urgent treatment of cardiac arrest, stroke, and other life-threatening 
medical emergencies, as well as the knowledge and skills to deploy those interventions. This

medical emergencies, as well as the knowledge and skills to deploy those interventions. This 
content is also offered as a course comprised of lectures, hands-on practice, written test, and 
return demonstration. 
Advanced practice registered nurse (APRN): An APRN is a registered professional nurse with an  
advanced degree, either masters or doctorate. There are four recognized APRN roles: certified  
registered nurse anesthetists, certified nurse midwives, clinical nurse specialists, and certified  
nurse practitioners. 
Acute coronary syndrome (ACS):  Refers to any group of symptoms attributed to the obstruction of 
the coronary arteries. The most common symptom prompting diagnosis of ACS is chest pain, 
often radiating to the left arm or angle of the jaw, pressure-like in character, and associated 
with nausea and sweating. 
Augmented diastolic:  An intra-aortic balloon pump (IABP) is positioned in the descending aorta. It

Augmented diastolic:  An intra-aortic balloon pump (IABP) is positioned in the descending aorta. It 
inflates during diastole, displacing blood volume and increasing, or augmenting, the diastolic 
pressure in the aortic root. 
Blood pressure: The pressure of the blood in the circulatory system, often measured for diagnosis, since 
it is closely related to the force and rate of the heartbeat and the diameter and elasticity of the 
arterial walls. 
Blood products: Any component of the blood that is collected from a donor for use in a blood transfu­
sion. Whole blood is rarely used; most blood products consist of specific processed compo­
nents such as red blood cells, blood plasma, or platelets. 
Blood type:  Also referred to as “blood group.” Any of various classes into which human blood can be 
divided according to immunological compatibility based on the presence or absence of specific 
antigens on red blood cells.

antigens on red blood cells. 
Braden Scale: An evidence-based method of determining a patient’s risk of developing a pressure ulcer. 
The patient is assessed for the ability to move or the presence of moisture, among other items, 
each of which is scored. The total score indicates whether a patient is at high or low risk. This 
assessment is performed on admission and then either daily or every shift. 
Cardiac arrest: The cessation of cardiac activity resulting in loss of an effective pulse. The treatment is 
immediate cardiopulmonary resuscitation. 
Cardiac index (CI): The cardiac output (CO) corrected to reflect the size of the patient. It has the follow­
ing formula: CO ÷ body surface area = CI. The body surface area is dependent on the patient’s 
height and weight and is measured in liter/minute/square meter. 
Normal value: 2.6 to 4.2 L/min/m2

Normal value: 2.6 to 4.2 L/min/m2 
Cardiac output (CO): The volume of blood pumped by the heart per minute, measured in liter per min­
ute (L/min). Normal value, 5 to 6 L/min.

305 Critical Care Nursing Perspective on the Electronic Health Record 
Cardiac rhythm: The electrical activity of the heart; the impulse starts at the sinus node, conducts 
through the atrial tracts into the atrioventricular node, and passes into the ventricles via the 
bundle of His, through the left and right bundle branches, and into the purkinje fibers in the 
ventricles. 
Cardiogenic shock: Severely impaired circulation of blood and delivery of oxygen to the tissues second­
ary to failure of the heart as an effective pump. 
Centers for Medicare and Medicaid Services (CMS): A federal agency within the U.S. Department of 
Health and Human Services that administers the Medicare program and works in partner­
ship with state governments to administer Medicaid, the State Children’s Health Insurance 
Program, and health insurance portability standards. 
Central lines:  An intravenous catheter that is passed through a vein and terminates in the right atrium 
of the heart.

of the heart. 
Central venous pressure (CVP): The pressure measured in the right atrium of the heart. It serves as an 
estimate of blood volume, although it is not a direct measure of this parameter. 
Chest tubes:  A flexible plastic tube that is inserted through the chest wall into the pleural space or 
mediastinum. It is used to drain air, fluid, or blood from the thoracic or mediastinal cavities. 
Clinical information system (CIS):  A computer-based system that is designed for collecting, storing, 
manipulating, and making available clinical information for the healthcare delivery process. 
Clinical nurse specialist (CNS): L i c e n s e d  r e g i s t e r e d  p r o f e s s i o n a l  n u r s e s  w i t h  g r a d u a t e  p r e p a r a t i o n 
(either master’s or doctorate). CNSs are clinical experts in the treatment of illness, and the

(either master’s or doctorate). CNSs are clinical experts in the treatment of illness, and the 
delivery of evidence-based nursing interventions in a specialty population (e.g., critical illness, 
women’s health, pediatrics, and geriatrics). 
Continuous positive airway pressure:  A technique of assisting breathing by maintaining the air pres­
sure in the lungs and air passages constant and above the atmospheric pressure throughout 
the respiratory cycle. 
Continuous renal replacement therapy (CRRT): An extracorporeal blood purification therapy 
intended to substitute for impaired renal function over an extended period of time.
 
Core measures: A set of quality indicators defined by the Centers for Medicare and Medicaid Services.
 
Critical care: The specialized care of patients whose conditions are life threatening and who require 
comprehensive care and constant monitoring, usually in intensive care units.

comprehensive care and constant monitoring, usually in intensive care units. 
Cross match: In transfusion medicine, this refers to the testing that is performed prior to a blood trans­
fusion in order to determine if the donor’s blood is compatible with the blood of an intended 
recipient. 
Diastolic: The lowest arterial blood pressure of a cardiac cycle occurring during diastole of the heart. 
Electrolytes:  Electrolytes are minerals in the blood and other body fluids that carry an electric charge. 
The primary electrolytes in the body are potassium, sodium, calcium, magnesium, chloride, 
and phosphorous. 
Electronic medication administration record (eMAR):  A method of listing the medications that are 
prescribed for a hospitalized patient and recording their administration. 
End diastolic Pressure:  The pressure in the ventricles at the end of diastole, when the ventricle is filled 
with blood, just prior to the systolic ejection.

with blood, just prior to the systolic ejection. 
Endotracheal tube: A hollow, flexible tube that is inserted via the mouth, through the vocal chords, and 
into the trachea. The purpose is to maintain a patent airway. 
Foley catheter: A flexible catheter that is inserted through the urethra and into the bladder for the pur­
pose of draining urine. 
Fraction of inspired oxygen (FIO
2): The percentage of oxygen that a patient is inhaling. Room air is 21% 
oxygen. Therapeutic delivery systems can supply an FIO 2 up to 100%. 
Heart failure:  A clinical syndrome characterized by systemic perfusion inadequate to meet the body’s 
metabolic demands as a result of impaired cardiac pump function.

306 Biomedical Informatics 
Hemodialysis: Utilizing a device with a semipermeable membrane to filter wastes and fluids from the 
blood when the kidneys no longer function. 
Hemodynamic monitoring: The expert collection and analysis of qualitative and quantitative data of 
cardiopulmonary function. Fluid-filled monitoring systems attach to intravascular catheters 
and are used for continuous invasive measurement of arterial and cardiac pressures. 
Infusion pump: Medical devices that deliver fluids, including nutrients and medications such as anti­
biotics, chemotherapy drugs, and pain relievers, into a patient’s body in controlled amounts. 
Institute of Medicine (IOM): An independent, nonprofit organization that works outside of govern­
ment to provide unbiased and authoritative advice to decision makers and the public. It was 
established in 1970 and is the health arm of the National Academy of Sciences, which was 
chartered under President Abraham Lincoln.

chartered under President Abraham Lincoln. 
Interdisciplinary plan of care (IPOC): The goal of the IPOC is to support continuity, quality, and safe 
patient-centric care utilizing the expertise of the various members of the healthcare disciplin­
ary team. 
Interoperable: The ability of a system to work with or use the parts or equipment of another system. 
Intra-aortic balloon pump (IABP): A mechanical device that is inserted via the femoral artery. It is 
comprised of a balloon that inflates with helium during diastole and deflates fight before sys­
tole. It increases myocardial oxygen perfusion and decreases the workload of the heart. It is 
used for patients with an acute myocardial infarction or cardiogenic shock. 
The Joint Commission (TJC): An independent, not-for-profit organization, TJC accredits and certifies 
more than 20,500 healthcare organizations and programs in the United States.

more than 20,500 healthcare organizations and programs in the United States. 
Mean arterial pressure (MAP):  The average pressure in a patient’s arteries during one cardiac cycle. 
It is considered a better indicator of perfusion to vital organs than the systolic pressure. It is 
calculated with the following formula: 
Systolic + 2
(diastolic )MAP = 3 
National Patient Safety Goals (NPSGs):  In 2002, The Joint Commission established its NPSGs pro­
gram. The NPSGs were established to help accredited organizations address specific areas of 
concern in regard to patient safety. 
Never events: The National Quality Forum defines never events as errors in medical care that are of 
concern to both the public and healthcare professionals and providers, clearly identifiable and 
measurable, and of a nature such that the risk of occurrence is significantly influenced by the 
policies and procedures of the healthcare organization.

policies and procedures of the healthcare organization. 
Oxygen saturation: Oxygen is carried in the blood attached to the hemoglobin molecules. Oxygen satu­
ration is a measure of how much oxygen the blood is carrying as a percentage of the maximum 
that it could carry. 
Peritoneal dialysis:  A method of removing waste products and fluid from the blood in the setting of 
kidney failure. A fluid, dialysate, is instilled into the abdomen and the exchange takes place 
between the blood vessels in the peritoneum and the dialysate. 
Positive end expiratory pressure (PEEP):  A technique used with patients who are intubated and on a 
ventilator in which positive pressure is maintained in the airway throughout exhalation, so 
that the alveoli (air sacs in the lungs) do not deflate completely at the end of expiration. The 
objective is to increase the time for oxygen–carbon dioxide exchange as well as to facilitate 
reexpansion of the alveoli on the next inspiration.

reexpansion of the alveoli on the next inspiration. 
Pressure ulcer: An injury to the skin and underlying tissue resulting from prolonged pressure, friction, 
or shearing forces.

307 Critical Care Nursing Perspective on the Electronic Health Record 
Pulmonary artery pressure (PAP):  A measure of the blood pressure found in the pulmonary artery 
measured by inserting a catheter into the right atrium and advancing it into the right ventricle 
and out into the pulmonary artery. The normal pressures are 9–18 mmHg/ 6–12 mmHg. 
Pulse oximetry:  A procedure used to measure the oxygen level (or oxygen saturation) in the blood. It is 
considered to be a noninvasive, painless, general indicator of oxygen delivery to the peripheral 
tissues, such as the finger or earlobe. 
Radio-frequency identification:  The wireless noncontact use of radio-frequency electromagnetic fields 
to transfer data, for the purposes of automatically identifying and tracking tags attached to 
objects. 
Sepsis: A potentially life-threatening complication of an infection that occurs when chemicals released 
into the bloodstream to fight the infection trigger inflammatory responses throughout the

into the bloodstream to fight the infection trigger inflammatory responses throughout the 
body. This inflammation can trigger a cascade of changes that can damage multiple organ 
systems, causing them to fail. 
STAT: A medical abbreviation for urgent or rush. Something ordered as STAT is to be done immediately. 
Stroke: A stroke occurs when the blood supply to part of the brain is interrupted or severely reduced, 
depriving brain tissue of oxygen and nutrients. Within minutes, brain cells begin to die. 
Systolic: The highest arterial blood pressure of a cardiac cycle occurring immediately after systole, or 
contraction, of the left ventricle of the heart. 
SVO
2: Mixed venous oxygen saturation reflects the amount of oxygen consumed by the tissues. It mea­
sures the difference between the oxygen delivered by the arterial system and the amount of 
oxygen returned to the heart by the venous system. Normal SVO2 is between 60% and 80%.

oxygen returned to the heart by the venous system. Normal SVO2 is between 60% and 80%. 
Tidal volume: The volume of air inspired or expired in a single breath during regular breathing. 
Tracheostomy: A surgical procedure to create an opening through the neck into the trachea. A tube is 
placed through this opening to provide an airway and to remove secretions from the lungs. 
Ventilator: A device that supports breathing. It delivers oxygenated air to the lungs under positive pres­
sure. The patient exhales passively. 
Venous thromboembolism (VTE): A deep venous thrombosis is a blood clot that forms in a vein deep 
inside a part of the body. The most common site is in the large veins in the lower leg and thigh. 
The danger is that when a clot breaks off and moves through the bloodstream as an embolism, 
it can lodge in the lungs. 
Ventricular assist device: A mechanical pump designed to support heart function and blood flow.

Ventricular assist device: A mechanical pump designed to support heart function and blood flow. 
Blood is taken from the ventricle and passes through the pump. It is then returned to the aorta 
for circulation throughout the body. 
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11.1 	 Introduction ...................................................................................... 310
 
11.2 	 IT Sphere of Influence ...................................................................... 310
 
Communicator • Educator • Decision Maker • Change 
Agent • Facilitator • Implementer • Risk Taker • Listener 
11.3 	 Information Technology Domains ................................................ 312 
Strategic Planning • Infrastructure • Security • Clinical 
Applications • Business (Nonclinical) 
Applications • Integration • Biomedical 
Engineering • Telecommunications • Clinical Leadership/Medical 
and Nursing Informatics 
11.4 	 Healthcare IT Skill Sets ................................................................... 314 
Project Management • Hardware and Software • Biomedical 
Engineering • Telecommunications • Development/ 
Programming • Clinical Informatacists • Security and Asset 
Protection • CIO and Leadership Team • Competing Forces

Protection • CIO and Leadership Team • Competing Forces 
11.5 	 Stakeholder Analysis .........................................................................317 
Need • Stakeholders • Politics • Funding • Executing the IT Project 
11.6 	 Managing IT Projects ....................................................................... 318 
Where Do We Begin? • How Do We Do It? 
11.7 	 How Do We Know We Are Done? .................................................320
 
Go-Live Decision • First Productive Use • Acceptance 
Philomena Diquollo 11.8 Conclusion .........................................................................................320 
11 
Healthcare Management 
Information Technology in 
the Full Service Facility 
309

310 Biomedical Informatics 
Chapter goals:  Explain various information technology (IT) roles and responsibilities in a healthcare 
setting; identify drivers for IT project decision making, discuss software implementation process. 
11.1 Introduction 
The evolution of technology use in patient care services has been fascinating. From the first “dumb” 
terminals and light pens at the nurse’s stations to the use of sophisticated mobile devices at the point 
of care, the landscape and workflow have dramatically changed. Much like the dot.com phenomenon 
of days past, the healthcare market at the turn of the century was ripe for the introduction of ways to 
reduce the use of pen and paper in the acute care setting. Application development exploded. And, as 
in the dot.com era, those applications that were able to meet customer demands have survived and 
matured. Not only have applications matured but healthcare culture and behavior is changing as well.

matured. Not only have applications matured but healthcare culture and behavior is changing as well. 
The expectation in these times is that hardcopy documentation is an exception rather than a rule and 
there should be easy ways to acquire data. 
In this chapter, the focus will be on what it takes to support a healthcare organization, understanding 
the complexity of a heavily regulated, highly technical, and safety-conscious environment. 
In the healthcare setting, the organizational role of the IT department is often that of “influencer” 
to support the mission and vision of the organization. The users of technology are the business owners 
directed and supported by the IT department. The domains IT supports are varied with necessary roles 
to manage operational and regulatory standards. Project selections and implementations are driven 
by infrastructure needs to stay technologically current and operational needs to support bedside and

by infrastructure needs to stay technologically current and operational needs to support bedside and 
diagnostic departments. Management of projects is focused and uses industry standard practices to stay 
on time and on budget. 
With the pervasive use of technology in healthcare, the role of the healthcare IT professional in orga­
nizations has evolved as well. Technology platforms themselves shape the skill set support of an envi­
ronment. Mainframe programming and, operational and technical support require a very different skill 
set and team from a Cloud hosted thin client environment. Clinical support staff has emerged as a 
requirement to support system users. 
A constant is changing technology needs in healthcare. Roles and responsibilities continually shift to 
meet the changing demands. The IT professional organization needs to be fluid and flexible to effectively 
lead and respond. 
11.2 IT Sphere of Influence

11.2 IT Sphere of Influence 
Most people new to the healthcare IT field consider the job technical in nature with a focus on infra­
structure. In fact, IT departments have a much wider sphere of influence in an organization. 
11.2.1 Communicator 
The hallmark of an effective IT department is the ability to communicate with all levels of the organiza­
tion. Keeping the organization aware of the IT roadmap, timelines, changes, and updates builds trust 
and relationships. As in any facet of business, relationship is the key to accomplishing organizational 
goals. Walking rounds and face-to-face time demonstrate willingness to take customers’ needs into con­
sideration. Conversation, formal or informal, keeps a pulse on the organization and helps to anticipate 
a situation before it develops into a dissatisfied customer. 
Communication can take many forms: face to face, meetings, policies and procedures, emails,

Communication can take many forms: face to face, meetings, policies and procedures, emails, 
blogs, newsletters, application messages, digital signage, and announcements. The important thing 
is to just do it. Keeping the intended audience in mind directs the method or methods that need to 
be employed.

311 Healthcare Management Information Technology in the Full Service Facility 
11.2.2 Educator 
Computers and software can still be foreign to many users in a healthcare organization. In spite of the 
pervasive use of technology in today’s world, the workings of IT in the healthcare business world can be 
a mystery. Federal regulations, threats in the marketplace, correct use of the technology, and industry 
trends are areas in which the general user in healthcare needs guidance and assistance. 
IT, like most industries, has its own language of acronyms and slang. The IT profession needs to be 
able to translate difficult concepts into terms the general user can understand. Often the general user 
does not understand why systems do not behave like personal devices. IT professionals are continually 
educating users on how and why things perform the way they do. 
11.2.3 Decision Maker

11.2.3 Decision Maker 
IT professionals lead and direct choices related to technology and use of systems. There are factors to 
consider when choosing infrastructure and software for the organization: ease of use, flexibility, scal­
ability, reputation, performance, support, to name a few. At the speed technology changes, the IT pro­
fessional must be cognizant of trends and directions in the market place. Systematic methodology for 
making the right selections for the right reasons to sustain an organization for the long term is impor­
tant. A choice for today will impact use for many years. 
Technology decisions are best made with end user involvement. The best product in the world may 
never be embraced by users if they are not included in the process. Building the relationship to engage 
end user participation in decision making contributes to successful selections. A goal of the IT decision

end user participation in decision making contributes to successful selections. A goal of the IT decision 
maker is to have the best information not only about a product but users’ perceptions of the product 
usability in their workflow. 
11.2.4 Change Agent 
Technology change in an organization is an interesting phenomenon. Sometimes it is the clinicians who 
drive change because of a new procedure, piece of equipment, or regulatory requirement. Although the 
change may be biomedical in nature, today the line is blurred between pure biomedical engineering and 
computer technology. Most diagnostic and procedural equipment coming available has the means to 
capture and store data for viewing, reporting, and analytics. On the technology side, improvements in 
infrastructure, network, and desktop devices require changes to provide faster systems, storage capabil­
ity, or bandwidth. 
In either case, IT professionals are often the drivers of the change and as such an understanding of

In either case, IT professionals are often the drivers of the change and as such an understanding of 
change theory, resistance to change, and communication effectiveness is valuable. Providing value to 
the end user when a new way of doing things is necessary supports culture change. Awareness that 
change is not easy prepares the IT professional to respond to users in a meaningful way. 
11.2.5 Facilitator 
There are times when a project may be contracted to third parties, or IT has been asked to participate in 
a demo or meeting for potential involvement. In these instances, it is important for the IT professional 
to facilitate communication and activities for the best interest of the organization. Regardless of who is 
performing functions of programming, installation, education, or support, the responsibility lies with 
the employed staff to ensure that all organization expectations and requirements are being met.

the employed staff to ensure that all organization expectations and requirements are being met. 
IT has a solid understanding of the way data move through the organization. Often IT is called upon 
to assist with linking fragments of data together, connecting the dots between systems to produce mean­
ingful information or improved workflow. By facilitating communication in projects, IT can provide 
structure to non-IT projects in the organization.

312 Biomedical Informatics 
11.2.6 Implementer 
Technology staff is very accustomed to following project management methodology. Although a depart­
ment may be the business owner of system, the IT organization is expected to provide structure and 
guidance to implementations. Members of the IT department are often called to participate as subject 
matter experts (SMEs) or as project leads in order to bring projects in on time and on budget. 
11.2.7 Risk Taker 
IT staff is constantly assessing risk to the organization. Evaluation of risk to end users related to business 
continuity, security, and malicious intent is weighing the potential for risk. And sometimes judgment 
calls must be made for the good of the many. It is difficult to deal in generalities when change is required. 
Assessment, coordination, and backup plans are a requirement to mitigate harm to the organization. 
11.2.8 Listener

11.2.8 Listener 
Users of IT may have difficulty articulating their needs. Especially when the request is for analytics, 
users may know the end result they are looking for but have difficulty explaining what they want. Often 
they need to be guided with specific questions to define what is needed. It is important that IT profes­
sionals listen without making assumptions. Time can be spent creating screens, forms, reports, outputs 
that are not what the user is requesting. Taking the time to listen and define saves time in the end. 
Working with technology can be frustrating to users. It is important to have an environment where 
users can complain or criticize without judgment in order to fix a problem. As in most situations in life, 
sometimes it is important to just listen so that our customers feel that they are heard and then to be able

sometimes it is important to just listen so that our customers feel that they are heard and then to be able 
to educate, repair, redesign, or think outside the box to achieve solutions to problems. 
11.3 Information Technology Domains 
Supporting healthcare environments requires groups of people whose function is devoted to particular 
aspects of the IT organization. To the casual observer, the “IT department” consists of staffs who manage 
desktops and printers. This perception cannot be further from the truth. Support of a complex healthcare 
environment requires teams of specialists who have specific areas of focus. Although the domains may 
vary from organization to organization, one will find typical types of specialties in any organization. 
11.3.1 Strategic Planning 
The IT executive team is the strategic planning unit for the technology direction of the organization. 
The executive team has the chief information officer who directs reports. This team directs the activities

The executive team has the chief information officer who directs reports. This team directs the activities 
of the IT organization to support the mission and vision of the entity, whether it is a large multifacil­
ity healthcare system or a small local hospital. Planning is a necessity to being fiscally responsible and 
responsive to organizational needs. 
Inputs to short- and long-term plans are provided by the organization stakeholders and from within 
the IT department itself. Together, plans or roadmaps are formulated to meet immediate needs and can 
extend out for several years. 
11.3.2 Infrastructure 
The infrastructure team is the foundation of the organization, which all other services build upon. The 
focus of the infrastructure team is obviously the building, maintenance, and support of networks, data 
centers, server rooms, Internet, RFID, WiFi, and devices that may be in use or connected to the network.

313 Healthcare Management Information Technology in the Full Service Facility 
Without sound design and support, the performance of application tools and diagnostic equipment 
will be suboptimum. Poor performance leads to user dissatisfaction, which leads to underutilization of 
systems or constant complaints to and about the IT department. This team manages both hardware and 
the utility software required to run and monitor network infrastructures. Utility software such as asset 
management and device security software is managed by this group. 
Th e  im p l e m e n ta ti o n  o f  s u p e ri o r  n e tw o r ks  b rin g s  s a ti s f a cti o n  t o  th e  t e c hn o l o gy  t e am ;  h o w e v e r ,  in 
the bigger picture a high performing infrastructure leads to greater employee satisfaction, supporting 
organizational change and acceptance. 
11.3.3 Security 
Healthcare organizations are highly regulated and audited by federal, state, and certifying organizations

Healthcare organizations are highly regulated and audited by federal, state, and certifying organizations 
for quality and adherence to standards and best practice. Federal Health Information Technology for 
Economic and Clinical Health (HITECH) laws and the Health Insurance Portability and Accountability 
Act (HIPAA) drive security activities of the IT department. It is always a surprise to the newcomer to 
healthcare IT how threatened the IT environment has become. As a result of regulations and malicious 
intent, it is important to have a strong IT security department to provide direction, support, and moni­
toring of infrastructure and use of systems. 
The IT or HIPAA Security Officer is a designated position in healthcare organizations. The respon­
sibility includes responding to IT security incidents and breaches, educating employees on IT security 
policies and procedures, and working closely with the IT security department to protect the local entity

policies and procedures, and working closely with the IT security department to protect the local entity 
or healthcare system from internal and external threats. 
11.3.4 Clinical Applications 
Clinical applications are those that are used by healthcare workers who provide direct patient care or 
systems in support of clinical care of the patient. Generally, doctors, nurses, therapists, medical tech­
nologists, assistants who treat and diagnose patients and document patient care are users of clinical 
applications. This is a very broad category that encompasses not only documentation systems such as an 
electronic medical record (EMR) but also “ancillary” systems such as the radiology, laboratory, phar­
macy, perioperative, perinatal, and cardiology information systems, to name a few. The functions in this 
domain focus on support of the clinical user workflow, including data capture to meet documentation,

domain focus on support of the clinical user workflow, including data capture to meet documentation, 
regulatory and patient safety requirements, quality indicators, and report writing. 
Applications in this domain can be as pervasive as an integrated physician order entry, documenta­
tion, charging and billing system such as an Epic, Cerner, Siemens, or McKesson product line, or a niche 
application that is used by a very specific subset of patient such as in an oncology center. Regardless of 
the type of application, the approach to implement and support the application follows similar paths. 
11.3.5 Business (Nonclinical) Applications 
Nonclinical applications support the operations of the organization: human resources, payroll, supply 
chain, registration, coding, billing, and decision support are examples in this domain. The support of 
these types of applications requires multiple teams that focus on the particular workflow of the respec­
tive departments. 
11.3.6 Integration

11.3.6 Integration 
Selections of software are shifting from the interfaced paradigm, or the “best of breed” implementa­
tions, to the integrated model, single-database structure for clinical and business applications. Even with 
this shift, legacy systems, niche software, and diagnostic modalities require some level of integration.

314 Biomedical Informatics 
Whether HL7 or DICOM integration, this team’s focus is on the transactions that move data from one 
system to another using these structure formats. 
With the advent of accountable care organizations to manage population health and health informa­
tion organizations to share regional and statewide patient data, the need to integrate will increase as 
time goes on. 
11.3.7 Biomedical Engineering 
As noted earlier, biomedical engineering and IT departments overlap more and more. Biomedical diag­
nostic and monitoring equipment relies heavily on IT infrastructure; IT is asked to facilitate and par­
ticipate in biomedical equipment implementations. 
The trend is to combine the departments. Combining the departments, or at least creating a dotted 
line connection, ensures communication. Biomedical companies have specifications to connect devices 
to the network; however, the infrastructure team has to review the technology to ensure that connec­

tions meet organization standards. 
11.3.8 Telecommunications 
Telecom, similar to biomedical engineering, has merged with IT due to overlapping infrastructure 
requirements. Many support devices for clinicians connect to networks, or run over IP networks in 
facilities. Smart phones, IP phones, IP voice badges require software management to program and con­
nect devices, set up clinical groups, and activate features needed by clinicians to perform daily clinical 
and fast communication functions. 
11.3.9 Clinical Leadership/Medical and Nursing Informatics 
Physicians and nurses have had positions in the IT department in the past; however, with the surge of 
EMR implementations, the position has moved to the forefront as necessary for high performing health-
care organizations. EMR applications and clinical information systems have workflows that are physi­

cian centric. Evolving regulatory requirements and reimbursement models require that plans of care 
and orders are entered directly into applications by the physician. Nurses and therapists are required 
to respond to physician orders with electronic documentation and have their own sets of regulatory 
requirements to document standards of care. 
To meet the needs of physicians, nurses, and therapists, informatics has developed into its own 
domain with expertise in clinical workflow, IT systems, and education of end users. Clinical practice 
has standards, yet it is not cookie cutter. Standards of care are the norm; however, applications must be 
flexible enough to account for the unusual or abnormal situation that may arise. Documentation and 
orders are still required, but understanding and responding to the needs of the clinicians require a team

orders are still required, but understanding and responding to the needs of the clinicians require a team 
that understands the clinical workflow and speaks the same language as the customer base. Typically, 
physicians and nurses are the primary members of this team. 
11.4 Healthcare IT Skill Sets 
11.4.1 Project Management 
The most successful installations are those managed by people with project management experi­
ence. IT installations are usually high-dollar, high-impact activities. To protect the organization by 
keeping projects well communicated, visible, structured, and moving forward, a certified project 
manager is necessary. In healthcare, there are typically two types of implementations: the purely

315 Healthcare Management Information Technology in the Full Service Facility 
technical implementation to support the infrastructure and the application implementation, which 
is an installation that ultimately impacts clinical and business applications users in their daily 
workflow. 
Project managers may come from a variety of backgrounds; however, credentials from national cer­
tifying organizations such as the Project Management Institute or the American Society for Quality 
(6 and Lean Sigma) are the types of credentials a project management office (PMO) requires. Clinical or 
technical backgrounds may not be required but are preferred. 
11.4.2 Hardware and Software 
11.4.2.1 Technical Staff 
Technical staff usually comes through certified agencies, for example, A+ training, technical schools, or 
degree programs. And some staff has come up through the ranks with on-the-job training. The trend

degree programs. And some staff has come up through the ranks with on-the-job training. The trend 
today is to hire a college educated staff that comes to the job with an understanding of what the job 
entails or experience in the particular service line. Job opportunities are available in asset management, 
asset protection, network engineering, LAN administration, wireless infrastructure, data center opera­
tors, server room management, and desktop support. 
11.4.2.2 Software Support 
Software support staff in healthcare to date usually have come out of clinical areas when an opportunity 
to transition to an IT role has presented itself. Implementations in clinical settings have required IT 
staff that understand the jargon in the medical field and have an understanding of clinical workflow. 
Software support can be the EMR, ancillary systems such as the laboratory information system, niche

Software support can be the EMR, ancillary systems such as the laboratory information system, niche 
software such as birth certificate reporting, or nonclinical applications used by the human resource and 
finance departments. 
The term “out of clinical areas” does not necessarily mean a clinical provider. People exposed to 
clinical workflow and the terminology used, such as technicians, clerical staff, and technology staff, 
are examples of the types of staff that have typically transitioned into these types of roles. Logical 
thinking and an ability to pick up the clinical jargon are skill sets a person new to this role needs to 
possess. 
With the emergence of degree programs, software support can be learned in the classroom setting 
but also needs to be paired with the skills described to be effective in a clinical setting. Software support 
positions through a vendor rather than a clinical setting employment allow for a longer learning curve

positions through a vendor rather than a clinical setting employment allow for a longer learning curve 
to pick up workflow and unique medical terms, phrases, acronyms, and user needs. 
These types of activities are implementations, maintenance of the application, end user support, 
workflow analysis, error resolution, and liaison between the clinical staff and the vendor. 
11.4.2.3 Interfaces 
Interface programming is a learned skill. HL7 and DICOM programming is typically not taught as a 
degree path of study but falls under the umbrella of application support. Interface programming is a 
path that is for the person  who has the IT training and experience in a medical environment. 
11.4.3 Biomedical Engineering 
Biomed is an area of study that can stand on its own in a healthcare setting or combined with the IT 
department. Diagnostic and procedural equipment have been evolving with a heavy use of technol­

ogy that now must conform to infrastructure and HIPAA standards established by the technology 
teams.

316 Biomedical Informatics 
11.4.4 Telecommunications 
Like biomed, telecom is its own field of study. Telecommunications management is heavily reliant on 
software not only in the switch room but also found in the tools used by telephone operators. Today 
operators use sophisticated keyboard consoles to manage incoming and outgoing calls, paging, IP 
phones, and other technologies used to notify or support healthcare staff, patients, families, visitors, 
and vendors. 
11.4.5 Development/Programming 
The development team consists of programming staff who are actual programmers. In a healthcare envi­
ronment, generally third-party software from recognized vendors is installed. Sometimes a workflow or 
department is so unique that it needs “in-house” development. Development can be web based, use util­
ity software for rapid development, SQL programming, or use traditional programming languages like

ity software for rapid development, SQL programming, or use traditional programming languages like 
C#. This team has to be versed in database management to manage size and space for developed apps. 
11.4.6 Clinical Informatacists 
The clinical voice drives the development and enhancements to applications used in healthcare settings. 
As a tool to document, collect, and present information, the inclusion of clinical technical leaders is 
necessary to add value to the electronic documentation system and promote the use of EMR. Physicians 
and nurses are valued and sought-after members of the team. Their input drives decisions on displays, 
input field layout, hard stops, warning, and language. Speaking the same language as the end users, the 
clinical informatacists bridge the gap between the technical teams and the providers. 
11.4.7 Security and Asset Protection 
The focus of these types of teams is protecting the assets of the organization, including hardware, soft­

ware, and data. Hardware selection, software licensing and versions, tracking, disposal, network moni­
toring and protection, conformance with federal regulations regarding security, and asset protection 
fall into these categories. Staff typically have technical backgrounds. Activities revolve around threat 
surveillance, protection, and business continuity. 
11.4.8 CIO and Leadership Team 
The Chief Information Office and the management leadership team set the strategic and tactical IT goals 
of the organization. Leadership comes from a variety of educational and experiential backgrounds in IT, 
computer sciences, biomedical engineering, medical or nursing informatics, with a variety of experi­
ences in healthcare, industry, or business. Hospital organization and operations knowledge makes for 
the most successful leaders in healthcare.

the most successful leaders in healthcare. 
11.4.9 Competing Forces 
Every physician and employee user of technology has an idea on how to improve services and work­
flow. Ideas and recommendations for improvements, enhancements, and new technology are discussed 
every day. Projects can be as simple as adding a data component to a screen or as complex as installing 
an application with hardware, network, interface, ongoing maintenance, and reporting requirements. 
Change is generally handled through a change control-management process, which requires business 
justification, analysis of the request, approval, and implantation. Simple requests generally are simple 
change control process; complex projects require more detailed justification.

317 Healthcare Management Information Technology in the Full Service Facility 
The direction of clinical, business, and ancillary system implementations and change in hospitals 
takes into account different factors that drive decisions. IT expense is one of many competing demands 
on a healthcare facility where there are expenses related to physical plant, labor, supplies, and medical 
equipment. Several factors are considered when deciding on how dollars should be invested. 
11.5 Stakeholder Analysis 
11.5.1 Need 
Three priorities that drive hospital expense decisions as to where dollars are best spent are patient safety, 
billing, and regulatory requirements. Keeping patients safe while maintaining high-quality care is 
of paramount importance in any healthcare organization. Safety is so important that healthcare has 
“National Patient Safety Goals,” which hospitals must achieve to be considered a safe environment.

“National Patient Safety Goals,” which hospitals must achieve to be considered a safe environment. 
Safety goals are nationally reported via scorecards and websites designed to keep the public aware of 
hospital performance. EMRs and department-specific applications support workflow to ensure that the 
right patient is receiving the right orders, right medications, and right procedures. 
Revenue cycle applications manage the collection of patient information, both demographic and 
clinical, to produce an output of a clean bill to be sent to insurance companies for payment. Revenue 
cycle applications include but are not limited to registration systems, scheduling, forms printing, digital 
signature, and archiving of registration information, coding, billing, payments due, insurance verifica­
tion, and medical necessity for procedures. Getting it right the first time to reach the ultimate goal of

tion, and medical necessity for procedures. Getting it right the first time to reach the ultimate goal of 
timely reimbursement back to the facility is what makes hospitals viable. Having applications that pro­
vide financial reporting and modeling assists executive and financial leadership in making informed 
decisions and strategic plans. 
Healthcare is a heavily regulated industry. All aspects of healthcare business have some sort of best 
practice clinical care requirements, as well as monitoring or reporting requirements to the federal gov­
ernment, state, local, or certifying or monitoring agencies. Electronic systems support recording of doc­
umentation of care in formats that are legible and clear. Alerts and prompts can be added to applications 
to ensure data capture. Discrete data fields can be reported on with high reliability to normalize data 
and meet reporting requirements. 
11.5.2 Stakeholders

11.5.2 Stakeholders 
Stakeholders help to guide decision makers. Having a business case to support funding, referencing 
the three drivers mentioned earlier, is how hard decisions are made on projects that move forward. The 
stakeholders must be able to justify how their requests for software and hardware fit into the organiza­
tion’s goals. Considering the breadth and depth of IT needs in an organization, there are many demands 
for funding. Stakeholders making their business case can be the most powerful influence in a decision 
to fund or not. 
11.5.3 Politics 
Political influences are both internal and external. Internally, hospitals are a business like any other 
business. Organizational relationships and culture factor into decisions on IT selections and implemen­
tations. External political influences are decisions by local, state, and federal administrations. As men­

tioned earlier, healthcare is a heavily regulated industry. All three branches of government collect data 
for public reporting and safety, provide payment for services, and guide relationships with healthcare 
entities through healthcare policy. Meeting regulations often involves IT solutions to capture, collate, 
and report necessary data elements such as lab results for public health surveillance, coding for billing, 
and clinical care outcomes for patient safety measurements.

318 Biomedical Informatics 
11.5.4 Funding 
There are four data streams for IT funding:
 1.  Operating budgets for general day-to-day expenses : Labor, supplies, contracts, repairs, licensing,  
training, and conferences generally fall into this category. Budgets are usually approved annually 
along with the rest of the hospital. The national benchmark for IT budgets is 4% to 7% of the total 
operating budget.
 2.  Capital funding for high-dollar expenses on one-time purchases : Generally, items greater than an  
organization threshold, such as $10 K, require additional approvals and are funded through capi­
tal dollars. Although the money comes from the same hospital revenue stream, these high-dollar 
investments for items such as initial implementations of hardware, software, or major upgrades 
are reported differently for acquisition and depreciation following accepted and regulated hospi­
tal accounting practices.

 3.	  Grant funding : This type of funding is possible for IT projects as many support clinical care, 
research, or workflow improvement. Often IT is asked to provide detail on estimated expenses as  
part of a larger grant request. Grants are a valuable funding source to introduce new technology 
to the healthcare setting.
 4. Direct donations: Usually provided by companies, individuals, or patients to support clinical ini­
tiatives, this type of funding is directed, meaning it is for a specific purpose, for example, a grate­
ful family providing an electronic device to be used in a pediatric area or for patient teaching. 
11.5.5 Executing the IT Project 
Previously, factors that went into the selection process for IT projects were discussed: but how do we  
actually make it happen? This section examines the project lifecycle of a major implementation from the

actually make it happen? This section examines the project lifecycle of a major implementation from the 
point of inception to the acceptance by the end user. 
11.6  Managing IT Projects 
11.6.1  Where Do We Begin? 
11.6.1.1 Define  Need 
Many organizations use a PMO or steering committee to evaluate requests for IT implementations. 
Requests are submitted in writing and require specific information for assessment. Typical information 
gathered includes 
• 	 Project overview 
• 	 Business  justification 
•	  Procurement  expense 
• 	 Ongoing licensing and maintenance fees 
• 	 Funding source 
•	  Increase/decrease to labor expense, operating expense 
• 	 Project sponsor 
• 	 Project owner 
11.6.1.2  Market Place Analysis 
Departments or service lines may choose to arrange vendors themselves for demonstrations of  
the product and obtain proposals for implementations. Larger projects may require a request for

the product and obtain proposals for implementations. Larger projects may require a request for  
information (RFI) asking specific questions on application functionality and/or a request for

319 Healthcare Management Information Technology in the Full Service Facility 
proposal (RFP), which includes both functionality and pricing. RFI and RFP returns from vendors 
are reviewed by a team of (SMEs) to accept or reject moving the vendor forward in the selection 
process. 
11.6.1.3 Funding 
Generally, for any project to move forward, funding has to be secured. As described earlier, one of the 
four funding sources will need to be defined and considered in the decision to execute. 
11.6.1.4 Contracting and Security Review 
Once proposal terms are negotiated, the agreement will move to the legal department for contract 
review of terms and conditions. Vendors doing business with a hospital are required to sign a Business 
Associate Agreement, which outlines guidelines for the two companies to work together ensuring con­
fidential handling of sensitive information and generally accepted compliance practices.

fidential handling of sensitive information and generally accepted compliance practices. 
Some organizations may require a simultaneous IT security review. Security assessments include 
generally accepted security or regulated topics such as HIPAA compliance related to password security, 
HIPAA audit and reporting tools, and encryption, to name a few. Remote hosted or Cloud solutions 
require a more in-depth analysis to confirm asset protection when data are stored offsite, including ven­
dor privacy and security policies and procedures, disaster recovery, data backup, restore, and destruc­
tion practices, data center physical safeguards, to name few. 
Whether initiated by a department or in partnership with IT, ultimately the request will go to the 
PMO for evaluation or assistance in the decision-making process and implementation process. 
11.6.2 How Do We Do It? 
11.6.2.1 Kickoff

11.6.2.1 Kickoff 
The first meeting to take place is run by the project manager. This meeting includes the PMO, stakehold­
ers, vendors, and the IT groups who will participate in the project. It reviews the contract for clarifica­
tion for all parties, the project plan, milestone activities, and risks to the project. 
11.6.2.2 Workflow Analysis 
A work place assessment and analysis is scheduled with the stakeholders to understand current state, 
future state, and the gaps that need to be addressed. IT implementations change the way a depart­
ment does business. As with any change process role definition, expectations, and concerns need to be 
addressed in advance of the implementation. 
11.6.2.3 Environment Build 
Based on the workflow analysis, the vendor and IT teams will begin the hardware and software configu­

rations. Stakeholder SMEs will be called upon time to time for clarification and review. 
11.6.2.4 Testing 
One can never say enough about the need to test, test, and test. Testing follows a typical pattern of inter­
face testing to ensure connectivity, then discrete data element testing to ensure each data component 
interfaces properly from one system to another and is displayed in the correct field with the correct 
value, followed by end-to-end or integrated testing. Integrated testing follows the workflow from the 
beginning of the process continuing all the way through to the last process. Many scenarios will be 
tested to insure that functionality is performing as expected. With a clinical system, integrated testing 
begins at the point of scheduling and continues through registration, clinical documentation, and cod­

ing until a bill is produced correctly.

320 Biomedical Informatics 
11.6.2.5 Policy and Procedure Development 
During the testing and training phase of the project, the stakeholders will review and edit or create poli­
cies to support use of the system. Policy and procedure may address day-to-day functionality and use as 
determined by the entity and will always include a policy specific to downtime and downtime recovery. 
At this time, it is recommended to develop a business continuity plan to address multiple types of out­
ages or interruptions to system use, both short and long term. 
11.6.2.6 Training 
Training is the crux of a successful implementation. No matter how well a contract has been negotiated, 
a system has been built, or the testing is successful, an end user trained to navigate and use the system 
correctly is the key indicator of success of a project. Organizations may require a competency test to 
ensure end user readiness. 
11.7 How Do We Know We Are Done? 
11.7.1 Go-Live Decision

11.7.1 Go-Live Decision 
Prior to a go-live date, a “go–no go” meeting is held, chaired by the project manager and including the 
project team. System readiness is discussed as well as training status, hardware readiness, and training 
completed. The team will decide to proceed with the go-live or postpone if necessary. Generally, the live 
date is evaluated at milestones or when risk is identified to keep executive sponsors apprised of project 
progress and potential issues or concerns. 
11.7.2 First Productive Use 
Live dates require planning to support end users of software and hardware, command center space for 
project management, phone numbers or other contact information for immediate assistance, issues lists, 
and issues management plan. The scale of the implementation determines the space required for a com­
mand center and the personal for support. If departments are open 24 hours, round-the-clock coverage

mand center and the personal for support. If departments are open 24 hours, round-the-clock coverage 
is arranged. Generally, go-live on site end user support lasts a few days or several weeks, depending on 
the implementation. 
11.7.3 Acceptance 
Most contracts include a period of acceptance, whereby the last payment due to the vendor per the 
contract is 30 days post live. Adding this clause to the payment terms ensures the vendor will meet its 
contracted deliverables. The project manager, in conjunction with the stakeholders, will determine if 
the vendor has met its deliverables satisfactorily and the issues that arose during the implementation 
are addressed to the stakeholder’s satisfaction. At this time, the software/hardware is turned over to the 
support teams and the project is closed as completed. 
11.8 Conclusion 
Healthcare organizations are dynamic environments. As clinical and business needs drive the health-

care entity to change, the IT department has to be flexible and facile to respond. Medical informatacists 
are change agents who will lead and support organization demands.

Level I: Core Concepts .................................................................................322
 
12.1 	 Introduction ......................................................................................322
 
12.2 	 Predictions: A Cautionary Tale ......................................................322
 
Metrics • Biomedical Predictive Analytics
 
12.3 	 HCAHPS Score .................................................................................328
 
12.4 	 Center for Disease Control Data (Trends) ....................................330
 
12.5 	 Future Scenarios ...............................................................................330
 
Scenario 1 • Scenario 2 • Scenario 3 • Scenario 4 • Scenario 5
 
Level II: BMI Predictive Analytics Applied ..............................................334
 
12.6 	 Case Study: Scenario 1 ......................................................................334
 
BMI Predictive Equation Example • Cost Factors • Mandate

BMI Predictive Equation Example • Cost Factors • Mandate 
Factors • Intangible Cost Factors • Analysis of Results
 
Level III: The Future of Biomedical Informatics ......................................338
 
12.7 	 BMI Predictions ................................................................................338
 
Five Y ears: Intelligent Data • Ten Y ears: Intelligent 
Assistants • Twenty-Five Y ears: Global Integration • Fifty Y ears: 
150-Y ear Life Span • One Hundred Y ears: Ten Steps Forward or Five 
Steps Back 
12.8 Summary ............................................................................................340
 
Questions .......................................................................................................340
 
Glossary ......................................................................................................... 341
 
12.A 	 Appendix: HCAHPS Survey ...........................................................342
 
12 
Future Directions for

12 
Future Directions for 
321

322 Biomedical Informatics 
12.1 Introduction
 
Extrapolating future trends should be quantifiable if events followed linear causality, similar to a series 
of billiard balls. The superposition principle states that, for all linear systems, the net outcome caused by 
two or more stimuli can be calculated by the sum of the responses caused by each stimulus individually. 
Another example is wave interference; if two or more waves traverse the same space, the net amplitude at 
each point is the sum of the amplitudes of the individual waves. Even if the physics is more complex, we 
should be able to simulate possible outcomes. A classic example is the butterfly effect. If a butterfly flaps 
its wings thousands of miles away, we should be able to calculate the net effect on weather if our models 
are sophisticated enough to capture all variables. 
The problem arises if the variables are nonlinear, “relating to a system of equations whose effects are

The problem arises if the variables are nonlinear, “relating to a system of equations whose effects are 
not proportional to their causes.” Such a set of equations can be chaotic. So if the effects—possible future 
technological outcomes—are not proportional to their causes, then we have to try our best guess. I will 
try to be more exact in the root causes and likely outcomes (Figure 12.1). 
12.2 Predictions: A Cautionary Tale 
Here is an allegory to illustrate how predictions can be wrong, that is, probable outcomes that resulted 
in unexpected results. The exponential growth of the US space programs in the 1960s led to the moon 
landing on July 20, 1969. The decision to expand our launch capabilities and land on the moon appears 
to have been motivated by military concerns during the Cold War— controlling the high ground . The 
cause and effect seems straightforward: Sputnik 1, a Russian satellite, was the first manmade satellite

cause and effect seems straightforward: Sputnik 1, a Russian satellite, was the first manmade satellite 
sent into orbit on October 4, 1957, beating US efforts. Then on April 12, 1961, Yuri Gagarin, a Russian, 
became the first human in space. Both the Americans and Russians captured Nazi rocket scientists after 
World War II who led their respective programs. One month later, on May 25, 1961, President Kennedy 
announced the intent to land on the moon by the end of 1960s. “We choose to go to the moon in this 
decade and do the other things, not because they are easy, but because they are hard, because that goal 
will serve to organize and measure the best of our energies and skills.” “There is no strife, no prejudice, 
no national conflict in outer space as yet. Its hazards are hostile to us all. Its conquest deserves the best 
of all mankind, and its opportunity for peaceful cooperation may never come again.” The space race

of all mankind, and its opportunity for peaceful cooperation may never come again.” The space race 
began. National pride was the stated goal, probably used to sell the program to the public; sorry to be so 
cynical, but trying to extrapolate all contributing factors is the intent of this allegory. The underlined 
comment there is no conflict in outer space as yet seems clear. So far all straightforward cause and effect. 
A sample of positive nonlinear factors : (1) The series Star Trek  was televised from September 8, 1966, to 
June 3, 1969. It started off slowly but quickly became very popular; interest in space exploration grew. 
(2) In 1968, 2001 A space Odyssey was another popular movie whose centerpiece was the space station, a 
stepping point to future space exploration. The enthusiasm for space was building. But moon landings 
were abruptly canceled a few years after the initial landing: what happened? Most predictions suggested 
an exponential growth in space exploration.

an exponential growth in space exploration. 
A few negative forces : (1) We beat the USSR to the moon, which (most likely) was the major driving 
factor for the space race, not future space exploration. (2) The Vietnam war was in progress and was 
enormously taxing on the American psyche and pocketbook. (3) The Watergate scandal (possibly) dom­
inated our political discourse, and the impeachment of Nixon on August 9, 1974, dominated our politi­
cal discourse. Political forces and budget priorities have complex origins. 
The Soviet Union canceled its manned moon landing programs in 1970, that is, the Proton and Zond 
(Soyuz) programs, due to failures and the preceding Apollo 11 Mission success. The public assumption at

Future directions of biomedical informatics 
Predictive analytics Future scenarios 
Five years: Scenario 1: 95% of all
Biomedical predictive analytics medical documentationIntelligent
Lubliner 2014 data integrated and online
Ten years: Scenario 2: All medical
devices will automaticallyIntelligentPredictive update Electronic HealthCost factors: Predictive Intangible assistants Recordsconfidence External mandates weights costs factors (PCF) 
Twenty-five Scenario 3: EHR(2) the
next evolution in useryears: Global interfaces and Distributed
Extracted Cost Political integration HealthcareSubsidies PositiveHCACPS factorsfrom trends implementing (user surveys)CDC reports technologies Fifty years: Scenario 4: DistributedPenalties Negative 150 year life healthcare: Medical care
Cost of not will evolve beyond ourspans. implementing Meaningful Confidence current location based
hospital-physician centrictechnologies use levels One hundred system 

forward or 5 Scenario 5: eDoctor andExample 
 
323 Future Directions for Biomedical Informatics 
FIGURE 12.1 Future directions of biomedical informatics.

324 Biomedical Informatics 
the time was that since they could not be first, they did not bother, or more likely the USSR was actually 
further behind then what they publicly admitted. 
Apollo Missions 11–20 were planned, but the last three missions were canceled: Apollo 18 (sched­
uled for July 1973), Apollo 19, and 20. Written memos testify that Nixon, in August 1971, tried to cancel 
missions starting with Apollo 15. The stated intent was to focus resources on the Space Shuttle, one of 
whose missions was to launch satellites, including military satellites, and to use the Saturn V rock­
ets for Skylab. Of the Saturn V rockets, Apollo-18-Saturn Rocket used for Apollo 17 moon mission, 
Apollo-19-Saturn Rocket on display in Houston Space Flight Center, and Apollo-20-Saturn Rocket 
were never built. 
Why were the predictions about a continued space exploration at that time wrong? Could we 
have projected this retrenchment from moon and off-planet landings? Maybe. Was information on

have projected this retrenchment from moon and off-planet landings? Maybe. Was information on 
intent deducible? Yes, but a great deal was unavailable at that time. Could we have built a 2001 space 
station? Probably, if we started 30 years ago, but the will, at least funding, was unavailable. Very 
few scientists, maybe their wishful thinking, predicted the space retrenchment; maybe they were 
naive. Regardless of the public disappointment, future projections by a large part of the scientific 
community were wrong. We had beat the USSR to the moon; Vietnam and associated huge public 
military outlays were a factor, and maybe Nixon’s Watergate deflected attention away, but that fac­
tor is a bigger stretch since that occurred 1 to 2 years later. Conclusion, projections are difficult, 
but if all components, including political factors, can be accounted for, a closer approximation of 
future trends can be obtained.

future trends can be obtained. 
The purpose of this allegory was to illustrate that future projections, in this example space explora­
tion, are composed of many complex factors. Even if they are based on sound technological grounds, 
they do not always come to fruition. 
But that is not to say we should not try and project optimistic scenarios. We can improve our health-
care systems with access to all, beat disease, and improve longevity with the right combination of public 
an
d private support. Biomedical informatics (BMI) is at the forefront of healthcare and can influence 
the future of healthcare delivery. Dreams are the precursors of actions, the precursors of future utopias. 
12.2.1 Metrics 
In order to quantify the likelihood of any BMI trends, it is necessary to weigh the contributing factors

In order to quantify the likelihood of any BMI trends, it is necessary to weigh the contributing factors 
and generate a predictive score that represents the likelihood of adoption and integration of future BMI 
initiatives. 
Predictive analytics  is the practice of extracting information from existing data sets in order to deter­
mine patterns and predict future outcomes and trends. It  does not tell you what will happen in the 
future. It forecasts what might happen in the future with an acceptable level of reliability and includes 
what-if scenarios and risk assessment.* 
Predictive analytics mines data to predict trends. It is widely used in credit scoring to determine the 
future credit worthiness of individuals. It is a pattern of behavior and facts; that is, if that individual has  
paid his bills in the past, his job, income, and any criminal behavior are scored. In predictive analytics,

paid his bills in the past, his job, income, and any criminal behavior are scored. In predictive analytics,  
the term of an explanatory variable is used, as opposed to independent variable, where the variables may  
not be statistically independent . 
*  www.webopedia.com

325 Future Directions for Biomedical Informatics 
An independent variable (explanatory variable), in mathematics, is a variable whose value determines 
the value of other variables.* 
The dependent variable (response variable) is a variable in a functional relation whose value is deter­
mined by the values assumed by other variables in the relation. 
In psychology, the dependent variable is usually a measurement of some aspect of the participants’ 
behavior. The independent variable is called independent because it is free to be varied by the experi­
menter. The dependent variable is called dependent because it is thought to depend (at least in part) on 
the manipulations of the independent variable (Weiten, 2013). 
For example, the area of a circle is given by A = πr2. Here, the independent variable is r, since its value 
determines the area ( A). So the dependent variable is A. 
12.2.2 Biomedical Predictive Analytics

12.2.2 Biomedical Predictive Analytics 
Predicting any future technology or direction, especially for a particular discipline, has been an inex­
act science, no more than guesses. The goal of this section is to quantify predictive analytics for BMI. 
Similar results can be achieved for other disciplines by limiting the scope or independent variables and 
setting the limits of the nonlinear equations. Then combining these technological subsets into a unified 
field theory (UFT) of an entire field enhances the predictive accuracy (a lofty goal; in physics, UFT even 
eluded Einstein, but that too will eventually be realized). 
Metrics that focus on specific factors unique to a field of study, that is, in this case the field of BMI, 
and incorporating into the predictive equation factors such as government mandates, reimbursement

and incorporating into the predictive equation factors such as government mandates, reimbursement 
scales, user attitudes, and political support coefficients represented as probability coefficients, required 
HHS surveys HCAHPS that frame the scope of the predictive field will increase the accuracy of the pre­
diction. Additional factors that enhance BMI predictive analytics are implementation and upgrade costs  
of elec
tronic health records (EHRs), Health Information Technology for Economic and Clinical Health  
(HITECH) meaningful use criteria, etc. A metaphor for this approach would be predicting tree growth  
but starting at a particular branch and extrapolating growth patterns. The limbs and branches each have  
had contributing growth factors, and backtracking, we extrapolate future growth. Once each branch or  
subfield has been modeled, we can then backtrack and model the entire tree. 
The BMI predictive equation will incorporate (Lubliner, 2015)

The BMI predictive equation will incorporate (Lubliner, 2015) 
 1.  Predictive confidence factors (short, medium, long, and future-term coefficients) 
 2. Cost: predictive (factor) weights (implementing or not implementing new technology) 
 3. Government mandates (subsidies, penalties, meaningful use, and political factors) 
 4. Intangible costs (positive, negative, and confidence factors) 
The rate of acceptance of a new technology or trend depends on cost, external mandates such as govern­
ment regulations, and the will or wave of progress that moves technology to some degree of acceptance.  
Each of these factors is defined in the succeeding sections. 
12.2.2.1 Predictive Confidence Factors 
The predictive confidence factors (PCFs) are used to estimate the likelihood of an event occurring 
(Table 12.1). They are broken down into short-term predictions (in the next 5 years) that have a high prob­

ability of occurrence since they presuppose trends that are in the pipeline and extrapolate them to their 
*  http://www.sciencedictionary.com.

80 
78.4 
71.8 
60 
57.0 
40Percent EHR system 42.0 
48.3 51.0 
39.6 
48.1 
34.8 33.9 
20 
20.8 
23.9 
29.2 
21.8 
18.2 17.3 17.3 16.9 
10.5 11.8 
0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 
 
326 Biomedical Informatics 
TABLE 12.1 Predictive Confidence Factor Coefficients (Multiplied by the Prediction to Indicate Predictive 
Likelihood or Divergence from Estimates) 
Short Term: 5+ years (linear Medium Term: 10+ years Long Term: 20+ years Future: 40+ years (nonlinear 
3%/year) (linear 2%/year) (nonlinear ±3%/year) ±2%/year) 
ST = 85% MT = 70% LT = 20%–40% FT = 5%–20% 
PCF = [ST, MT, LT, FT] 
= [3%, 2%, ±3%, ±2%] 
logical conclusions. Taking that into consideration, we need probability factors to reflect the likelihood 
based on the distance (time) to the predicted event, multiplied by the overall prediction for short term 
(5+ years), medium term (10+ years), long term (20+ years), and future (40+ years). The long-term pre­

diction could be thought of as a nonlinear system “relating to a system of equations whose effects are 
not proportional to their causes.” Examples are conflicts between nations, biological outbreaks, or 
some technological breakthrough, where the response has effects that are not proportional to the scale. 
Imagine a cure for some types of cancers. Attempting to calculate or predict future events has to include 
nonlinear factors. The longer the period, the higher the probability of nonproportional causes that may 
skew predictions. 
The 3% rate for short- and medium-term trends was extrapolated from the January 2014 Center for 
Disease Control (CDC) report, indicating EHR adoption of 3.3% per year prior to the stimulus plan in 
2009, HITECH Act (Figure 12.2). A PCF has to be extrapolated for each field based on representative

2009, HITECH Act (Figure 12.2). A PCF has to be extrapolated for each field based on representative 
trend data. Data were available for both 5- and 10-year periods (the 5-year EHR rate from 2001 to 2006 
FIGURE 12.2 EHR implementation statistics as of January 2014. Notes: EHR is electronic health record. “Any 
EHR system” is a medical or health record system that is either all or partially electronic (excluding systems solely 
for billing). Data for 2001 to 2007 are from in-person National Ambulatory Medical Care Survey (NAMCS) inter­
views. Data for 2008 to 2010 are from combined files (in-person NAMCS and mail survey). Estimates for 2011–2013 
data are based on the mail survey only. Estimates for basic system prior to 2006 could not be computed because 
some items were not collected in the survey. Data include nonfederal, office-based physicians and exclude radi­
ologistis, anesthesiologists, and pathologists. (From CDC/NCHS, National Ambulatory Medical Care Survey and

ologistis, anesthesiologists, and pathologists. (From CDC/NCHS, National Ambulatory Medical Care Survey and 
National Ambulatory Medical Care Survey, Electronic Health Records Survey. CDC https://www.google.com/url?s ­
a=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&docid=-Wg5J-nGEhQ6nM&tbnid=ZL5cFGMGh 
YbfKM:&ved=0CAUQjRw&url=http%3A%2F%2Fwww.cdc.gov%2Fnchs%2Fdata%2Fdatabriefs%2Fdb143.htm&ei 
=RwaeU9iYNq7jsATUyYDYCw&bvm=bv.68911936,d.cWc&psig=AFQjCNErUDWAq0Ky5ZuQKfNXsFQCleaoeg 
&ust=1402951600266245.)

327 Future Directions for Biomedical Informatics 
was 2.2% per year, but there was an anomaly in 2002 and 2003 that skewed growth negative. Adjusting 
5- and 10-year growth to 3% seems justifiable). After that in 2010, adoption doubled to 6.85%, the year 
after government mandates and cost sharing were contributing cost factors . These will be factored in 
Section 12.2.2.2. Nonlinear growth factors are based on external factors accelerating or decelerating 
predictive trends that have to be continuously recalculated for predictive accuracy. In this case, not only 
a stimulus plan that subsidized cost, but also government mandates, technological advancements, and 
the percentage increase in certain age populations (baby boomers) have changed the shape of the growth 
curve (Figure 12.2). 
12.2.2.2 Cost Factors (Predictive Weights) 
Predictive cost factors are broken down into several subfactors: cost of implementing new technologies,

Predictive cost factors are broken down into several subfactors: cost of implementing new technologies, 
cost of lack of efficiency by not implementing a technology, and the intangible cost appearing to be falling 
behind the state of the art in that field (Table 12.2). This last factor, intangible costs, is a complex, nonlinear 
factor. If patients go to a hospital and find no EHRs, digital scheduling boards, Wi-Fi connectivity, or state­
of-the-art technology, they may have a negative impression of the quality of the medical services. 
The Health and Human Services (HHS) center for Medicare and Medicaid embeds the Hospital 
Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey under its Inpatient 
Prospective Payment System (IPPS) as one of the determining factors for reimbursement. Since patient 
satisfaction scores are required by HHS and penalties are assessed at 1%, 2%, and 3% per year progres­

sively, they should be factored into cost predictions. 
12.2.2.3  External Mandates 
External mandates are government regulations and penalties that clearly rate high on any calculations 
to predict implementing technologies. These can take many forms: positive subsidies by government to 
offset costs, in particular the HITECH Act as part of the 2009 Stimulus Bill allocating $19.7 billion to 
help hospitals and physicians; penalties, where any Medicare or Medicaid bill, starting in 2015, will be 
reimbursed at a lower rate progressively, without electronic submission by physicians, not all medical 
practitioners as of 2015, or Hospital EHRs will incur a progressive 1%, 2%, and 3% penalty per year if bills 
are not submitted electronically. The meaningful use guidelines determine the integration level of the

are not submitted electronically. The meaningful use guidelines determine the integration level of the 
EHRs (Chapters 3 and 4). The last factor, political factors , influences funding levels. This is not a politi­
cal statement, just an assessment of the role funding levels play in future predictions of BMI initiatives. 
Party A, as of 2014, voted 50+ times to repeal/replace the Affordable Care Act (ACA) (Obama Care) and 
did not support HITECH support to subsidize EHR implementation. Party B passed funding EHRs and 
the ACA and voted to increase funding in these areas. There are three values: a political party supportive 
TABLE 12.2 Cost Factors, Predictive Weights 
Implementing new technology (Cimp) Not implementing new technology Intangible costs 
Hardware and software outlays (CNimp) Hospital Consumer Assessment of  Cimp = Avg.( (net profits/year (s)) Tyr = Revenues this year ex $150M Healthcare Providers and Systems 
Example (HCAHPS) Lyr = Revenues last year ex $175M

Example (HCAHPS) Lyr = Revenues last year ex $175M 
$10 million (EHR Hosp .) ΔABS [ avg. ( revenues/years)] Penalties 1%, 2%, and 3% (negative  0 . 067   Cimp CNimp = $150 million net profit Avg.(net profits / year(s)) values) 
The average depends on length of  (publicly reported by HHS) $175M − $15 0M
projection; ST (2–4 years), MT CNimp = = 0.166 $15 0 M
(5 years), etc. Reduction in reimbursement 1%, 2%, 
and 3% after 2015 
If Cimp is below 10% (0.1) and This is a multiyear calculation This is a patient satisfactory score 
reimbursement probability >90%, If revenues have decreased for that affects Medicare and Medicaid 
Cimp is not a factor. multiple years, one factor could be 
 reimbursement. 
patient confidence. Should be
  Hospitals must have 300+ completed 
correlated with HCAHPS score.
 surveys/year.

Intangible Costs (IC) (Positive or Negative Attitudes toward Biomedical Informatics Technologies Effecting Future 
Adoption) 
Positive (individual events) i.e., Negative (individual events) Confidence level (overall) 
doctor, a procedure, etc. 
ICp confidence level from (0–0.9) ICn same scale -ve(0–0.9) ICo scale (0–1.0) 
(09. high confidence) A ICp=0.5 and ICn -0.5 cancel each other This is an overall confidence of medicine 
1.0 w
ould be absolute certainly 	 (i.e., no net effect) related to doctor(s), pharmaceuticals 
almost impossible to attain research, etc. 
 
Mandates: Government or Professional 
(Negative Value Disproportionally 
(Relationship to Future Biomedical Informatics Predictions) Affects BMI Predictions) 
Subsidies Penalties Meaningful use (ranking Political factors 
-HITECH subsides through 1%, 2%, and 3% the implementation -Party supports healthcare (+1.0) 
end of 2015 value (1.0) reduction in quality) -Party negative support (-1.0) (affect

end of 2015 value (1.0) reduction in quality) -Party negative support (-1.0) (affect 
-After 2015 value (0.5) 50% Medicare and Level 7=(1.0), Level 6 BMI funding levels) 
future probability funding Medicaid (0.9) -Split congress (0.5) (funding could go 
reimbursement Level 1=(0.3), no either way) 
after 2015 MU=(0.0) 
MSi [1.0, 0.5] MPi [0.1,.2,.3] MUi [1,.9,.8..7………0.0] MPOLi [1.0, 0.5, −1.0] 
328 Biomedical Informatics 
TABLE 12.3 BMI Prediction Calculation Factoring in Mandates 
TABLE 12.4 Intangible Factors 
of BMI (value 1.0); a spilt congress (value 0.5), in which case funding could go either way; and negative 
support (value −1.0). A negative mandate, no matter how compelling the scientific data, for example, cli­
mate change with a more than 98% global scientific community consensus, will influence funding and 
skew predictions accordingly. This may change in the future, and these coefficients should be adjusted 
accordingly (Table 12.3). 
12.2.2.4 Intangible Costs

12.2.2.4 Intangible Costs 
Intangible costs are the most difficult to assess. If patients/customers believe that a business or profes­
sion is not at an acceptable level of technology integration, they will be less confident of the skill level of 
the practitioners. Extreme examples might be a phone store selling flip phones or an electronics store 
selling cathode ray tube televisions or a doctor’s office using a typewriter. As soon as you see stacks of 
paper records rather than EHRs, you predict that the physicians are not aware of the latest medical 
technologies (Table 12.4). 
12.3 HCAHPS Score 
A key metric is the HCAHPS survey of 21 questions measuring patient satisfaction required by the HHS, 
which will be publicly available and factored into Medicare and Medicaid reimbursement. The first public 
reporting of HCAHPS results in March 2008 included 2,521 hospitals and 1.1 million completed surveys;

reporting of HCAHPS results in March 2008 included 2,521 hospitals and 1.1 million completed surveys; 
the Spring 2012 public reporting entailed 3,851 hospitals and 2.8 million completed surveys. Summary 
analyses of HCAHPS scores are available on the HCAHPS website www.hcahpsonline.org (Table 12.5). 
The intent of the HCAHPS initiative is “to provide a standardized survey instrument and data-
collection methodology for measuring patients’ perspectives on hospital care. HCAHPS survey

HCAHPS Cover Nine Topic Areas 
1 Communication with doctors 
2 Communication with nurses 
3 Responsiveness of hospital staff 
4 Pain management 
5 Communication about medicines 
6 Discharge information 
7 Cleanliness of the hospital environment 
8 Quietness of the hospital environment 
9 Transition of care 
New Overall rating of hospital 
329 Future Directions for Biomedical Informatics 
TABLE 12.5 HCAHAPS Patient Survey Categories 
items complement the data hospitals currently collect to support improvements in internal cus­
tomer services and quality related activities.”* 
The Hospital Value-Based Purchasing (VBP) Program is an initiative of the Centers for Medicare and 
Medicaid Services (CMS) that rewards acute care hospitals with incentive payments for the quality of 
care they provide to people with Medicare. 
The Hospital VBP Program was established by the 2010 ACA, which added Section 1886(o) to the

The Hospital VBP Program was established by the 2010 ACA, which added Section 1886(o) to the 
Social Security Act. The law requires the Secretary of the Department of HHS to establish a VBP 
program for inpatient hospitals. To improve quality, the ACA builds on earlier legislation—the 2003  
Me
dicare Prescription Drug, Improvement, and Modernization Act and the 2005 Deficit Reduction Act. 
These earlier laws established a way for Medicare to pay hospitals for reporting on quality measures, a 
necessary step in the process of paying for quality rather than quantity.
† 
Penalties‡: 
• 	 The  Hospital Readmission Reduction Program imposes financial penalties on hospitals for 
“excess” readmissions compared to “expected” levels of readmissions. The penalty program began 
on October 1, 2012. The initial payment penalties are based on the 30-day readmission measures

on October 1, 2012. The initial payment penalties are based on the 30-day readmission measures 
for heart attack, heart failure, and pneumonia that are currently part of the Medicare IQR. 
• 	 Reduce hospital base Medicare payments by up to 1% in FY 2013. 
• 	 The potential penalty increases to 2% of base payments in FY 2014. 
• 	 Three percent in FY 2015 and beyond. 
The HHS center for Medicare and Medicaid embeds the HCAHPS survey under its IPPS as one of 
the determining factors for reimbursement. The complete title of the program is “Hospital Inpatient 
Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective 
Payment System; Quality Reporting Requirements for Specific Providers; Hospital Conditions of 
Participation; Payment Policies Related to Patient Status.”
§ 
HHS requires that as part of its IPPS, the HCAHPS survey, hospitals must survey patients through­

§ 
out each month of the year, and IPPS hospitals must achieve at least 300 completed surveys over four 
calendar quarters. HCAHPS is available in official English, Spanish, Chinese, Russian, and Vietnamese 
*  http://www.hcahpsonline.org/home.aspx. 
†  http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/ 
Downloads/FY-2013-Program-Frequently-Asked-Questions-about-Hospital-VBP-3-9-12.pdf. 
‡ AHA.org. 
§ http://www.gpo.gov/fdsys/pkg/FR-2013–08–19/pdf/2013–18956.pdf.

330 Biomedical Informatics 
versions.  HCAHPS Quality Assurance Guidelines Manual  is available on the official HCAHPS website. 
Ten HCAHPS measures (six summary measures, two individual items, and two global items) are pub­
licly reported on the Hospital Compare website * for each participating hospital. 
HCAHPS Scoring† 
 1.  Hospital VBP utilizes HCAHPS scores from two time periods: a baseline and a performance 
period. For FY 2013, the baseline period covers patients discharged from July 1, 2009, through 
March 31, 2010, and the performance period from July 1, 2011, through March 31, 2012. 
 2. The Patient Experience of Care Domain Score has two parts: the HCAHPS Base Score (maximum 
of 80 points) and the HCAHPS Consistency Points Score (maximum of 20 points). 
 3.	  The second part of the Patient Experience of Care Domain is the Consistency Points Score, which  
ranges from 0 to 20 points. Consistency Points are designed to target and further incentivize

ranges from 0 to 20 points. Consistency Points are designed to target and further incentivize 
improvement in a hospital’s lowest-performing HCAHPS dimension. 
 4. The Patient Experience of Care Domain Score is the sum of the HCAHPS Base Score (0–80 points) 
and HCAHPS Consistency Points Score (0–20 points), which ranges from 0 to 100 points and 
comprises 30% of the Hospital VBP Total Performance Score. 
12.4 Center for Disease Control Data (Trends) 
The CDC reported in January 2014 (Figure 12.2) ‡ 
• 78% of office physicians had some form of basic EHR system (CDC data Table 12.2) 
• 	 From 2001, where it stood at 18%, to 2010, where it was 51% 
– 51%–18% = 33% increase or 3.3% per year imp rate prior to stimulus incentives 
• 	 From 51% in 2010 to 78.4% in 2013 
– 78.4–51 = 27.4% increase or 6.85% per year, doubled due to stimulus plan 
12.5 Future  Scenarios 
The following are future BMI scenarios divided into several categories and time frames. They will be

The following are future BMI scenarios divided into several categories and time frames. They will be 
rated by time period (short, medium, long, and future); technological difficulty (easy, medium, and dif­
ficult); and the likelihood of occurring (low, medium, and high) in the indicated time frame and factors 
that may contribute positively or negatively. The scenarios proposed were chosen because they appear  
to be technologically feasible, following current trends; but feasibility can be trumped by other external 
forces. Each scenario will include a table entry summarizing parameters and predictions. 
12.5.1 Scenario  1 
Hypothesis: In the next five years, 95% of all medical documentation will be integrated and online; EHRs  
are just one of many components (Table 12.6). 
Discussion 
Data: As of 2013, the CDC data indicated that 78% of physicians use some form of EHR. Government

Data: As of 2013, the CDC data indicated that 78% of physicians use some form of EHR. Government 
mandates require EHRs by hospitals and physicians at the end of 2015 and subsequent penalties in  
Medicare and Medicaid reimbursement. By 2015, about 95% of physicians and hospitals will use EHRs. 
But what about dentists, optometrists, etc.? 
* www.hospitalcompare.hhs.gov. 
† http://www.hcahpsonline.org/files/HCAHPS%20Fact%20Sheet%20May%202012.pdf. 
‡ http://www.himss.org/News/NewsDetail.aspx?ItemNumber=27596.

Parameters Time Period (Y ears) Technological Difficulty Likelihood of Occurring 
[ST, MT, LT, future] [easy, medium, difficult] [low, medium, high, very high] 
[5, 10, 20, 40+] [1, 2, 3] [<25%, 50%, 75%, 90+] 
Predicted  outcomes Short term (5 years) (2015–19) -Hospitals and physicians 1 -Very high 90%+ 
-Dentists, optometrists, -Medium 50% 
etc. 2 
331 Future Directions for Biomedical Informatics 
TABLE 12.6 Scenario 1 
• 	 By mid-2014, dentists do not have the regulatory requirements to convert to electronic dental 
records (EDRs). 
• 	 Minnesota is the only state that requires dentists to implement EHRs by the end of 2014, but there 
are currently no penalties.* 
• 	 Approximately 50% of dentists use digital x-rays as of June 2014. 
• 	 Electronic Dental Records (EDRs) have not yet reached the level of EHRs, and in general have not 
met the Health Insurance Portability and Accountability Act (HIPAA) and HITECH meaningful  
use criteria with associated supporting forms, labs, etc.

use criteria with associated supporting forms, labs, etc. 
•	  EDR pressures include 
– 	 Safer record keeping during disaster recovery 
– 	 Pressures from insurance companies to submit claims digitally 
– 	 Drug interactions with other treatments 
– 	 Linkages between dental disease and certain illnesses such as heart disease 
– 	 Individual requests for copies of their dental records (currently physicians are required  
by HIPAA to supply copies of medical records) 
• 	 American Dental Association (ADA)
†: 
• 	 ADA advice on the EHR incentive program  (May 2013): “Theoretically, all dentists are eli­
gible for both the Medicare and Medicaid EHR incentive programs since dentists were  
included in the provider categories established by the federal EHR incentive program stat­
utes. Practically speaking, since Medicare pays for very little dental work the dentist’s eli­
gibility would depend on his/her work through the Medicaid program run by each state  
individually.”

individually.” 
• 	 The ADA has been working, since 2007, on Systemized Nomenclature of Dentistry (SNODENT) 
to standardize terminology in the dental field, similar to SNOMED (see  Chapter 4)
‡ 
• 	 To provide standardized terms for describing dental disease 
• 	 To capture clinical detail and patient characteristics 
• 	 To permit analysis of patient care services and outcomes 
• 	 To be interoperable with EHRs and EDRs 
mmary (Analysis) 
e HHS mandates require all hospitals and physicians to convert to EHRs by 2015 or receive reim­
rsement penalties from Medicare and Medicaid if bills and data are not electronically submitted. 
e 2009 Stimulus Bill provided funding to help defray implementation cost not only for hospitals and 
ysicians but other medical practitioners, including dentists, which will expire by 2015.

ysicians but other medical practitioners, including dentists, which will expire by 2015. 
This combination of carrot and stick will ensure hospitals and physicians reach the 95%+ EHR 
plementation goal in the next 5  years. But additional funding beyond 2015 is not guaranteed. 
litical uncertainties in the next few elections will have a great deal of impact on EHR expansion for 
ttp://www.ihealthbeat.org/articles/2013/7/25/minnesota-requires-dental-care-providers-to-implement-ehrs. 
ttp://www.ada.org/en/member-center/member-benefits/practice-resources/dental-informatics/electronic-health-records. 
ttp://www.ada.org/en/member-center/member-benefits/practice-resources/dental-informatics/snodent. 
Su
Th
bu
Th
ph
im
P
o
* h
† h
‡ h

Predicted outcome Short-medium (5–10 years) (2014–2023) -Hospitals and ph ysicians 1 - V
ery high 90%+ 
-Wireless medical devices 1 -Medium 90+% 
   
332 Biomedical Informatics 
TABLE 12.7 Scenario 2 
all other medical practitioners. Other medical specialties such as dentists, optometrists, mental health-
care workers, etc., are estimated to be no better than 50/50 overall (physicians+dentists + other medical 
practitioners) whether they meet that 95%+ goal in the next 5 years. 
12.5.2 Scenario 2 
Hypothesis: In 5 to 10 years, all medical devices will automatically update EHRs directly. This will not 
only be in hospitals but will include wearable wireless medical devices (Table 12.7). 
Discussion

In hospitals, this trend has already begun. Entering data by nurses is a tedious and time-consuming 
endeavor and prone to error. The primary factor is initial cost, upgrading EHRs and equipment, these 
minor impediments can be offset by the time saved by nurses and more accurate readings and seems to 
be a likely bet of occurring. 
Nonhospital medical devices, that is, wireless wearable medical devices, equipment in physicians’ 
offices, etc., will also have the ability to wirelessly update medical records. Data records may be kept 
by individuals, but this data will be accessible by physicians for a more longitudinal view of patients. 
Also at-home monitoring of critically ill patients will reduce hospital stays. This also seems highly likely 
especially for preventive care mandated in the 2010 ACA, Obama Care. 
Summary

Summary 
EHRs’ aim is to provide a complete view of patient health data. Since most of this data are more relevant 
in everyday venues, not having this incorporated in EHRs seems counterproductive. So there is a high 
likelihood of automatic EHR integration. 
12.5.3 Scenario 3 
Hypothesis: EHR(2), defined as the next evolution in user interfaces and distributed healthcare. In the 
next 5 years, EHR user interfaces will be easily customizable to reflect the needs of each medical practitio­
ner with little need for drop down menus and designed to reflect current phone and tablet user interfaces 
(Table 12.8). 
If current generation of EHRs follows past evolutionary designs, such as the Microsoft Office Suite or 
Windows 7-8 operating systems. Newer user interfaces Windows 10 and touch screen phones and tablets 
TABLE 12.8 Scenario 3

TABLE 12.8 Scenario 3 
Predicted outcome Short term (5 years) (2014–2018) -Hospitals and physicians 1 -Very high 75%+ 
-Dentists, optometrists, etc. 2 -Very high 75% 
-EHR(2) -Very high 50%–75%

333 Future Directions for Biomedical Informatics 
will have intuitive user interfaces, either selecting an icon or gestures to expand the items with some 
series of gestures, etc. 
A reasonable percentage of physicians access EHRs through their portable devices and some hospital 
staff also use tablets. The pressure to make screens more user friendly, enhancing efficiency, and leaving 
more time for medical care, as opposed to data entry, would seem to support EHR(2), the next evolution 
in EHR design. Predictive level is very high—75% for scenario 3. 
12.5.4 Scenario 4 
Hypothesis: Long term  (20+ years) distributed healthcare : Medical care will evolve beyond our current 
location-based, hospital–physician office centric system. Wireless medical devices will be worn, or in 
more acute situations, pacemakers, defibrillators, cancer care, etc. devices will be implanted and con­
nected wirelessly. Pill dispensers, as will most of devices, will be intelligently connected to the Cloud,

nected wirelessly. Pill dispensers, as will most of devices, will be intelligently connected to the Cloud, 
to close the  healthcare loop. Telemedicine be ubiquitous, communicating with either live or simulated 
health advisers. Proactive care will change the face of healthcare and reduce costs dramatically, since 
outpatient care is significantly less expensive (Table 12.9). 
The forces leading to a more distributed healthcare system are considerable. Hospitals are closing 
and being replaced by ambulatory emergency departments. Coverage for in-hospital stays is being 
reduced. Outpatient medical centers, both acute and nonacute, such as minute clinics are proliferat­
ing. Online apps that allow medical practitioners with Skype-like video interactions are already here. 
New certifications such as CCRN-E allow critical nurses to monitor patients in rural ICUs. Virtually 
everyone already has Smart phones and tablets that are increasing in capability; the computing power

everyone already has Smart phones and tablets that are increasing in capability; the computing power 
of Smart phones is comparable to PCs. In the near future, medical kiosks in malls and public spaces 
will allow the equivalent of a medical checkup in minutes automatically linked to EHRs and medical 
practitioners will immediately be notified to triage acute situations, possibly even to dispense drugs, 
with a wearable injection or patch. The systems may be able to detect pre-heart attack symptoms and 
dispense blood thinners connected to an eDoctor with embedded intelligence. 
A new medical paradigm has to be designed as a real-time feedback system that integrates healthcare 
with the next generation of EHRs and real-time wireless medical equipment and communications. 
Summary 
All the factors leading to a distributed healthcare paradigm and EHR(2) seem inevitable. The tech­
nology is there, which will reduce the cost involved in outpatient care and facilities and will, in some

nology is there, which will reduce the cost involved in outpatient care and facilities and will, in some 
respect, promote more personalized care through in-home doctor visits on demand through phone or 
tablet. Proactive healthcare with new wearable medical monitoring devices worn or through phones has 
already begun to appear. The only question is the speed at which this integrated system will be com­
monplace. The prediction is well above 50% in the next 20 years and even sooner. 
TABLE 12.9 Scenario 4 Statistics 
Predicted outcome Long term (20+ years) (2014–2033) -Distributed healthcare -Medium 50%+ 
-Intelligently web-based -Medium 50+% 

Predicted  outcome Long term (40+ years) (2014–2053) -eDoctor  2 -Medium 25%–50%+ 
-Intelligent kiosks 2 -Medium 25–50+% 
334 Biomedical Informatics 
TABLE 12.10 Scenario 5 Statistics 
12.5.5 Scenario 5 
Hypothesis: eDoctor and intelligent medical kiosks  that can diagnose and dispense drugs in the next 
40 years (future), all linked to a global EHR network—EHR(3) (Table 12.10). 
We are moving toward intelligent self-driving cars. As of 2014, Google has prototypes that have driven 
over a million miles without an accident. There have been a few accidents, but currently with 50,000 
driving deaths a year and hundreds of thousands of injuries and medical and repair costs into hundreds

driving deaths a year and hundreds of thousands of injuries and medical and repair costs into hundreds 
of billions a year, this would be a vast improvement. At the very least, the current cars that automatically 
stop before hitting the car in front will be commonplace shortly. 
In 2014, the CDC reported that 600,000 people died of heart diseases per year in the United States. 
The cost is $108.9 billion annually.* H eart disease constitutes one in four deaths per year. There are 
725,000 heart attacks each year, of which 525,000 are first heart attacks, and 92% first noticed chest pain 
as a symptom. Imagine if this happened in some public area or at work. A patient could walk to an intel­
ligent kiosk or device; all public places could be mandated to have one, similar to defibrillators for air­
planes. The device will do a quick diagnosis, and using its own software, eDoctor, or after an e-consult

planes. The device will do a quick diagnosis, and using its own software, eDoctor, or after an e-consult 
with an online doctor, will dispense an antiplatelet medication to prevent the formation of blood clots in 
the arteries. This could be true for asthma, allergic reactions, etc. If there were a predisposition to allergy 
or heart attack, it could be embedded into a wrist watch to dispense a life-saving drug. Wrist bands 
could also be available to dispense drugs while in sleep for individuals with a history of heart attacks. 
Intelligent medical kiosks are similar. As computing speed and sensors increase, walking slowly 
through the entrance could generate a quick medical diagnostic evaluation. The third-generation 
EHR(3) would have a virtual doctor that could interact and recommend treatments and, by having 
your EHRs, could tell you to eat your vegetables, stop smoking, and more realistically monitor your

your EHRs, could tell you to eat your vegetables, stop smoking, and more realistically monitor your 
exercise, possibly turning off the computer or TV until you complete your exercise regimen. 
Summary 
In 40+ years, it will be technologically feasible and could be incorporated into healthcare costs. EHR(3) 
and intelligent kiosks are feasible, but possible intrusion into people’s lives might be a factor that can 
prevent adoption. It has a probability of 25% to 50%. 
Level II: BMI Predictive Analytics Applied 
12.6  Case Study: Scenario 1
 
The following calculates all factors in scenario 1 (utilizing predictive analytics equations ) 
Prediction: In the next 5 years, all (95%+) medical disciplines will ubiquitously incorporate EHRs. 
• 	 Predictive  factors: 
• 	 Cost: Reimbursement by Medicare, Medicaid, and prescriptions has mandated that after 
2015, progressively 1%, 2%, and 3% will be subtracted from reimbursement if claims are not 
submitted electronically.

submitted electronically. 
*  http://www.cdc.gov/heartdisease/facts.htm.

a. Cimp (cost of implementing new technology in physicians, office) 100,000 (software + hardware) 
cost 1,000,000 net income 
hospital =.1 
2014, 2015 0.9 90% cost covered by Stimulus plan 
2016, 2017, 2018 0.5 Unclear 50/50 probability of 
Avg. 0.7 subsidized cost. New funding bills 
b. CNimp (cost not implementing new technology) 
0.2% avg P enalties: 1% 2016, 2% 2017, 3% 2018 
c. HCAHPS assume initial 10% impact 
Results 
Cimp (0.7 factor × 0.1 EHR 
compliance) 
=(0.7 × 0.1) 
=0.07 
+ 0.2 (10% noncompliance by 2016; 
(i.e. CDC graph estimates 90% EHR 
implemented) 
+0% HCAHPS 
+(0.2 × 0.1) +0.0 
+.02 +0.0 
=0.09 Means in 9% of physicians 2014–2019 cost may be an 
implementation issue 
Cost of implementation an issue for Adopting EHR (physicians) 
(Only after 2016 when funding stops) 
0.09 or 9% of physicians EHR implementation costs will be an issue (with 
CDC implementation curve 90% will have completed implementation, so 
this only affects remaining 10%) 
Dependent on

Dependent on 
increase Funding 
after 2015 
BMI Predictive Analysis .85[CInt+Cnint+HCAPHPS)+(Mandates)+(Intangible costs)] 
=0.85[0.09+(Mandated) + (Intangible costs)] 
 
335 Future Directions for Biomedical Informatics 
• 	 Probability high. 
• 	 Contributing factors: 
• 	 Cost of transitioning to EHRs will decrease. 
• 	 This is a short-term prediction, occurring in the next 5 years, which usually has a high probability 
of occurrence since it presupposes trends that are in the pipeline and extrapolating to their logical 
conclusions. 
12.6.1 BMI Predictive Equation Example 
BMI Predictive Analysis: 2014–2019 
1. Predictive Confidence Factor (PCF)
 i.	 Scenario A: PCF, Short Term = 0.3% 
0.3% × 5 Years = 15%, implies starting with 85% probability prediction is accurate 
12.6.2 Cost Factors 
2. Predictive Cost Factors 
12.6.3 Mandate Factors

12.6.3 Mandate Factors 
3. Mandates: (Table 12.11) 
1.	 MSi (mandate compliance) 
from 2014 to 2019 (first 2 years reimbursement covered, last few years uncertain avg. value 
=(1.0 +.5 probability)/5 years 
=(1.0,1.0,0.5,0.5,0.5)/5= 3.5/5=0.7 
2. 	 MPi (penalty): 1%, 2%, 3% reimbursement penalties for Medicare and Medicaid patients 
penalties for noncompliance start at end of 2015

(Negative Value 
Disproportionally Affects BMI 
(Relationship to Future Biomedical Informatics Predictions) Predictions) 
Subsidies Penalties Meaningful use (MU) Political factors 
(ranking the 
implementation quality) 
-HITECH subsides through 1%, 2%, and 3% reduction Level 7=(1.0), Level 6 (0.9) -Party supports healthcare (+1.0) 
end of 2015 value (1.0) in Medicare and 
-After 2015 val
ue (0.5) 50% Medicaid reimbursement Level 1=(0.3), no -Party negative support (−1.0) 
future prob. funding after 2015 MU=(0.0) (affect BMI funding levels) 
Percentage have met MU -Split congress (0.5) (funding 
could go either way) 
MSi  [1.0, 0.5] =0.7 MPi MUi  [1,.9,.8..7………0.0] MPOLi [1.0, 0.5, -1.0] 0.7 
=−0.112 0.815 
336 Biomedical Informatics 
TABLE 12.11 BMI Mandates 
3. 	 2014 to 2019 
When penalties start in 2016, the remaining outliers (no EHRs) will feel financial pres­

sure to implement systems. EHR implementation (2014 = 78 + 3% = 81%, 2015 = 84%, 2016 
= 87%, 2017 = 90%, 2018 = 93%) 
(100–81 = 19%, 100–84 = 16%, 13%, 10%, 7%) = 0.19 + 0.16 + 0.13 + 0.10 + 0.07)/5 
= − 0.112 
4. 	 MUi (meaningful use) 
This is more difficult since there are seven levels of achievement and reimbursement per­
centages based on compliance levels that are in flux. Estimate in ( compliant 1.0, partial 
0.5, none −0.5) this last term reflects 5% do not implement EHR’s, 
currently 78% have implemented EHRs (CDC data), and 22% remaining. If we predict 
95% EHR compliance, 95%–78% = 17%. 
At an annual implementation rate of (3%–6.8%) per year, approximately avg. 5.0% 
= (1 × 0.78) + (0.5 × 0.17) − (0.5 × 5%) = 0.78 + 0.085 − 0.025 = 0.815 
(the political climate has an important effect on future funding)

(the political climate has an important effect on future funding) 
5. From 2014 to 2016 president supportive of healthcare 1.0 in 2017, 2018 support could go either 
way 0.5 (1,1,0.5,0.5,0.5) per 5 years = 3.5/5 = 0.8 
The factors are multiplied by MPOLi since positive or negative support will determine 
funding or passing future initiates. 
0.85 [0.09 + (Mandates) + (Intangible costs)] 
0.85 [0.09 + ([0.7 + 0.12) × 0.815] × 0.7) + intangible costs] 
0.85 [0.09 + (.66178) × 0.7) + intangible costs] 
0.85 0.09 + .463246 + intangible costs] + intangible costs] 
MPA = 0.85[.553246 + Intangible costs] 
12.6.4  Intangible Cost Factors
 4.  Intangible  costs
 i.  ICp  (positive effects) (using 0.9 confidence level, best case, for EHR adoption) 
 1. focusing on EHRs = (current EHRs 0.78 × 0.9) = 0. 702
 ii.  ICn (negative effects) (22% remaining (where 17% have upgraded 95% prediction
 1. =(0.17 × 0.9) = 0.153 
)

iii. 	 ICo (confidence level) this is difficult to assess, but in the United States, we have, as of 2013, 143 
million Smart phones, which is about 45% of population. Let us assume 5% growth per year  
(2014–19). Overall confidence implies public support, which can influence public policies and 
future funding levels
 1.  (0.45,0.5,0.55,0.60,0.65)/5  years  =0.55 
Caveat: If all the mandated factors indicated an absolute certainty of occurrence, that is, guaranteed future  
EHR funding, all users met optimum meaningful use goals, level 7, and political support was certain, the val­
ues could reach a probability exceeding 100%. These probability estimates generate reasonable results by bal­
ancing factors that represent historical results. Prior efforts by political parties for 50  years to pass healthcare  
reforms were without success. It is reasonable to assume there will be bumps in the road. Including factors

reforms were without success. It is reasonable to assume there will be bumps in the road. Including factors  
that represent these historical norms may be more predictive of future realities (Table 12.12). 
= 0.85[.553246 + (0.702 – 0.1530) × 0.55] 
= 0.85[.553246 + (0.552) × 0.55] 
= 0.85[.553246 + 0.3036] 
= 0.85[0.856846] 
= 0.7283191 approximately 73% 
Prediction there is a 73% probability that 95% of all medical staff will have EHRs in 5 years. 
12.6.5 Analysis of Results 
At the start of this 5-year prediction, dentists, optometrists, dermatologists, mental healthcare work­
ers, etc. are not required by law to implement EHRs and there is no government funding allocated for  
this purpose post-2015. There are pressures that will push medical practices in this direction, but this  
final group may move slower and take longer to implement EHRs saturation at the 95+% level. 
Alternate Scenario:

Alternate Scenario: 
If the political factors supported additional funding for EHR implementation through 2019, altering the 
MPOLi factors to (1: high probability of political support) for all 5 years, this would increase the predic­
337 Future Directions for Biomedical Informatics 
TABLE 12.12 BMI Mandates 
Intangible Costs (IC) (Positive Or Negative Attitudes toward Biomedical Informatics Technologies Affecting Future Adoption) 
Positive (individual events) i.e., doctor, a Negative (individual events) Confidence level (Overall) 
procedure, etc. 
ICp confidence level from (0–0.9) (09. high ICn same scale -ve(0–0.9) ICo scale (0–1.0) 
confidence) A ICp=0.5 and ICn -0.5 cancel each This is an overall confidence of 
1.0 would be absolute certainly almost impossible other (i.e., no net effect) medicine related to doctor(s), 
to attain 0.153 pharmaceuticals research, etc. 
=0.702 0.55 
tiv

tiv
e probability significantly, increasing the probability to 90% (Table 12.13). 
TABLE 12.13 Altering Factors to Analyze Effect on Predictive Equations 
Change Factors MPOLi (Implies Higher Probability of Expanded EHR Funder beyond 2015) 
Original MPA= New factors: 0.5 is 1.0 (for 2016 – 2019)
 
MPOLi (1,1,0.5,0.5,0.5)/5 = 0.7 MPOLi (1,1,1,1,1)/5 = 1.0
 
= 0.85[0.09 + (0.66178) × 0.7 + 0.856846] = 0.85[0.09 + (0.66178) × 1.0 + 0.3036]
 
= 0.85[0.856846] = 0.85[1.05538]
 
= 0.7283191 = 0.8970
 
Probability approximately 73% Probability approximately 90%

338 Biomedical Informatics 
Level III: The Future of Biomedical Informatics
 
12.7 BMI Predictions
 
Where do we go from here, creating meaning out of chaos ? In the second decade of the twenty-first cen­
tury, we have already linked the planet into an integrated web that allows us to communicate virtually 
instantly. These early generations of Smart phones and tablets provide a glimpse of what is possible with  
intuitive user interfaces. We are poised at the threshold of the next evolutionary step. 
In the next decade, technology will provide true symbiotic interaction between users and technology. 
Embedded sensors will provide real-time data to be collected in every sphere of science. The troika of 
computers, sensors, and intelligent energy monitors will reduce per capita energy usage and change the 
trajectory of our civilization. The only caveat is the unexpected: war, disease, religious strife, and maybe 
extraterrestrials, benevolent ones.

extraterrestrials, benevolent ones. 
• 	 In meteorology, satellites and ground-based sensors on land and in the oceans, with more accu­
rate simulation software, will provide ever more detailed weather and climate projections. 
• 	In transportation, sensors embedded in vehicles, roadways, and intelligent drones will  
dynamically adjust traffic patterns. Intelligent vehicles will reduce accidents, allow for  
smaller lighter vehicles, and immediately dispatch repair vehicles. Smaller lighter vehicles  
will also reduce overall energy consumption. The rate of 50,000 vehicle deaths per year may  
be reduced dramatically. 
• 	 More efficient intelligent buildings will reduce energy consumption. In 2012, about 461  
billion kWh of electricity was used for lighting by the residential and commercial sectors.

billion kWh of electricity was used for lighting by the residential and commercial sectors.  
This was about 17% of the total electricity consumed by both these sectors and about 12% of  
total US electricity consumption.* Energy-efficient light bulbs use approximately 75% less  
energy than older light bulbs, so these energy consumption percentages will drop.
† An exam­
ple of a technology changing energy consumption is the intelligent web-controlled NEST  
Thermostat, which learns your personal patterns. As of 2013, it is estimated to have saved 30%  
of heating costs per year (https://community.nest.com/thread/1021). This trend of intelligent  
sensors will accelerate. 
12.7.1 Five Years: Intelligent Data 
These evolutionary technologies will also alter the face of healthcare. In the next 5  years, medical 
sensors will be ubiquitously embedded in all our devices, Smart phones, clothing, jewelry, etc., wire­

lessly linked through a newer more intelligent EHR. We may have to create a new term that represents  
real-time wireless integration of medical data linked into data accumulated in our daily lives, maybe a 
“LIFE record ” (LIFEr). More than medical data will be accumulated; video clips, dietary choices, daily 
itineraries, website and reading preferences, medical records, etc. All these devices will be tied together 
with a personal digital assistant that learns your patterns and predicts your needs. For example, when 
you open your smart device, only news articles in your area of interest will be displayed first. Traffic  
patterns and alternate routes for your personal commute as well as shopping or sales items related to 
your past purchases will be displayed. Health-related data will also appear, suggesting exercise, dietary,  
and medical alerts.

and medical alerts. 
*  http://www.eia.gov/tools/faqs/faq.cfm?id=99&t=3. 
† http://energy.gov/energysaver/articles/led-lighting.

339 Future Directions for Biomedical Informatics 
12.7.2 Ten Years: Intelligent Assistants 
Personal digital assistants will become relatively intelligent. You can have an intelligent dialog dis­
cussing specifically health and financial issues, and maybe these assistants will have the rudiments 
of a personal friend or therapist. They may also mine data from your LIFEr record, analyzing work 
frustrations and suggesting job changes, and the probability of success of landing that new position. 
They constantly inform you about available openings as well as education and training opportunities, 
a nagging mom. They can analyze job trends and suggest moving into related fields, both personal and 
financial. They can suggest available apartments that are more convenient to work. LIFEr would have 
access to your financial records and could suggest changes in your spending or investment strategies. 
With the ability to turn them off. 
12.7.3 Twenty-Five Years: Global Integration

12.7.3 Twenty-Five Years: Global Integration 
As communications are embedded in every device, including medicine, clothes, food items, etc., the 
world will truly be smaller. Food, medicine, or any commodity will be automatically tracked by every 
transaction and shipment or production adjusted automatically. This interdependence could be so great 
or the global scarcities of food and energy so acute that the borders will essentially dissolve. The other 
mitigating factor is military budgets that consume between 1% and 4.5% (the US budget was 4.5% of GDP 
in 2013) of world resources, which may be unsustainable. Other driving factors might be a global crises 
that could only be solved by global partnerships. At some point with the world population approaching 
9 billion in 25 years, some global consolidation on a logical level seems probable.* (Though the world has 
surprised us before WWI, WWII, etc.) 
12.7.4 Fifty Years: 150-Year Life Span

12.7.4 Fifty Years: 150-Year Life Span 
Information and research tools will allow intelligent software to share results in real time, and advance­
ments will be fed directly into pharmaceutical or production facilities. This will include medical devices 
or embedded drug dispensers. Research equipment will be semi-intelligent in targeted areas to conduct 
research independently, thus speeding up medical discoveries. Since life expectancy doubled from 1900 
(40 years) to 2000 (80 years), doubling again does not seem unreasonable in 50 years with the accelerated 
rate of technological and medical research. 
12.7.5 One Hundred Years: Ten Steps Forward or Five Steps Back 
This is a tough prediction. If we assume that technology continues to accelerate at the current pace, we 
could see advances that may be unrecognizable to scientists today. A hundred years ago, there were no

could see advances that may be unrecognizable to scientists today. A hundred years ago, there were no 
computers, TV, Internet, and antibiotics, and medical scanners consisted of simple x-rays. How would 
we have described our current technology in early twentieth century terms? In the next 100 years, the 
lines between biology and technology will blur. Gene cell therapy will be adaptable to most diseases, 
and nano-robotics or intelligent microbes will traverse our system to augment our immune system. 
Stem cell research will generate or repair diseased organs, including our brains. These device-embedded 
biotechnologies will monitor and report to future EHRs. We too will have direct brain access to the 
global information web with technology. Education will transform to where we can close our eyes and 
join global virtual classrooms or interact with a virtual personal teacher. Since data or knowledge can

join global virtual classrooms or interact with a virtual personal teacher. Since data or knowledge can 
be downloaded to an embedded storage device or instant access to global data stores, facts may not be as 
important as organizing and extracting meaning. 
* http://data.worldbank.org/i ndicator/MS.MIL.XPND.GD.ZS .

340 Biomedical Informatics 
Universal medical access will hopefully be available to all. Planetary resources should be adequate if 
global conflict and income inequalities are resolved and resources are equally shared. At the very least, 
some limit on resource allocation needs to be set. Nobody is so valuable that they are worth more than 
10 or 100 times that of others. If an average salary in 2015 is $50,000, then 100 times that is $5 million. It 
is estimated currently that 100 families have the equivalent resources of 3 billion people. A future based 
on an individual’s knowledge and contribution to society would benefit all. 
Sociological advances seem to move more slowly. Many have the same prejudices their grandparents 
had. We could have the ability to start colonizing other planets, possibly driven by resource or overpop­
ulation concerns, but if we bring our attitudes and prejudices with us, we remain stagnant and recreate

ulation concerns, but if we bring our attitudes and prejudices with us, we remain stagnant and recreate 
the inequities of the past wherever we are. Will there be a rich–poor divide or will we evolve beyond our 
infancy. We have to be optimistic; we are the teachers, philosophers, gurus that will set the foundations 
of future societies. In 100 years from now, our future civilization will stand on our shoulders, a duty and 
privilege we do not always appreciate. 
12.8 Summary 
The science of BMI is in its infancy. The recent funding mandates that began in 2009 in the United 
States spurred adoption by hospitals and physicians. During this period of rapid expansion, physi­
cians and nurses faced the challenge of navigating and entering data with relatively primitive user 
interfaces. Phase I involved the adoption of EHRs and the development of the support IT infra­
structure. This next phase, beginning after 2015, will be to tailor the user interfaces to the needs

structure. This next phase, beginning after 2015, will be to tailor the user interfaces to the needs 
of individual users and to provide sophisticated navigation capabilities that have been available to 
tablet and Smart phone users for the past decade. Auto data entry to EHRs has slowly begun, but this 
capability is critical in hospital settings where nurses have numerous monitoring devices, far too 
many to enter this data manually. Earlier in the book, consider the analogy to airplane pilots who 
might be similarly stressed if they had to fly the plane and simultaneously enter critical data on wind 
speed, direction, etc. Try this with five patients and the task is daunting. 
This chapter proposes metrics to quantify predictive analytics for BMI. Any prediction is a 
complex combination of factors, but if most of the variables are provided, estimates can be reli­
able. Finally a series of possible evolutions to this science are discussed mostly to raise the con­

cerns and hopes of professionals in the field regarding the future benefits that can be achieved. 
Proactive diagnosis and treatment can reduce the severity of most diseases, and with new treat­
ment methodologies, these diseases can be cured. The adage “knowledge is power” should be the 
mantra of BMI. 
Questions 
Level I 
 1. Why extrapolate future trends in medical practice? 
 2. What is predictive analytics? Explain how independent and dependent variables are used in pre­
dictive analytics? 
 3. Explain what the author defines as the four components of medical predictive analytics. 
 a. In your opinion what does each component add to the analysis of future trends? 
 b.  What are predictive confidence factors? 
 c. What are cost: predictive (factor) weights? 
 d.  What are government mandates? 
 e. What are intangible costs?

4. What are HCAHPS scores? 
 a.  Why are they included in the medical predictive analytics? 
 b.  What are the government penalties for low HCAHPS scores? 
 5. What do the CDC EHR trends imply for future EHR adoption? What do they include and exclude 
in their data? 
 6.  In Section 12.5 (Scenario 2), do you agree or disagree with the prediction: “In 5–10   years  
all medical devices will automatically update Electronic Health Records directly. This will  
not only be in hospital but will include wearable wireless medical devices.” Explain your  
analysis. 
Level II 
 7. In Table 12.13, two alternative predictions are made concerning the “probability of expanded EHR 
funder beyond 2015”: one prediction is 73% and another is 90%. Explain if you agree or disagree  
with higher mandates, government or professional, are reasonable. Explain your analysis. 
Level III 
 8.  In this section the author predicts a number of medical technologies for the next 5–100 years.

Level III 
 8.  In this section the author predicts a number of medical technologies for the next 5–100 years. 
 a.  Which one do you agree with and why? 
 b.  Which one do you disagree with and why? 
 9.  Make your own prediction on future medical technologies or methods of medical practice, not 
discussed in the textbook. Provide some research data to support your hypothesis. As a class proj­
ect, present your findings to the class. 
Glossary 
Dependent variable (response variable) is a variable in a functional relation whose value is determined 
by the values assumed by other variables in the relation. 
Hospital Value-Based Purchasing  Program is a Centers for Medicare and Medicaid Services initiative  
that rewards acute care hospitals with incentive payments for the quality of care they provide 
to people with Medicare. 
HCAHPS initiative is “to provide a standardized survey instrument and data collection methodology

HCAHPS initiative is “to provide a standardized survey instrument and data collection methodology 
for measuring patients’ perspectives on hospital care. HCAHPS survey items complement the 
data hospitals currently collect to support improvements in internal customer services and 
quality related activities.” 
Hospital Readmission Reduction Program  imposes financial penalties on hospitals for “excess” read­
missions when compared to “expected” levels of readmissions. 
Independent variable (explanatory variable), in mathematics, is a variable whose value determines the 
value of other variables. 
Predictive analytics  is the practice of extracting information from existing data sets in order to deter­
mine patterns and predict future outcomes and trends. It does not tell you what will happen in 
the future. It forecasts what might happen in the future with an acceptable level of reliability 
and includes what-if scenarios and risk assessment.*

and includes what-if scenarios and risk assessment.* 
*  http://www.webopedia.com. 
341 Future Directions for Biomedical Informatics

342 Biomedical Informatics 
12.A Appendix: HCAHPS Survey*
 
* http://www.hcahpsonline.org/Files/HCAHPS%20V7%200%20Appendix%20A1%20-%20HCAHPS%20Expanded%20 
Mail%20Survey%20Materials%20(English)%20July%202012.pdf.

347 Future Directions for Biomedical Informatics 
Sample Initial Cover Letter for the HCAHPS Survey
[HOSPITAL LETTERHEAD]
[SAMPLED PATIENT NAME]
[ADDRESS]
[CITY, STATE ZIP] 
Dear [SAMPLED PATIENT NAME]: 
Our records show that you were recently a patient at [NAME OF HOSPITAL] and discharged on [DISCHARGE 
DATE]. Because you had a recent hospital stay, we are asking for your help. This survey is part of an ongoing 
national effort to understand how patients vie w their hospital experience. Hospital results w ill be publicly re­
ported and made available on the Internet at www.hospitalcompare.hhs.gov. These results will help consumers 
make important choices about their hospital care, and will help hospitals improve the care they provide. 
Questions 1 to 25 in the enclosed survey are part of a national initiative sponsored by the United States Depart­
ment of Health and Human Services to measure the quality of care in hospitals. Your participation is voluntary

ment of Health and Human Services to measure the quality of care in hospitals. Your participation is voluntary 
and will not affect your health benefits. 
We hope that you will take the time to complete the survey. Your participation is greatly appreciated. After you 
have completed the survey, please return it in the pre-paid envelope. Your answers may be shared with the hos­
pital for purposes of quality improvement. [OPTIONAL: You may notice a number on the survey. This number 
is used to let us know if you returned your survey so we don’t have to send you reminders.] 
If you have any questions about the enclosed survey, please call the toll-free number 1-800-xxx-xxxx. Thank 
you for helping to improve healthcare for all consumers. 
Sincerely, 
[HOSPITAL ADMINISTRATOR]
 
[HOSPITAL NAME]
 
Note: The OMB Paperwork Reduction Act language must be included in the mailing. This language can be either

Note: The OMB Paperwork Reduction Act language must be included in the mailing. This language can be either 
in the cover letter or on the front or back of the questionaire. The exact OMB Paperwork Reduction Act language 
is included in this appendix. Please refer to the Mail Only, and Mixed Mode sections, for specific letter guidelines.

Appendix A: Application 
Development for Electronic 
Health Records–Mobile 
Applications Development 
Brief synopsis of components available in all four appendices: 
• Setting up a development environment 
• Appeasing the Tiki gods 
• Hello world 
• Mobile app structure 
• B: HTML 
• What is HTML? 
• HTML5 specification 
• Single-page applications 
• HTML tags: advanced 
• Creating an application wireframe 
• C: What is CSS? 
• CSS3 specification 
• Applying styles to your wireframe 
• The human interaction 
• CSS advanced styles 
• Knowing your audience 
• Separating screens 
• D: JavaScript 
• What is JavaScript? 
• Alert (“Hello world”) 
• Some basic functions 
• Using libraries 
• Bringing your app to life 
• Applying functionality 
• Wrapping up 
• Wrapping your application into PhoneGap 
• Deploying to Google Play 
349

350 Appendix A: Application Development for Electronic Health Records 
A.1 Introduction 
These appendices, A1–A4, provide a brief tutorial on developing web applications. They are specifically 
targeted to biomedical informatics students who want to understand the core components used in cre­
ating both web and user apps for mobile devices. The components are HTML5, Cascading Style Sheets 
(CSS), JavaScript, and PhoneGap. PhoneGap (http://phonegap.com/) is a product from Adobe, which 
allows applications for mobile devices to be created from generic components such as HTML5 and 
JavaScript and translated so that they can be utilized by all mobile device operating systems such as iOS 
(Apple), Android, BlackBerry, and Windows devices. 
A.2 What Is Covered? 
The chapters of this book are structured around the various technologies necessary to build mobile

The chapters of this book are structured around the various technologies necessary to build mobile 
a p p l i c a t i o n s  u s i n g  w e b - b a s e d  t e c h n o l o g i e s .  W e  will  r e vi e w  H T M L  ( H yp e r  T e xt  M a r k u p  L an gu a g e ) , 
CSS, and JavaScript. 
We will reinforce the theories presented in the chapters by building parts of a personal health records 
app by using the material presented throughout the chapters. 
The first section is focused on getting familiar with the technologies used in mobile app development, 
along with the tools necessary to deploy our applications for production use. 
The rest of the chapters are focused on covering “everyday use” HTML/CSS/JavaScript along with 
code examples, images, and step-by-step instructions in building and deploying a personal health 
records application. 
A.3 Getting Started 
Welcome to the rapidly expanding world of mobile app development using web technologies! Over the

Welcome to the rapidly expanding world of mobile app development using web technologies! Over the 
course of the next few chapters, we will walk through the process of creating App-Store ready mobile 
applications. Due to the high market share of Windows machines currently in circulation, we will focus 
on using the Android platform (you need a Mac and iPhone to develop iPhone applications). However, 
the beauty of using web technologies to create mobile applications is that we are easily able to reuse 
most, if not all codes for both platforms (one of the biggest benefits of using web technologies). The only 
requirement for the following code to run is a WebKit-based browser (Safari and Google Chrome at the 
time of writing this book). 
A.3.1 Mobile Applications at a Glance 
A.3.1.1 Using PhoneGap 
Since most of our conversation throughout the book will be based upon using the technology

Since most of our conversation throughout the book will be based upon using the technology 
“PhoneGap,” I would like to give the technology its own introduction including its history and what it 
actually does so that we can jump into some of its amazing features. 
PhoneGap is a program that allows web developers to use their preexisting web-based skills and 
create applications using HTML, CSS, and JavaScript rather than having to learn each platform’s pro­
prietary languages. 
PhoneGap has created (and continues to create) APIs or modules for developers to access device-
specific hardware using pure JavaScript, allowing the developer to have an almost native finished 
project.

351 Appendix A: Application Development for Electronic Health Records 
By allowing the developer to develop in one language across all platforms, it allows developers to keep 
costs down and develop a larger quantity of apps in a shorter amount of time. PhoneGap is great for 
applications such as the following: 
Informational applications 
Directory applications (such as Yelp) 
2D gaming 
PHR/EHR applications 
Enterprise business communication apps 
PhoneGap does have its constraints, however. By developing in web languages, we sacrifice speed of cre­
ation with the power of UI animation and heavy computing. JavaScript is considerably slower (although 
there are major improvements with the language), it does not match each platform’s native language in 
terms of computing power. 
Also, since PhoneGap is essentially a webpage, we are limited to a single application view. In both iOS 
and Android, WebViews are allotted to use about 60% of the total memory allowed for the application,

and Android, WebViews are allotted to use about 60% of the total memory allowed for the application, 
meaning we lose the ability to leverage 40% of the memory allotted for the application before the app 
launches. 
Before developers use any technology, they should weigh the project at hand and use the appropriate 
technologies for the application that needs to be made. 
A.3.1.2 Device Capabilities 
Although we do not have enough time to go over most of the technologies that are available for 
developers to use when creating mobile applications, it is still worthwhile to mention what we can 
do briefly. 
During the writing of the book, the following link: http://docs.phonegap.com/en/edge/guide _ 
platforms_index.md.html will give you a full understanding of the hardware integration that 
PhoneGap has made available for us. Let us go over some of the main hardware APIs made avail­
able for us. 
A.3.1.2.1 Touch

A.3.1.2.1 Touch 
This is a phone-level API but one of the most important. JavaScript is able to log touch events such as 
touchstart, touchmove, and touchend. At the time of writing this book, all iOS devices and 99% of 
Android devices support both single and multiple touch events allowing the developer to allow for rich 
touch-based interaction with their applications. 
A.3.1.2.2 Geolocation 
Since the beginning of mobile app development, app developers have tried to integrate geolocation in as 
many apps as they can. The reason for this is because phones are mobile and developers want the user to 
be updated with correct geographical location. Whether it is to find restaurants around you, or get the 
local weather, the use of geolocation is a crucial aspect of most app developers’ apps.

local weather, the use of geolocation is a crucial aspect of most app developers’ apps. 
PhoneGap has created an easy way for us to access a user’s initial geolocation and a way to update that 
geolocation as periodically as we want. 
A.3.1.2.3 Hardware Sensors 
Hardware sensors are standard in most phones, and developers have made use of these sensors to create 
rich applications for many uses. 
Although there are many, PhoneGap currently has two readily available sensors for public use 
(although there are third-party plug-ins that are available for download and use).

352 Appendix A: Application Development for Electronic Health Records 
A.3.1.2.4 Accelerometer 
With the use of the accelerometer, we are able to capture device movement of the x, y, and z access of any 
device. This would be useful when creating an application that is “motion aware” such as a maze game 
where the ball or game piece moves based on the phone’s current position in a user’s hand. 
A.3.1.2.5 Gyroscope 
The gyroscope is generally used when a developer wants to capture and display the current heading 
(north, east, south, west) of a user. They are generally used for compasses and other applications that 
require the use of a compass or heading. 
A.3.1.3 Device Connectivity 
PhoneGap provides an interface for users to retrieve the current connectivity a user has at any given 
time. Suppose you are creating an application that requires the use of the Internet. If a user does not

time. Suppose you are creating an application that requires the use of the Internet. If a user does not 
have an Internet connection, you could tell them that they need to have Internet connection to make use 
of the mobile application. As we will learn later on, making the life of your users as easy as possible is 
crucial to the commercial success of your application. 
The current network statuses a phone could have are as follows: 
• Connection: unknown 
• Connection: Ethernet 
• Connection: Wi-Fi 
• Connection: Cell 2G 
• Connection: Cell 3G 
• Connection: Cell 4G 
• Connection: Cell 
• Connection: None 
A.3.1.4 Camera 
Multimedia such as photos and videos have become an intricate part of apps today (Instagram, Twitter, 
Facebook). With the use of PhoneGap, we are able to access a user’s camera roll or give them the ability 
to take pictures in real time. 
A.3.2 Preparing the Development Environment

A.3.2 Preparing the Development Environment 
In order to be successful in creating mobile applications, it is necessary to set up your computing envi­
ronment to sustain the development of your applications. 
 1.  P
ick a text editor. 
 a.	  I personally prefer Notepad++ (http://notepad-plus-plus.org/) 
 i.	  Notepad++ is a very mature editor packaged with rich features.
 I. 	 Color coding. 
  Notepad++ detects what language you are writing and separates them with different 
colors and fonts.
 II. 	 Line numbering. 
  You can easily sift through your code and “bookmark” lines for later inspection. 
 III. Notepad++ supports most major languages and is able to detect and separate them. 
  However, every person has a preference. Please visit http://en.wikipedia.org/wiki/Comparison_ 
of_text_editors for a larger list of text editors to compare and choose from. 
 2.  Creating a folder structure to create an application.

 2.  Creating a folder structure to create an application. 
Once you have chosen and downloaded a text editor of choice, it is time to set up our development 
directory.

Appendix A: Application Development for Electronic Health Records 353 
On your desktop (or directory of choice), create a folder named PHR by right-clicking in the directory 
and navigating to the “new” option and selecting folder. 
Once you have created the PHR directory, double-click it to enter the folder. Once inside, we need to 
create subdirectories to ensure we maintain an organized development directory (having files in one 
folder can make it hard to manage, especially larger projects). 
As per the mentioned process create the following folders in the PHR folder: 
• Images 
• CSS 
• Scripts 
These folders will help us organize our projects and hold files based on their file extension to help us 
navigate through the project. 
After you are finished, your folder structure should look like the following: 
Next, open your text editor. We are going to create an HTML file that will serve as the “backbone” of 
our application.

our application. 
To save an index.html file in your PHR directory from your text editor: 
 1.  Go to File > New File. 
 2. Go to File > Save As. 
 3. Find the directory where you created the PHR folder and then enter the PHR folder. 
 4. Save the file as index.html.

354 Appendix A: Application Development for Electronic Health Records 
Congratulations! You have now saved your first HTML document. If you double-click the document 
from the folder your default browser should open the document and you will see a blank screen. 
Now that we have our file structure set up, let us download, install, and set up our Android environment 
so that we have the ability to create and launch apps on either your Android device or the Android simulator. 
1. Check for Java. The use of Eclipse for Android requires the use of the Java Development Kit, which 
is not standard on most computers. To update or install Java, please visit: http://www.oracle.com/ 
technetwork/java/javase/downloads/jdk8-downloads-2133151.html 
and download either the 64 bit or ×86 version (for 32-bit computers). Once downloaded and installed, 
we now can download Eclipse. Eclipse is a development environment used to create Java and Android

we now can download Eclipse. Eclipse is a development environment used to create Java and Android 
projects. Android was generous enough to bundle Eclipse with all the necessary Android SDKs making 
it easy to start creating Android applications. Please follow the link http://developer.android.com/sdk/ 
index.html and download and install the Eclipse ADT Bundle. 
Once installed, place the resulting folder in a place where you will not need to move it (you will soon 
find out why).

355 Appendix A: Application Development for Electronic Health Records 
The next step in setting up PhoneGap is adding variables to your Windows environment (PhoneGap 
is actually missing complete chunks of information, and it took hours to figure out on my own). 
1. Go to your Start menu, navigate to the “Computer” tab, right-click it, and pick the Properties tab. 
2. Once the Properties window appears, navigate to the left-hand pane and click the “Advanced 
System Settings” link. A “System Properties” window appears, click the button that says 
“Environment Variables.”

356 Appendix A: Application Development for Electronic Health Records 
3. Once in your Environment Variables, navigate to the bottom half of the window “System 
Variables” and click the “New” button. 
Type in “JAVA_HOME” (all capitals) for variable name and find the path where the Java JDK is in your 
system (should be in the program files folder in the C drive by default) and copy and paste that path into 
the variable value.
 4. Press OK. 
5. Press New once again. 
a. 	 This time, type in ANT_HOME for the variable name. 
b.	 For the value, find the ANT_HOME folder in your system. It should be in the Eclipse folder 
we downloaded earlier (this is why you cannot move this folder, if you move it, you will need 
to update the system variables). 
c. 	 Go to the adt-bundle folder > eclipse > plugins. You should see the org.apache. 
ant_1.8.4.v201303080030 folder. Double-click it. Copy the path name from the top window 
and make it the variable value for the ANT_HOME variable.

357 Appendix A: Application Development for Electronic Health Records 
Press OK. 
6. The environment we have to set up already exists, so all we have to do is to edit it. 
a. Find your way down to the PATH variable and click the Edit button. 
7. Navigate back to the adt-bundle folder > eclipse > plugins on your system and take out a new 
notepad document. 
a. Double-click the Ant folder and then double-click the Bin folder that lies in the Ant folder.

358 Appendix A: Application Development for Electronic Health Records 
Copy the path at the top search bar into the notepad and then add a semi-colon “;”. 
8. Navigate back to the Java JDK folder in your C > program files folder and then double-click on the 
Bin folder within it. 
a. Copy the path at the top search bar and paste it after the semi-colon that follows the Ant path. 
b. Add a semi-colon to the end of that path. 
9. Navigate back to the adt-bundle folder and double-click the sdk folder this time. Double-click the 
platforms folder. Copy the path and paste it in your word doc. Place a semi-colon after the path. 
10. Go back to the SDK folder and double-click on the tools folder. Copy the path and paste it in the 
word document. Place a semi-colon after the path. 
11. Your word document should look like the following: 
Put all the paths on one line and copy them to the clip board.

Put all the paths on one line and copy them to the clip board. 
Go back to the path variable and add a semi-colon to the last added path. Then paste all the paths we 
just created in the word document into the path. 
Press OK. 
Press OK to leave the environment variables. Press OK again to leave system properties. 
Your paths should now be set and Cordova should be able to read them while trying to create an 
Android project.

359 Appendix A: Application Development for Electronic Health Records 
Great! Now let us set up PhoneGap! The PhoneGap setup takes a few steps. First, we will need to 
download a tool known as Node.js. Node is a command line tool that lets us download packages 
from the web. PhoneGap has adopted the use of Node.js in order to simplify and streamline the app 
creation process. 
1. Download Node JS. Follow the link: http://nodejs.org/download/. 
a. 	 Once downloaded and installed, we can test the install as follows. Go to your Start menu and 
type cmd in your search bar and press Enter to open the command prompt. 
b. 	 To see if Node was properly installed, simply type npm and press Enter in the command 
prompt. 
c. 	 You should see the following: 
If you did not see this, please try the installation of Node again. 
A.3.2.1 Cordova 
Once we know Node works we are going to follow the instructions at the following URL: http://

Once we know Node works we are going to follow the instructions at the following URL: http:// 
docs.phonegap.com/en/3.4.0/guide_cli_index.md.html#The%20Command-Line%20Interface, 
which are instructions as to how to download and configure the Cordova command line tools for 
Android. 
In your command prompt simply type npm install –gcordova 
(Warning: If you are not the administrator on your computer this will not work. Make sure to gain 
administrator access to the computer you will be working on). 
Node will then download the Cordova command line tools and you should now be able to create 
PhoneGap projects with ease. 
(Note: The directory where you ran the install command is where the Cordova folder will be installed 
to, i.e., my Cordova folder is now installed in \Users\Daniel.) 
Time to test our install! Let us type in a command to create our first Cordova project. Simply type the 
command Cordova create hello com.hello.hello HelloWorld.

360 Appendix A: Application Development for Electronic Health Records 
If successful, you will receive a message like so: 
There are four parts to the “Cordova” command to create an application:
 1. Cordova create: 
a.	 Create is a command to run a batch file in the Cordova folder in which they compile the nec­
essary files in order for you to be able to compile on an Android device.
 2. Hello: 
a. 	 Where we typed in hello is a friendly name where Cordova will create a folder so we can 
later find the project. When we navigate to the Cordova folder, you will see the folder named 
“hello.”
 3. com.hello.hello: 
a.	 We need not worry much about this except that we need one. This is a unique namespace 
that will uniquely identify itself on the Appstore. Google and Apple use it when you want to 
launch your app from an external website.
 4. HelloWord: 
a. 	 This is the last part of the command and certainly not the least important. This represents the 
actual project name.

4. HelloWord: 
actual project name. 
If you do not type in the full command, the creation of the app will fail and you will need to try 
again. 
We must now add the platforms we are going to make the application for. Currently, the two main 
competitors in the app world are Apple and Google so we will not bother with smaller markets such as 
Microsoft of Bada. 
1. Change directory into the hello folder by typing cd hello in the command prompt. 
2. Next, let us add the platforms we want to make the application for: 
a. 	 Cordova platform add android 
b. 	 Cordova platform add iOS 
3. Then, let us build, prepare, and compile each platform so that they are ready to be used. 
a. 	 Cordova build (press Enter) 
b. 	 Cordova prepare android (press Enter) 
c. 	 Cordova compile android (press Enter)

c. 	 Cordova compile android (press Enter) 
Great! You have now successfully built your first PhoneGap application for Android! Let us put this to 
the side for a bit as we will come back to it later as we learn some HTML skills and we want to test it on 
our emulator. 
Examples: 
Appendix A Example: 
Now that we have Node JS and PhoneGap configured for our Windows environment, it is time to add 
the project to Eclipse and run it for the first time. 
Step 1: 
The first step in importing our PhoneGap project is to open Eclipse. Find the directory where you 
stored the adt-bundle download and double-click the Eclipse executable.

361 Appendix A: Application Development for Electronic Health Records 
Once Eclipse is open, it is time to import the project for use. Importing a PhoneGap project is quite 
different than creating a new Android application from Eclipse. Traditionally Eclipse helps you cre­
ate your Android application by “wrapping up” the necessary executable JAR files in order to run an 
Android project. However, Cordova does this for us when we create our application via the command 
line. They also include their own JAR files, which help us run applications using HTML, CSS, and 
JavaScript. 
Step 2: 
Now we have to import the project. We achieve this by doing the following: 
1. Go to File > New > Project.

362 Appendix A: Application Development for Electronic Health Records 
2. Select and expand the Android tab and select the “Android Project from Existing Code” Option. 
3. Click on the Browse button

363 Appendix A: Application Development for Electronic Health Records 
4. From here, search for the directory where we saved our “hello world” project. Once you find it, 
click on it, and press OK. You should now see the project (along with other Cordova files) in your 
package explorer located on the left-hand side of Eclipse. 
5. Now that the project is important, we need to set up our virtual Android device to allow us to run 
our projects on the Emulator. Note: If you have an Android device, you can compile directly on 
your device by connecting your phone via USB and installing the appropriate drivers from your 
manufacturer. 
a. 	 We first need to go to the virtual device manager. On the main screen go to Window > 
Android Virtual Device Manager. 
b. 	 Once in the AVD menu, click on the create button. 
c. 	 Fill in the following information about your virtual device:
 i.	  Device name
 ii. 	 Device (you can choose from the drop down)

 iii. 	 Target (operating system of the device)
 iv. 	 CPU type
 v.	  Memory options 
1. 	 Note: set the RAM to 768 if you do not have at least 16GB of RAM installed on your 
computer, or your virtual device will not run.

364 Appendix A: Application Development for Electronic Health Records 
And press OK. We have now successfully set up our Android Virtual Device. 
6. Our last step is to run the project. To do this, simply right-click the project, find Run As >, and 
select “Android Application.”

365 Appendix A: Application Development for Electronic Health Records 
Your Android Virtual Device will now appear and the program will now run!

Appendix B: Mobile 
B.1 HTML 
HTML or Hypertext Markup Language will be the first skill we learn as it is the backbone and starting 
point to creating any web-based application. 
B.2 What Is HTML? 
HTML is a markup language that comprises a set of “tags” that allows developers to render text, images, 
video, audio, colors, shapes, and more on an HTML page. An HTML page is nothing more than a simple 
website on the Internet. 
Go over HTML5 specification here. 
B.3 What Are Tags? 
Tags are nothing but separators in an HTML page that allow us to organize information in a meaningful way 
on an HTML page. In most cases, HTML tags have opening and closing tags and the information is enclosed 
within them. Let us take a look at some HTML tags. Open your text editor of choice and let us begin: 
<! Doctype> 
<html> 
<head> 
</head> 
<body> 
</body> 
</html> 
B.3.1 Let Us Break Each Tag Down
 1. <!Doctype>

<html> 
<head> 
</head> 
<body> 
</body> 
</html> 
 1. <!Doctype> 
a. 	 The Doctype tag is a tag that is placed at the top of every HTML5 document. It simply tells the 
document to render HTML in the HTML5 specification. This tag is one of the very few that 
are self-closing.
 2. <HTML> 
a. 	 The HTML tag is a tag that encloses all HTML elements in a document. All HTML elements 
should be enclosed within this mandatory tag. 
367

368 Appendix B: Mobile Applications Development
 3. <head> 
a. 	 The Head tag is a tag that is used to link to external documents. It is not of much use now but 
it will be used to link external style sheets and JavaScripts.
 4. <body> 
a. 	 The Body tag is a tag that encloses all “user facing” tags. Any tags that a user should see go 
between these tags. 
Great! You now know the basic template for creating HTML web applications. Again these are guide­
lines, as if we put tags outside the body of a document they will still render. However, keeping the basic 
guidelines of HTML structure as important, as in most cases you will be working in teams and other 
developers will expect to see a “standard” of coding. Following this template also helps developers keep 
their code more “manageable” since most applications get quite big. 
If you save and run your document, you will see that you will be viewing a blank page. HTML tags

If you save and run your document, you will see that you will be viewing a blank page. HTML tags 
by default have no colors or size, so they will not appear unless explicitly told to. Let us start populating 
our document with tags that you will use when making web applications to make it a bit less boring. 
Between the body tags, let us add a tag called a div(<div></div>). Div tags stand for divider tag, which 
simply gives us a way of dividing information logically on a page. Think of a paragraph in a book. Each 
time you have a new thought or “section,” we separate them by giving them a new paragraph. If the 
entire book was written in one big paragraph, the reader would not know where one thought stopped 
and a new thought began. This same concept goes into HTML documents. 
B.3.2 Divs 
1. Div is a nickname for “division.” 
2. You are “dividing” information. 
3. Divs are block-level elements (we will come back to this). 
4. Divs can hold the following:
 a.	 Text
 b.	 Images

 a.	 Text
 b.	 Images
 c.	 Video
 d.	 Audio
 e. Other tags 
So, let us add a div with some content to our page:

369 Appendix B: Mobile Applications Development 
By simply adding a divider to our document and inserting the words “Hello World” we tell the docu­
ment to render these characters in the document. If we refresh, the page “Hello World” should appear 
in the top left corner. 
The next tags we will go over are the UL tag and the LI tag. These tags are used in conjunction 
wi th  e a c h  o th e r ,  s o  i t  i s  w o rth  g o in g  o v e r  b o th  o f  th e m  a t  th e  s am e  tim e .  ULs  o r  un o r d e r e d  li s ts 
are used to encompass list items. In the past 10 years or so, web applications have gone from being 
“ self -co n tain ed”  a p p li ca ti o ns  t o  a p p li ca ti o ns  tha t  ar e  used  b y  b illi o ns  o f  peo p l e  ar o un d  th e  w o r l d. 
Organizing and displaying large sets of data has always been a challenge for developers and designers 
alike. On websites, the developers and designers have much larger screens to utilize for information

alike. On websites, the developers and designers have much larger screens to utilize for information 
display. However, since most phones are not much larger than 4 inches, we are faced with the chal­
lenges of displaying enormous data sets in small areas. The use of lists has been a best friend to mobile  
app de
velopers. 
B.3.3 UL 
 1. UL stands for unordered list. 
 2. Technically, it is no different than a div and renders the same. 
 3. We use them because as developers we expect to see a set of LIs or list items enclosed in unordered 
lists. 
 4. A block-level element. 
LI  or list items are exactly what they sound like, “list” “items.” They are elements that are put into a list  
for the user to see. By default, <Li></li> tags are rendered with a bullet point (which we will later remove). 
B.3.4 LI 
 1. Stands for list item. 
 2.  Usually contains some sort of information that needs to be displayed as a list. 
 3. By default, most browsers render them with a bullet point.

2.  Usually contains some sort of information that needs to be displayed as a list. 
 3. By default, most browsers render them with a bullet point. 
 4. They should be enclosed in ULs. 
Now t
hat we know what ULs and LIs are, we should now add them to our HTML document. 
Notice that my LIs get rendered with bullet points. They are also on separate lines. This is called 
being a “block element.” Block elements are tags or “elements” that have their own line space. After a 
tag is closed, HTML will automatically break the line and render the next element on the following line. 
Block-level elements are one of three types of elements. We will go over inline block and inline elements 
shortly.

370 Appendix B: Mobile Applications Development 
Also note the indentation of elements when writing in my text editor. It is imperative that a developer 
writes codes in a way that is easy to read, for both yourself and other developers. 
When an element is inside or a “child” of another element, it should be indented, so relationships 
between elements are easily recognized. 
Writing comments is also a critical part of the application development life cycle. Since our document 
is now only 20 lines it does not help much; however, when our lines of HTML get to be thousands of 
lines, it helps to comment what elements do or what information they hold. This helps when having to 
update projects months later or when other developers help or collaborate in your project. 
• 	 Will finish HTML elements at a glance. 
B.3.5 IMG 
IMG tags allow developers to easily link images in an HTML document. Luckily for us, rendering

B.3.5 IMG 
IMG tags allow developers to easily link images in an HTML document. Luckily for us, rendering 
images in HTML is as simple as including a link to the image resource and letting the browser handle 
the rest. In most programming languages, it is up to the developer to incorporate codes to render the 
image manually. 
An image comprises two main (and mandatory) properties: 
B.3.6 SRC Attribute 
• This defines the actual source of the image in which the browser will try to render the image. 
B.3.7 alt Attribute: 
• 	 If the browser cannot load the resource or the resource does not exist, the alt text will appear 
instead of an image. 
Since we have no inner HTML in the IMG tag, the image tag need not be closed, thus making it a “self­
closing” tag. 
B.3.8 Inputs 
Inputs are a very important part of HTML documents. Inputs allow interactivity between the program 
and the user. Without inputs, web applications are simply informational pages and they are quite boring.

and the user. Without inputs, web applications are simply informational pages and they are quite boring. 
Inputs can hold various amounts of information and perform different actions. On mobile devices, 
different kinds of inputs will trigger the phone to bring up different kinds of keyboards. Let us explore 
a few different kinds of inputs. 
1. Input type of text 
These inputs are meant to hold general text. This will trigger the general keyboard on a phone.

2.  Input type of email 
These inputs also hold general information. However, on mobile devices it will trigger the phone to 
  
 4. Input type of password 
The input type of password will trigger the phone to raise a general keyboard; however, it will render 
all text as bullets instead of plain text to ensure privacy and keep a password private from others’ eyes. 
Important properties of inputs: 
 1.  The type attribute: 
 a. 	 As we went over, inputs have a type attribute that will trigger different keyboards and trigger 
different behaviors in the document. 
371 Appendix B: Mobile Applications Development 
use a ke
yboard that includes email characters such as the @ symbol as seen in the following: 
3. Input type of tel 
This input type is generally used for when you want the user to either enter a telephone number or 
be forced to use numeric keys. This input type will trigger the “number” pad and force the user to input 
numbers as seen in the following:

372 Appendix B: Mobile Applications Development 
2. The placeholder attribute: 
a. 	 The placeholder property allows us to tell the user what the input’s purpose is without having 
to clutter the document with labels. This is especially useful since we have very limited spaces 
on mobile devices. The following example shows that the input is requesting for your email. 
Once the user starts typing, the browser automatically deletes the text and allows the user to 
type in their own value. 
Open your HTML document and let us enter the following: 
B.4 Application Skeleton 
Writing a mobile application is comparable to building a house. 
First, we build a structure, we add the walls and decorate, and finally, we move in. Mobile app devel­
opment is similar. The first step in mobile application development is creating the app “skeleton,” or the 
wireframe of the application. With a wireframe, we will create all HTML elements that will be used in 
the application.

the application. 
B.5 Let Us Make a Wireframe 
Enough with the theory, let us get to work! The first and probably hardest part in making any mobile 
applications is creating a “storyboard” for the application. When we make mobile applications, there are 
four questions we need to answer: 
 1. What are we making? 
 Ans.	  F or this particular book, we will be creating a mobile PHR application that allows us to  
enter personal health–related information to show, analyze, and keep track of our personal 
health history. 
 2.  What information are we providing? 
 Ans. 	 I n this case, we are providing our user with the ability to see their personal health history 
in an efficient manner. 
 3. Who is our audience? 
 Ans. 	 U sually, apps have a target audience (i.e., tinder for singles looking to date or open

 Ans. 	 U sually, apps have a target audience (i.e., tinder for singles looking to date or open  
table for restaurant goers in their late 20s and early 30s). However, due to the rapid  
growth and awareness of the medical field in the past few years, our target audience  
has vastly increased. Our audience is now anyone from 12  years old to 99  years old that  
owns a smartphone. 
 4. How can we present the information to our audience? 
 Ans.	  Thi s question is really an accumulation of the past three questions. By answering the  
first three questions we can easily answer this question. However, we do need to make  
sure to create a sound HTML structure in order to be able to present our information  
to the public. 
To see a full explanation of creating a preapplication checklist, please visit: <insert link with full expla­
nation here>

nation here> 
Now that we have answered some preliminary questions, it is time for us to start coding! The first 
thing we are going to do is go into our PHR project folder and open our index.html file in your HTML 
editor (again, I use notepad++).

373 Appendix B: Mobile Applications Development 
Let us start off by entering some of our basic tags. 
As you can see we are using the same tags as earlier. We need our Doctype to declare an HTML5 
document, HTML tags to encompass all other HTML tags, our head tags to link JavaScripts and CSS, 
and our body that holds all visible HTML elements. 
Our application consists of four pages: 
 1.  Landing screen or “profile page.” 
 2.  Enter new data screen, where we will be able to fill in and store information about our medical 
history. 
 3. A list view of all past entries. 
 4. A settings page, where we can change personal information such as name and DOB. 
In creating a wireframe, we need to create a “holder” or a division for each screen so that they have a 
place to “live” on the application. That being said, let us create an area for each screen to exist on the app. 
All screens will have their own “containers,” which will be represented by different divs. Notice all

All screens will have their own “containers,” which will be represented by different divs. Notice all 
of the “screen divs” have the same class. We do this because we are going to later identify these screens 
with similar CSS in the next chapter. Also, clearly indenting children divs makes it easier to know that 
our screens are children of the body tag. Every child element should have one tab indent from its parent 
to help keep the document neat and organized while coding. 
Since we now have the holder for our screens, it is time to decide and “code” the elements necessary 
to create each screen. Since this is an introductory book, let us keep each screen as simple as possible.

374 Appendix B: Mobile Applications Development 
We allow the user to display their name on their profile along with their date of birth, weight, current 
age, a way to get to settings, and a way to see our current notes and add a note. 
Since the “profile” screen is our first screen, we will code all our HTML elements for this screen within 
the index.html page. Normally, each screen gets its own HTML page, which gets dynamically injected 
into the document. However, since HTML has some latency loading on phones, we want to ensure a 
“native” like experience for our users therefore having our first screen load as quickly as possible. 
If you run your HTML document, you will find that there are no styles associated with our elements. 
By default tags hold no styles (with the exception of ULs that have margins and LIs that have bullets). 
Let us finish our profile page! We now should add a div to contain two buttons that will lead us to our 
health history or our settings page.

health history or our settings page. 
Notice that inputs are self-closing tags. The reason that some elements are self-closing is because they 
have no “inner HTML” and only contain properties and values. All inputs (with the exception of the 
textarea tag) and IMG tags are self-closing tags. 
And that is it! We have now successfully created the wireframe for the first page of our application! 
Now since we have an idea of how we structure elements, I will briefly go over the structure to the rest 
of the pages so that we can then move on to CSS and styling our application. 
Let us go back to the main folder of our PHR app on our computer and create a new file called 
“settings.html.” Once it is created, open it in your HTML document.

375 Appendix B: Mobile Applications Development 
Since they are actually just “fragments” of a bigger application, and not their own full page, we do not 
have to add the default Doctype and HTML tags that go on every HTML page. Rather, we will just add 
all the elements necessary to creating a page within the “settings_screen” div that lives in index.html. 
Since this screen is packed with elements, we have to split them into two screen shots. On the 
top of the page, we are going to create a header, which holds the page title, a back button, and the 
“toggle edit” button. We will use the “toggle edit” button to enable or disable the ability for users 
to enter and edit information (so they do not do so by accident). We will encompass the inputs with 
in a form for later submission to either a phone or a server. Let us go over some new elements seen 
on the settings page.

376 Appendix B: Mobile Applications Development 
When running the settings.html page, you should see all of your elements in a list view, with bullet 
points. Again, we will remove them later with the use of CSS. Congratulations, we have now wireframed 
the second screen in our application! Let us close settings.html and now open the editor and create a 
new file called “history.html.” 
This screen will provide us with a list view of all our current items we have entered in our PHR app to 
keep track of health changes over time. This list gets generated dependent on the user, so we cannot do 
much with it now except set it up for later use. 
And that is it! Our history.html is mostly generated LIs from a database so we do not have much static 
content to fill it with. However, we should note the “add_item” button. This button will allow us to get to 
the final screen, which will allow us to enter a new item in our personal health record history.

the final screen, which will allow us to enter a new item in our personal health record history. 
Let us move on to creating our add item screen. Close the history.html document and create a new 
html document called “additem.html.” 
This screen will not have many elements since it will simply contain a way for us to create a new item 
in our history list. 
First, we start with the “add_item_holder” which is just a way to organize all the other elements 
that belong within the add item “fragment.” Again, when we run our application, we are going to load 
fragments of HTML to speed up initial load time and keep the html DOM light, preventing lag and 
decreased performance. Second, we add our back button that let us cancel creating a new item. 
We then add our form. Our form contains most of the elements on this page, so let us go over them 
in detail. 
1. The form element is used to logically hold inputs and textarea elements that allow for collabora­

in detail. 
tion with other developers. Using HTML standards is important, especially in a collaboration 
environment. 
2. 	We are going to use the input element to allow us to enter a title for our medical history item. We use 
“title” as the placeholder, eliminating the need for a traditional label to show the user the input’s use. 
3. We use a textarea to enter notes. A textarea allows the user to input multiline text that might be 
too long for an input. This is perfect for what we need it for, notes. 
4. The last element is our Submit button. The input type of “submit” tells the HTML document 
that we want to perform an action with our form and usually will redirect us to another page. 
However, since this is a single-page application, we are going to use JavaScript to override the 
default behavior of our submit button and perform another action.

377 Appendix B: Mobile Applications Development 
And we now have a complete skeleton of our application! It is now time to learn about CSS and start 
styling our application. 
Html5 Language Reference (Source World Wide Web Consortium www.w3c.org) 
HTML5 Markup Language
 
(http://www.w3.org/TR/html-markup/elements.html)
 
(Another HTML5 resource http://www.w3schools.com/tags/tag_menuitem.asp)
 
Command Example 
Hyperlink Example: <a href=“ ./page.html” </a> 
Basic html structure 
<!DOCTYPE html>
 
<html>
 
<head>
 
<title> my program>/title>
 
</head>
 
<body>
 
<h1> start page LARGE FONT></h1> 
<p> this is a link < a href=“test.html”> </a> </p> 
<!-- a comment line --> 
<body> 
</html> 
Address address {display: block; } address {font-style: italic; } 
Area Area{display: none;} 
The area element represents either a hyperlink with some 
text and a corresponding area on an image map 
Article Article{display: block;} 
The article element represents a section of content that

The article element represents a section of content that 
forms an independent part of a document or site 
Audio <audio controls> 
An audio element represents an audio stream. Provides a <source src=“beatles.mp3” type=“audio/mpeg”> 
standard for playing audio files. </audio> 
B b{font-weight:bold;} 
Bold 
Base 
The base element specifies a document-wide base URL for Interface HTMLBaseElement :HTMLElement{attribute 
the purposes of resolving relative URLs DOMString href; attribute DOMString target;}; 
Body Body{display:block;margin:8px} 
The body element represents the body of a document (as 
opposed to the document’s metadata). 
Br <br> 
The br element represents a line break. 
Button Button type=submit 
The button element is a multipurpose element for Button type=reset (resetting a from) 
representing buttons. Button type=button 
<button type=“button”>Click Me!</button> 
Canvas <script>

Canvas <script> 
which can be used for dynamically rendering of images var canvas=document.getElementById(‘myCanvas’); 
such as game graphics, graphs, or other images. 

378 Appendix B: Mobile Applications Development 
 
var ctx=canvas.getContext(‘2d’);
 
ctx.fillStyle=‘#FF0000’;
 
ctx.fillRect(0,0,80,80);
 
</script>
 
Command type=radio <input type=“radio” name=“your name” value= 
“choice”/> 
The command element with a type attribute whose value is “ 
radio” represents a selection of one item from a list of items. 
Form Form{display: block; margin-top:0em;} 
The form element represents a user-sub-mittable form. <form> 
Password: <input type=“password” name=“pwd”> 
</form> 
Html Html{display: block} 
The html element represents the root of a document. <!DOCTYPE HTML> 
<html> 
<head> 
<title> My test document </title> 
</head> 
</html> 
H1-H6 font sizes H1=24px 
H2=22px 
H3=18px 
H4=16px 
H5=12px 
H6=10px

<html> 
<head> 
</head> 
</html> 
H2=22px 
H3=18px 
H4=16px 
H5=12px 
H6=10px 
Input Input type =“text” 
The input element is a multipurpose element for Input type =“password” 
representing input controls. Input type =“checkbox” 
Input type =radio” 
Input type =“button” 
Input type =“submit” 
Input type =“reset” 
Input type=“text” 
Input type =“file” 
Input type =“image” 
Input type =“date” 
Input type =“email” 
Input type =“search” 
Input type =“color” 
<form> 
First name: <input type=“text”
 
Name=“firstname”><br>
 
Last name:<input type=“text”
 
Name=“lastname”> 
</form> 

379 Appendix B: Mobile Applications Development 
 
Link <head>
 
The link element represents metadata that expresses <link rel=“stylesheet” type=“text/css” href=“theme.css”>
 
inter-document relationships </head> 
HTML5 video <video width=“320” height=“240” controls> 
Internet Explorer 9+, Firefox, Opera, Chrome, and Safari <source src=“movie.mp4: type=“video/mp4”> 
support the <video> element. </video>

Appendix C: Cascading 
Style Sheets 
C.1 What Is It? 
CSS or “Cascading Style sheet” is a markup language that allows us to style our HTML document. 
Without CSS, our HTML documents would be no more than simple text on the screen. With the use of 
CSS, we are able to create rich user interfaces that allow us to enhance the user experience by organizing 
and stylizing data. Through the use of CSS, we are able to render HTML tags with shapes, colors, sizes, 
positioning, borders, fonts, images, opacity, and more. 
C.2 Why Do We Need It? 
When creating an application, we are more than likely creating an app to appeal to a certain group of 
users. Through much trial and error, I have learned that certain groups of people need information 
displayed in a different manner. For example, when creating a medical-based application, I learned that 
medical professionals are used to looking at interfaces that had white and blue colors. Medical profes­

sionals are usually under high stress, and the use of bright colors such as orange or yellow make them 
feel like there is an emergency, while white and blue “calm” them. Also, displaying content is a challenge 
we face every day. In the medical field, doctors expect to read as little text as possible due to the fast-
paced nature of the job. As app developers, we face this issue all the time. 
C.3 Jumping Right in 
Where do we put CSS? CSS has its own document type (.css) that gets linked in the head of our docu­
ment. Let us go ahead and open our text editor. Create a new document and save it as index.css in the 
CSS folder of the PHR project we created earlier. Once saved, let us open our index.html document and 
link it in the head of the document. 
381

382 Appendix C: Cascading Style Sheets 
As you can see, the stylesheet tag is linked in the head of the HTML document and contains three 
proprieties. 
Rel: This tells the document that it is a style sheet.
 
Type: This also tells the document it is a text/CSS file.
 
Href: This can contain either a relative or an absolute path to a style sheet. Make sure you link the file 
correctly, or you will not see any styles.
 
Can styles not be placed directly in the document? 
Yes but, placing styles in separate sheets allow: 
1. The developer to create a style sheet for every screen. 
a. 	 That is, one style sheet for the settings page, one for the main page, etc. 
2. Easier to later identify and alter styles once you have created the application. 
3. You can then make these style sheets templates that you can reuse in later applications. 
4. You can dynamically load style sheets. 
a.	 Larger or more files mean slower load times. If you import them as we use them ( i.e.,

a.	 Larger or more files mean slower load times. If you import them as we use them ( i.e., 
only load the settings CSS when we use the settings page), it helps keep the document 
lighter. 
C.4 There Are Three Ways to Target Our Elements in CSS 
C.4.1 We Are Able to Target Elements by Their ID 
IDs are element identifiers used in the document to identify a unique element in the document. You 
should not use an ID more than once in the document. Doing this will “confuse the document” when 
applying styles and targeting elements in JavaScript. 
We are able to target an element’s ID in CSS by prefixing the ID with the # symbol. 
C.4.2 We Are Able to Target Elements by Their Class Name 
Classes are semi-unique identifiers meant to identify a group of “like” elements together. They can be 
used to apply similar styles to a set of HTML elements, or to apply a similar action to multiple HTML 
elements.

elements. 
Targeting a class name requires the prefix of a period. I

383 Appendix C: Cascading Style Sheets 
C.4.3 We Are Able to Target Elements by Their HTML Tag Name 
Each HTML element is associated with their own tag name. We are able to target elements by their tag 
name, i.e., we can target all divs with the div tag name or unordered lists with the UL tag. 
The div tag requires no prefix. 
C.5 Diving Right in 
Due to the brevity of the book, I will not be able to go over all of the styles that CSS has to offer. To 
see a full list of styles along with their explanations, please visit: http://www.w3schools.com/css / 
default.asp. 
Let us open our index.css document and our index.html document in our Word Editor. If you remem­
ber from the previous chapter, we made a few divs that were to be used as “screens” for our application. 
Each screen has their own ID. First, let us create a similar style for each that will act as the “template” 
for all screens. *Note, all images used in this sample app can be found at: http://combustioninnovation .

for all screens. *Note, all images used in this sample app can be found at: http://combustioninnovation . 
com/PHR/img and may be used for this app. 
Styles of note: 
For every web application we create, we always set the body and HTML tags to full height and width 
of the screen by using percentages (since we do not know the height and width of the screen, we let the 
browser do the math for us), and we remove the 8px of margin that the browser inserts into the docu­
ment by default.

384 Appendix C: Cascading Style Sheets 
Each screen should be the full height and width of the phone. We use percentages rather than a 
definite number of pixels because there are many different phone sizes. The web browser automati­
cally does the math for us and will adjust the width and height of any element that has a percentage 
value. 
C.6  	Let Us Now Go Ahead and Finish Styling the Rest of the 
Profile Page. Put the Following Styles in Your Style Sheet

385 Appendix C: Cascading Style Sheets 
Please visit http://combustioninnovation.com/PHR/img to download currentmedications@2x.png and 
profile@2x.png and place them into our images folder in our directory. 
Notice that we have a class of “main_button” that defines base styles for both of our buttons in our 
style sheet. Go back to your index.html page and add the class of “main_button” to our profile and 
settings buttons and remove the “values” to allow  there to be just a background image for both of the 
buttons.

386 Appendix C: Cascading Style Sheets 
Our index.html page should now look like the following: 
This completes our styles for our “main page.” As mentioned earlier, we will dynamically load CSS 
into separate style sheets in order to maintain code and decrease loading times for our pages. Let us 
close index.html and index.css and open our settings.html page. 
First, let us create the settings.css file in our CSS folder and link it on the top of our settings.html 
page. Traditionally, we would link CSS files in the head of our document, and this would be bad practice. 
However, to keep our page light, we are only going to link and load the settings.css file when we go to 
our settings page to compensate for phones and their limited processing power. The CSS file should be 
linked like the following: 
Now, let us style the page by applying the following styles in our settings.css page:

388 Appendix C: Cascading Style Sheets 
This page will allow us to update our personal information on the main page. As a refresher, the 
toggle_edit_info element will allow us to toggle our inputs disabled or enabled to ensure that we do not 
edit information by accident. After all styles are applied, our settings page should look like the following:

389 Appendix C: Cascading Style Sheets 
Please remove the body styles we applied in the settings.css, as it will conflict with our index.css style 
sheet when we dynamically load this page. 
We can now close our settings.html and settings.css, as we will come back to it at a later time. 
Next, let us open history.html. Just like the settings page, create history.css in the CSS folder and link 
it to the top of the history.html page. Once linked, let us apply the following styles: 
As you can see there is not much to style on this page at this point because most of the content on this 
page is dynamically generated as a list view of all of our medical items. We will come back and style our 
list items once we have an active list on the page. (Once we start using our local database.) For now, our 
history.html should look like the following:

390 Appendix C: Cascading Style Sheets 
We can now close history.html and history.css. Now open our add_item.html. Create the add_item. 
css in the CSS folder and link it on the top of the page. Let us apply styles based on the styles we have 
previously created for other elements in this app (we want to keep consistency in our styling throughout 
the app). Open add_item.css and add the following styles:

392 Appendix C: Cascading Style Sheets 
After applying our styles, our add item HTML page should look like the following: 
I have styled this page a little differently as I wanted to demonstrate some of the more “advanced” 
properties of CSS. Let us break down some of the differences in our styles:
 1. #add_history_item_form input[type=“text”] 
a.	 input[type=”text”] is a CSS pseudo selector that allows us to only target inputs that have the 
type of text set as the “type” property. Also, since I am targeting #add_history_form as a pre­
fix, it will only target inputs that are “children” elements of that element.
 2. #add_history_item_form input[type=“submit”] 
type of submit set as the “type” property. Also, since I am targeting #add_history_form as a 
prefix, it will only target inputs that are “children” elements of that element.

prefix, it will only target inputs that are “children” elements of that element. 
We have now completed styling of our entire application! It is now time to use JavaScript to allow us to 
navigate through our app and fill it with data.
 
Additional information:
 
For additional information on CSS please visit the following:
 
List of CSS properties: http://www.w3schools.com/cssref /.
 
CSS pseudo selectors: http://www.w3schools.com/css/css_pseudo_classes.asp.
 
ID vs class selectors: http://css-tricks.com/the-difference-between-id-and-class/.

Appendix D: JavaScript 
D.1 What Is JavaScript? 
JavaScript is an interpreted computer programming language. As part of web browsers, imple­
mentations allow client-side scripts to interact with the user, control the browser, communicate 
asynchronously, and alter the document content that is displayed. It has also become common in 
server-side programming, game development, and the creation of desktop applications. Interpreted 
programming languages get executed at runtime while compiled languages get precompiled and 
then run. The advantage to compiled languages is that they are more powerful and can do heavier 
calculations. 
JavaScript does have its advantages, however. JavaScript has the ability to run on any device or plat­
form that runs a web browser (which is pretty much any device with an Internet connection). JavaScript 
is almost standard across all platforms allowing developers to reuse the same code on any device rather

is almost standard across all platforms allowing developers to reuse the same code on any device rather 
than having to rewrite it when changing platforms. 
By its nature, JavaScript is not an object-oriented language. JavaScript is a functional language 
with the ability to create objects. This allows developers to create a sequence of commands without 
the “steeper” learning curves of an object-oriented language and the overhead of creating objects in 
memory. 
D.2 Where Do We Link Scripts? 
Most developers link their scripts at the head of their document, while I prefer to link mine at the bot­
tom of the body. The reason being (this holds true mostly for mobile), the loading of scripts may slow 
down the rendering of HTML elements because it is linked before HTML elements appear in the docu­
ment (HTML documents read tags from the top of the document to the bottom). By linking scripts at

ment (HTML documents read tags from the top of the document to the bottom). By linking scripts at 
the bottom of the page, we allow the page and its styles to load before we worry about loading the func­
tionality of the page, ultimately enhancing the user experience. 
D.3 Types of Variables 
Variables 
Variables are placeholders in memory that exist in every programming language. They give developers 
the ability to assign values to them dynamically without the developer knowing the actual value. 
393

394 Appendix D: JavaScript 
In JavaScript, we can easily assign data to variables. 
In this case, we assign the first variable firstvar the string of “hello.” Of course, this is not why we 
really use variables, especially if we know that we want to alert “hello.” However, suppose we want to 
alert our user a value that we might not know. 
For example, if we had an application where we wanted to display the users’ date when they clicked 
a button, it would be impossible for us to know the current date for all users at any given time. How do 
we solve this? We assign a variable in which we know the “key” to, which would be a friendly name or 
address in which we can retrieve the value in storage, and then use it at a later time. Take a look at the 
following: 
As the developer, we know that we want to retrieve the date object for our user, but we do not know 
the actual time or value of that date. However, we do know that the variable “mydate” will represent the

the actual time or value of that date. However, we do know that the variable “mydate” will represent the 
current date and time, so we can assign a date to it and use it in our function. If we alert mydate, it will 
tell us the current date and time. 
D.3.1 Local Variables 
Local variables are variables that are declared within a function and then “erased” from memory auto­
matically when the function is complete. It is usually wise to declare a function locally because JavaScript 
deletes the function from memory and we no longer have to worry about it. However, the drawback of 
having our variables deleted is that sometimes we need variables to persist until the user has finished 
using the application. In this case, using a local variable will not suffice. 
D.3.2 Global Variables 
Global variables have an application-wide scope and are values that do not get deleted by JavaScript 
automatically (they must be manually removed from memory). However, unlike local variables, we only

automatically (they must be manually removed from memory). However, unlike local variables, we only 
have to worry about assigning a value one time to our global variable.

395 Appendix D: JavaScript 
For instance: 
Since we know that our first name will always be the same, we should only have to declare that vari­
able one time throughout our program. By doing this, we are able to allow multiple functions to utilize 
this variable without having to declare it again. Global variables do have drawbacks, however. 
1. Any variable defined in the global name space owns that “location” in memory, so you will not be 
able to reuse the same variable name in memory again in any function. 
2. JavaScript does not use garbage collection on global variables. If you have a lot of global variables, 
and do not manage your memory properly, your application starts to slow down noticeably. 
3. The global variable is declared once, which is an issue for variables that need the most up-to-date 
 a. For instance: 
If we declare mydate in the global namespace, it gets assigned the date from the second that the script

If we declare mydate in the global namespace, it gets assigned the date from the second that the script 
is loaded into memory. Even though it may be more convenient for it to be declared once and reused, 
the date will remain the same even if we call the variable many hours later. If you want the value of the 
variable to update, you have to manually change the variable’s values, as JavaScript will not do it for 
you. When using global variables, try to assign only values that will remain constant throughout your 
application, such as a name, age, or any other value that will probably not change throughout the user’s 
session on the application. 
What kinds of data have the ability to be assigned to variables? 
Though this goes against most languages I believe that the following is one of JavaScript’s biggest 
strengths. Developers have the ability to assign almost any kinds of data types to variables, as variables 
are data agnostic.

are data agnostic. 
We are able to assign: 
Strings: “Hello World”; 
Integers, Floats, Doubles: 1

396 Appendix D: JavaScript 
Booleans: true
 
Objects: var person = {
 
“name”:“dan”,
 
“occupation”, “rockstar”,
 
}
 
Arrays: var array = [‘one’,‘two’,‘three’];
 
Other functions: var dan = getName();
 
D.4 Making Our First Script 
Let us create a new document called scripts.js and save it in the scripts folder we created previously. 
We have now linked our scripts to our HTML page and are able to perform any function that lies  
inside the scripts.js file. 
D.5 Function Parameters 
JavaScript, like most languages, has the ability to accept arguments or parameters in its functions to 
enable functions to by dynamic. Parameters are similar to variables, except that they are values usually 
passed from other functions, and do not have to be assigned a space in memory. It also gives the devel­
oper the ability to take one function’s variables and pass it to another function to perform an action. 
Parameter types: 
Parameters can contain the same data as variables, which include

Parameters can contain the same data as variables, which include 
• Strings 
• Integers 
• Objects 
• Arrays 
• Other functions 
• Booleans 
Just like variables, parameters do not have to have a predefined data type, as they are read at runtime. As  
this is strength of JavaScript, this could also be a weakness if the developer abuses the “data type agnos­
tic” methodology of JavaScript. Although a JavaScript error will not crash your application, it will cause 
your application to have a “dead end,” which will result in a terrible user experience. 
In the example given, we create a function that will alert the user’s age. Between the function brackets, 
we place a parameter of my age that will be the variable when we alert a user’s age. By using a function 
parameter, we have a way for multiple elements to call the function and change the variable value, with 
very little effort. This is one of the main advantages of passing parameters over using function variables.

1.  Declaring the function with the word “function” tells the script we are going to declare a  
function. 
 2. “HelloWorld” is a friendly name created by us so we can later call that function. 
 a. 	 Preferably, it is much easier to name functions that have relevance to the function it will per­
form so we have better indication of what the function does. 
 3. () inside our brackets we are able to pass parameters to the function, which we will go over a little 
later. 
 4. {} Inside the curly braces is where we are able to tell the script what we want the function to do. 
Whether it has to have an alert box to say “Hello world” or change the font of a div, it will all go 
in
side the curly braces. 
Now since we know how to declare a function, we have to know how to trigger it. Just because it is linked, 
it does not mean we can use it yet. To use it in our document, we need to link it to an element. 
397 Appendix D: JavaScript 
Making our first script:

Making our first script: 
We have now linked our scripts to our HTML page and are able to perform any function that lies 
D.5.1 Creating Our First Function 
In its most basic form, we create a function to perform an action. There are four parts to every function. 
Open yo
ur text editor and create a new HTML file called practice.html and enter the following: 
Then create a new file in your JS folder and call it index.js and enter the following: 
Save it. Open your HTML page in chrome and press the button and you should see the following:

398 Appendix D: JavaScript 
Congratulations, we have just created our first script! 
D.6 Using a Library 
JavaScript is great, and it is made even easier by using fantastic libraries that help us making syntax and  
mundane tasks easier and more efficient. When creating web and mobile applications, I usually use a 
library called JQuery (http://jquery.com). JQuery is a fantastic library that helps with many tasks such 
as attaching events to elements easily and efficiently. 
JavaScript Language Reference 
JavaScript
 
Excellent source http://www.w3schools.com/
 
Code Example 
JavaScript can be defined before the HTML code body 
<!Doctype html> 
<html> 
<head> 
<script> //JavaScript
 Function  getCELSIUS(farenheight) // converts farenheight to Celsius
 { 
 return (5/9) * (farenheight - 32);
 } 
</script> 
</head>
 
<body>
 
<button type=“button” onclick=“getCELSIUS(72)”> </button> // calls function
 
</body>
 
</html>
 
JavaScript can be defined in the HTML code body 
<!Doctype html>

</body>
 
</html>
 
<html> 
<body> 
<button type=“button” onclick=“getCELSIUS(72)”> </button> 
<script> // defines JavaScript function 
{
 Function  getCELSIUS(farenheight) // converts farenheight to Celsius 
 {return (5/9) * (farenheight - 32); 
} 
</script> 
</body> 
</html> 

JavaScript 
Excellent source http://www.w3schools.com/ 
JavaScript can be defined in an External Program 
<html> 
<body> 
// function is stored in an external file called DansScript.js 
<script src=“DansScript.js”></script> 
</body> 
Conditional Statements If (x<10) {CODE;} 
If
 
Else If (x<10) {CODE;}
 
Else if Else {CODE2;}
 
Switch //use a number of alternative blocks. evaluates the variable or function, in Switch ( x ) // some variable or 
this case variable x, if x=0 assigns result to xlow (something previous defined) function in parentheses 
{Case 0; xlow; break; 
Case 1: xmed; break; // assigns variable 
xmed if x=1; 
Case 2: xhigh; break; 
} 
Function Function  getCELSIUS(farenheight) 
JavaScript functions are objects {return (5/9) * (farenheight - 32); 
Return statement stops the execution of the function } 
//to call the function in your html 
code

code 
Temp = getCELSIUS (75) 
JavaScript Loops For (i=0; i<10; i++) 
{some calculation;} 
Math. Random(); //returns a random number 
Math.min () //finds lowest number 
Math.max(5,10,15,20); returns value 5 
Math.max() Finds highest number 
Math.max (50,100,150) returns value 
150 
Appendix D: JavaScript 399

Glossary
 
Advanced cardiac life support (ACLS):  The American Heart Association set of guidelines of  clinical 
interventions for the urgent treatment of cardiac arrest, stroke, and other life-threatening 
content is also offered as a course comprised of lectures, hands-on practice, written tests, and 
Advanced practice registered nurse (APRN): An APRN is a registered professional nurse with an 
advanced degree, either master’s or doctorate. There are four recognized APRN roles: certified 
registered nurse anesthetists, certified nurse-midwives, clinical nurse specialists, and certified 
the coronary arteries. The most common symptom prompting diagnosis of ACS is chest pain,

The Affordable Care Act (ACA): The act passed in March 2010 and upheld by the Supreme Court in 
June 2012, often referred to as Obama Care. 
The American Medical Association (AMA) Ethics Group:  sets guidance for physicians to pursue. The 
American Reinvestment & Recovery Act (ARRA): Passed by the Congress in 2009 contained $782 bil­
lion to jumpstart the economy and $20 billion targeted at promoting EHRs. 
Arterial blood gases (ABG): requires drawing blood from an artery. Often taken from the radial artery 
at the wrist or the femoral artery in the groin, but a number of other sites are also used. ABG

at the wrist or the femoral artery in the groin, but a number of other sites are also used. ABG 
provides more comprehensive information that simply pulse oximetry information, which is 
vital for critically ill patients in intensive care units (ICUs). 
Batteries: p r o vi d e  e l e ctri cal  e n e r gy  fr o m  c h e mi cal  r ea cti o n s,  th ey  in c o rp o ra t e  e l e ctr o c h e mi cal  c e lls, 
which allow the flow of ions. 
Beer–Lambert law: A law relating to the attenuation of light by a material passing through a substance. 
Bioinformatics: research focus, analyzes datasets for genomics, proteins etc. “The branch of information

Bioinformatics: research focus, analyzes datasets for genomics, proteins etc. “The branch of information 
science concerned with large databases of biochemical and pharmaceutical information” 
(world English Dictionary); it intersects with the field of computational biology. 
Biomedical engineering:  A field dealing with the application of engineering principles to medical 
practice. It also lies at the intersection of electrical engineering and the biological sciences. 
401

402 Glossary 
Biomedical informatics:  extrapolates meaning from diverse biological, medical, nursing, health, and 
clinical research sources and structures that data via intuitive interface with enhance 
healthcare and delivery. (Lubliner 2014) 
Blood pressure:  is the pressure on the walls of blood vessels exerted by circulating blood, which is 
measured by the force per unit area. Blood pressure is the brachial arterial pressure usually 
measured in the upper arm as blood moves away from the heart. The pressure of the blood in 
the circulatory system, often measured for diagnosis, since it is closely related to the force and 
rate of the heartbeat and the diameter and elasticity of the arterial walls. 
Blood products: Any component of the blood that is collected from a donor for use in a blood  transfusion. 
Whole blood is rarely used; most blood products consist of specific processed components 
such as red blood cells, blood plasma, or platelets

such as red blood cells, blood plasma, or platelets 
Bone marrow:  The contents of the bone that contain stems cells that can develop into a variety of 
cell types, for example, neutrophils, eosinophils, basophils, monocytes, dendritic cells, and 
Braden scale: An evidence-based method for determining a patient’s risk of developing a pressure ulcer. 
assessment is performed on admission and then either daily or every shift.

Brain stem: Part of the brain that includes the midbrain, pons, and medulla oblongata. Functions 
include cardiac, respiratory, and autonomic (involuntary) functions; blood pressure; and heart 
rate. 
immediate cardiopulmonary resuscitation (CPR). 
Cardiac index (CI):  The cardiac output corrected to reflect the size of the patient. Formula: cardiac 
output ÷ body surface area = cardiac index. The body surface area is dependent on the patient’s 
height and weight. Measured in liters/minute/square meter. Normal value: 2.6–4.2 L/min/m
2 
Cardiac myocyte:  A muscle cell that is 100 μ in length. It is composed of bundles of myofibrils that con­
tain filaments. Myofibrils are tubelike structures that propagate signals inside muscles.

tain filaments. Myofibrils are tubelike structures that propagate signals inside muscles. 
Cardiac output (CO):  The volume of blood pumped by the heart per minute, measured in liters per 
minute (L/min). Normal value: 5–6 L/min. 
through the atrial tracts, into the atrioventricular (AV) node, passes into the ventricles via the 
CCRN-E: An extension of the Critical Care Registered Nurse (CCRN) certification for RNs who moni­
tor crucially ill patients remotely in a tele-ICU or an e-ICU. 
Cells: The basic functional units of living organisms. They are the smallest units that can replicate.

Cells: The basic functional units of living organisms. They are the smallest units that can replicate. 
Humans contain approximately 100 trillion cells. Plants and animals are made up of eukaryote 
cells that contain compartmentalized areas, organelles, where metabolic activities take place. 
Center for Medicare and Medicaid (CMS): A federal agency within the United States Department of 
Health and Human Services that administers the medicare program and works in partner­

Glossary 403 
Cerebral cortex:  The outer covering of the cerebrum in large mammals. Two thirds of its surface is 
embedded groves (valleys) called the “sulci.” The ridges called “gyri.” 
It contains: 
• Frontal lobe: voluntary movement, planning, thought 
• Parietal lobe: includes the somatosensory cortex—touch 
• Temporal lobe: hearing and comprehending speech 
• Occipital lobe: visual processing center 
Cerebellum: The part of the brain involved in motor control. Its functions include balance, voluntary 
movements, motor learning, and some cognitive functions (language) (10% volume, but con­
tains 50% of the neurons in the brain). 
Chest tubes:  A flexible plastic tube that is inserted through the chest wall into the pleural space or

Clinical Decision Support System (CDSS):  A software that assists healthcare professionals in making 
diagnosis-, treatment-, and workflow-related decisions. 
Clinical Document Architecture (CDA):  The HL7 Version 3 Clinical Document Architecture (CDA ®) 
is a document markup standard that specifies the structure and semantics of “clinical docu­
ments” for the purpose of exchange between healthcare providers and patients. 
Clinical Information System (CIS):  A computer-based system that is designed for collecting, storing, 
manipulating, and making available clinical information for the healthcare delivery process.

Clinical Nurse Specialist (CNS):  L i c e n s e d  r e gi s t e r e d  p r o f e s s i o n al  n u r s e s  wi th  gr a d u a t e  p r e p ar a ti o n 
women’s health, pediatrics, geriatrics, etc.) 
Clinical research informatics:  The discovery and management of new knowledge relating to health and 
disease. It includes management of information related to clinical trials. 
C o m p u t e d  t o m o g r a p h y  ( C T  o r  C A T ) : A technique that uses numerous 2D x-ray slices, to create a 
three-dimensional view of the body. 
Cognitive systems:  A series of artificial intelligence paradigms with “the ability to engage in abstract 
thought that goes beyond immediate perceptions and actions.

thought that goes beyond immediate perceptions and actions. 
Combined DNA Index System (CODIS) program: The Federal DNA Identification Act in 1994, estab­
lished this national identification index of DNA records. 
Clinical Context Management Specifications (CCOW): CCOW is a standard for allowing independent 
systems to synchronize context on a single workstation, providing a seamless interface for the 
user of that workstation (ensuring consistent user authentication, display of the same patient, 
display of the same order, etc.) 
Consumer Health Informatics:  The field “devoted to informatics from multiple consumer or patient 
views. These include patient-focused informatics, health literacy and consumer education.” 
own health, for example, health information literacy, consumer-friendly language, personal

own health, for example, health information literacy, consumer-friendly language, personal 
ics analyzes consumers’ need for information. 
Continuity of Care Record (CCR):  A subset of information focused on timely care of an individual 
either in an emergency situation or provided to another physician focusing on current health 
status, medications, and treatment. 
Continuous positive airway pressure (CPAP): A technique for assisting breathing by maintaining the 
air pressure in the lungs and air passages constant and above atmospheric pressure throughout 
the respiratory cycle.

404 Glossary 
 
Core Measures: A set of quality indicators defined by the Centers for Medicare and Medicaid Services.
 
Critical Care: The specialized care of patients whose conditions are life-threatening and who require 
Cross Match: In transfusion medicine, refers to the testing that is performed prior to a blood transfu­
sion in order to determine if the donor’s blood is compatible with the blood of the intended 
Council on Ethical and Judicial Affairs (CEJA): A council that focuses on periodic updates of the Code 
of Medical Ethics. 
Data mining:  The process of finding previously unknown patterns and trends in databases and using 
that information to build predictive models.

that information to build predictive models. 
Defense in Depth: A security measure that involves layers, similar to an onion, of security to ensure any 
breach that occurs can be detected and repulsed. 
Dependent variable: (response variable) A variable in a functional whose relation and value are deter­
mined by the values assumed by other variables  in the relation. 
Depolarization:  Muscle cells, cardiac myocytes, are made up of negatively charged cells, when positive 
2+), sodium (Na+), and potassium (K +), the polarity 
of the cell becomes positive and the cell contract (negative to positive membrane potential). 
Diastole: The relaxation of the heart muscle,  accompanied by the filling of the chambers with blood. 
Initially both atria and ventricles are in diastole, and there is a period of rapid filling of the

Initially both atria and ventricles are in diastole, and there is a period of rapid filling of the 
ventricles followed by a brief atrial systole. At the same time, there is a corresponding decrease 
in arterial blood pressure to its minimum, normally about 80 mm of mercury in humans. 
Digital Communications and Communications in Medicine (DICOM):  The DICOM standard facili­
tates interoperability of medical imaging equipment by specifying; network communications , 
a set of protocols to be followed by devices claiming conformance to the standard; the syntax 
and semantics of commands  and associated information, which can be exchanged using these 
protocols; media communication , a set of media storage services to be followed by devices 
claiming conformance to the standard, as well as a file format and a medical directory struc­
ture to facilitate access to the images and related information stored on interchange media,

ture to facilitate access to the images and related information stored on interchange media, 
information that must be supplied with an implementation for which conformance to the stan­
dard is claimed. 
Digital radiography:  A technique that replaces photographic film with x-ray sensors. It is used primar­
ily by dentists. 
Electrochemistry:  “A science that deals with the relation of electricity to chemical changes and with the 
Electrocardiogram (EKG):  A device that measures the electrical activity of the cardiac muscle of the 
heart. 
Electrotonic spread:  A change in membrane potential (e.g., a receptor potential or synaptic poten­
tial) originating in one region of a cell ( ∆V
that distribute and flow intra- and extracellular to adjacent membrane regions (at distance 
d), where they in turn cause changes in membrane potential ( ∆V(d) ). However, the underly­

ing currents get progressively smaller with distance because fractions of them are diverted 
through transmembrane ion leak channels. Thereby, the elicited adjacent membrane potential 
changes ( ∆V(d) ) are reduced in size and altered in shape (electro tonic decrement). http:// 
www.springerreference.com/docs/html/chapterdbid/116505.html 
Electrolytes:  Minerals in the blood and other body fluids that carry an electric charge. The primary elec­
trolytes in the body are potassium, sodium, calcium, magnesium, chloride, and phosphorous. 
Electronic health record (EHR)*:  A  c o ll e cti o n  o f  h e al th  da ta  fr o m  m ul ti p l e  s o ur c e s .  Thi s  i s  a more 
expansive term , versus EMR, and refers to all information of the health of the body. It is

Glossary 405 
designed to share information among providers and includes all laboratory information and 
specialist data (used almost exclusively by the Office of the National Coordinator (ONC) for 
Health Information). 
EHR-S: Functional Model (FM) Release 2 2014: “outlines important features and functions that should 
be contained in an EHR system.” Through the creation of functional profiles, this model pro­
vides a standard description and common understanding of functions for healthcare settings. 
Electronic medical record (EMR):  Records used for diagnosis and treatment, refers to medical treat­
ment and history and is a digital form of a medical chart and often refers to information gath­
ered in a local practice. (It is often used, but EHR is the preferred term.) 
Electronic Protected Health Information (ePHI):  Guidelines to ensure patient confidentiality. 
Electronic medication administration record (eMAR):  A method of listing the medications that are

End diastolic pressure:  The pressure in the ventricles at the end of diastole, when the ventricle is filled 
Endotracheal tube: A hollow, flexible tube that is inserted via the mouth, through the vocal chords and 
Excitation-contraction coupling (ECC):  The process whereby an action potential triggers a myocyte 
Expert systems:  Computerized applications that combine computer hardware, software, and special­
Fast Health Interoperable Resources (FHIR):  (hl7.org/fhir)—“is a next generation standards frame­
work (2014) created by HL7. It combines the features of HL7’s Version 2, Version 3 and CDA
®

® 
product lines while leveraging the latest web standards and applying a tight focus on imple­
mentability for mobile phone apps, Cloud communications, EHR-based data sharing, server 
communications. 
Foley catheter: A flexible catheter that is inserted through the urethra and into the bladder for the 
purpose of draining urine. 
The Functional Magnetic Resonance Imager (fMRI) 1990s: measures brain activity and neural  activity 
G I F T  ( G N U  i m a g e  fi n d i n g  t o o l ) : is an open framework system. http://www.gnu.org/software/gift/ 
GNU (Gnu’s Not Unix), a UNIX-like operating system, incorporates tools to query images. It 
allows you to create your own index of images.

allows you to create your own index of images. 
HCAHPS: An initiative “to provide a standardized survey instrument and data collection methodology 
Health informatics:  Is “the interdisciplinary study of the design, development, adoption and applica­
tion of IT-based innovations in healthcare services delivery, management and planning.” 
Heath Insurance Portability and Accountability Act (HIPAA):  Th e  A c t  o f  1 9 9 6  t h a t  r e q u i r e d  t h e 
Health and Human Services (HHS) to develop standards for Electronic health records, data 
interchange, security, and unique EHR identifies for records.

interchange, security, and unique EHR identifies for records. 
HITEC ACT, part of the ARRA, was adopted and provided almost $20 billion in funding to 
help hospitals and physicians make their transition to EHRs. 
metabolic demands as a result of impaired cardiac pump function. 
Health information exchange (HIE): is the ability to share/exchange medical information across differ­
ent medical records systems. http://www.healthit.gov/HIE

1. There are a number of triggers called danger-associated molecular patterns (DAMPs) that can 
d
ifferentiate between healthy and unhealthy cells. 
 a.	  The innate immune system recognizes molecules via the innate immune system by pattern recog­
nition receptors triggered by cell death or injury 
 b. DAMPS are often derived from the plasma membrane, nucleus, endoplasmic reticulum, and cyto­
sol and mitochondria. 
 1. Pathogen-associated molecular patterns (PAMPs) another set of triggers generated by bacteria 
and viruses. 
 a. Delivery of PAMPs to their respective receptors constitute part of the initiated innate immune 
control. 
Inference engines:  Engines that determine which rules match those of the supplied data and match 
those with the highest probabilities. 
Informatics: The “field of study to apply information technology to another field—from healthcare to 
journalism to biology to economics” (Indiana University).

The Hospital Value-Based Purchasing (VBP) Program:  A Centers for Medicare & Medicaid Services  
(CMS) initiative that rewards acute-care hospitals with incentive payments for the quality of 
Hospital Readmission Reduction Program (HRRP):  The HRRP imposes financial penalties on hospi­
tals for “excess” readmissions when compared to “expected” levels of readmissions. 
406	 Glossary 
Health and Information Management Systems Organization (HIMSS):  A global nonprofit organiza­
tion focused on health IT. 
Health Level 7 International (HL7):  A standards organization that provides a framework for medical 
data exchange and sharing and standards that software organizations use to ensure for data 
interoperability. It is a nonprofit organization with members that represent a large percentage 
of all EHR development organizations. HL7 is an American National Standards International

of all EHR development organizations. HL7 is an American National Standards International 
(ANSI) accredited standard for healthcare. The level 7 refers to the International Standards 
Organization (ISO) seventh level, the highest achievement of software integration and usabil­
ity of the ISO seven layer models. 
Hemoglobin: An iron-containing protein bound to red blood cells and makes up nearly all the oxygen 
present, with the exception of a small amount dissolved in the plasma. It is a metalloprotein­
ase, a generic term for a protein that contains a metal ion cofactor. 
HIPAA Title II: A standard that describes security and privacy that sets limits and conditions on the use 
blood when the kidneys no longer function.

Hemodynamic monitoring:  The expert collection and analysis of qualitative and quantitative data of 
cardiopulmonary function. Fluid-filled monitoring systems are attached intravascular cath­
eters and are used for continuous invasive measurement of arterial and cardiac pressures. 
The HIPAA Privacy Rule: A rule that establishes national standards to protect individuals’ medi­
cal records and other personal health information and applies to health plans, healthcare 
clearinghouses, and those healthcare providers that conduct certain healthcare transactions 
electronically. 
The HIPAA Security Rule:  A rule that establishes national standards to protect individuals’ electronic 
personal health information that is created, received, used, or maintained by a covered entity.

personal health information that is created, received, used, or maintained by a covered entity. 
The Hippocratic Oath: Dating back the fifth century BC, describes the responsibility of physicians to 
focus on the well-being of their patients. 
The Immune System: “The immune system is a network of cells, tissues, and organs that work together 
to protect the body from infection.” (NIH) 
Immune System Response:

Glossary 407 
Independent variable: (explanatory variable) In mathematics, is a variable whose value determines the 
Infusion pump: A medical device that delivers fluids, including nutrients and medications such as anti­
Inductive charging:  is a method by which a magnetic field transfers electricity from an external source 
Institutional Review Board (IRB) or Privacy Board 
International Statistical Classification of Diseases and Related Health Problems (ICD9-10):  Created 
by the World Health Organization (WHO), it provides a list of codes, symptoms, diseases, and

by the World Health Organization (WHO), it provides a list of codes, symptoms, diseases, and 
social issues related to diseases. It has over 14,000 codes to ensure medical documents clearly 
refer to similar medical conditions to later be cross referenced to track epidemics and treat­
ment. Example of some of the categories is A00-B99 Infectious and Parasitic Diseases, F00-F99 
Mental and Behavioral Disorders, I00-I99 Diseases of the Circulatory System. 
ICD Clinical Modification (CM): version 10 (ICD 10 CM)  is maintained by the Center for Medicaid 
and Medicare Services (CMS) and is a U.S. national code, that provides more details than the 
The Institute of Electrical and Electronics Engineers (IEEE) Standards Organization (SA):  An orga­
nization that develops standards for the interoperability electronic of devices. 
The international Health Terminology Standards Development Organization (IHTSDO): A  nonprofit

The international Health Terminology Standards Development Organization (IHTSDO): A  nonprofit 
organization in Denmark. It owns SNOMED CT. http://www.ihtsdo.org/ 
The Integrating the Healthcare Enterprise IHE http: //ihe.net/ A non-profit organization created by 
the U.S. Healthcare Industry and the Radiology Group of North America (RGNA) and sup­
ported by Health Information Management Systems Society (HIMSS). 
The Institute of Medicine (IOM):  An independent, nonprofit organization that works outside of gov­
ernment to provide unbiased and authoritative advice to decision makers and the public. It 
was established in 1970 and is the health arm of the National Academy of Sciences, which was 
Interdisciplinary Plan of Care (IPOC): The goal of IPOC is to support continuity, quality, and safe 
ary team.

ary team. 
Intra-Aortic balloon pump (IABP): A mechanical device that is inserted via the femoral artery. It is 
Korotkoff sounds: Sounds that medical personnel listen for when they are taking blood pressure using 
a noninvasive procedure. There are five Korotkoff sounds but only two are primarily used for

a noninvasive procedure. There are five Korotkoff sounds but only two are primarily used for 
blood pressure: systolic (first) and diastolic (fourth: within 10 mmHg above the diastolic blood 
pressure). Some devices also use the fifth. The other three are used to detect heart disease. 
Logical Observation Identified Names and Codes (LOINC): Database used to identify medical labora­
tory observations. 
Lymphocytes: Adaptive immune cells—B cells and T cells are responsible for mounting responses to 
specific microbes based on previous encounters (immunological memory). 
Lymphatic system: A network of vessels and tissues composed of lymph, an extracellular fluid, and lym­
phoid organs, such as lymph nodes . Immune cells are carried through the lymphatic system 
and converge in lymph nodes, which are found throughout the body.

408 Glossary 
mHealth: Stands for mobile health. It is remote medical care supported by mobile devices. 
Magnetic resonance image (MRI):  or Nuclear MRI MRI’s utilize non-ionizing absorption and emis­
sion in the Radio Frequency (RF) and is best suited for non-calcified i.e. soft tissue.
 
Mean arterial pressure (MAP): The average pressure in a patient’s arteries during one cardiac cycle. It is
 
considered a better indicator of perfusion to vital organs than the systolic pressure. 
Meaningful use:  Defined by the Center for Medicare and Medicaid Services (CMS) as a series of stan­
dards and incentive programs used as criteria for physician reimbursement. 
Medical informatics:  (Often used interchangeably with biomedical informatics but the term “bio­
medical” is currently the preferred term used by the leading informatics body in this field, 
the AMIA) “is the science and art of modeling and recording real-world clinical concepts

the AMIA) “is the science and art of modeling and recording real-world clinical concepts 
and events into computable data used to derive actionable information, based on expertise in 
medicine, information science, information technology, and the scholarly study of issues that 
impact upon the productive use of information systems by clinical personnel.” [S. Silverstein, 
MD]. 
Medical logic modules (MLMs):  Modules containing knowledge for a single medical diagnosis 
decision. 
Mini-clinics:  are walk in clinics usually staffed by physicians assistants or registered nurses (RNs) to 
treat non-acute medical conditions. 
Motor cortex: is the region of the cerebral cortex involved in the planning, control, and execution of 
voluntary movements. 
The primary motor cortex  generates neural impulses sent to the spinal cord that control the 
execution of movement. 
The supplementary motor area (SMA) , involved in the planning of movement, planning of

The supplementary motor area (SMA) , involved in the planning of movement, planning of 
sequences of movement, and the coordination of the two sides of the body. 
Nationwide Health Information Network (NHIN):  Also called eHealth Exchange  developed by the 
U.S. Office of the National Coordinator (ONC) for Health Information Technology, is a series 
of specifications to securely exchange health data. The goal of the ONC is to tie together HIEs 
to create a nationwide network. 
National Patient Safety Goals:  In 2002, The Joint Commission established its National Patient Safety 
Goals (NPSGs) program. The NPSGs were established to help accredited organizations address 
specific areas of concern in regard to patient safety. 
concern to both the public and healthcare professionals and providers, clearly identifiable and

Nursing informatics:  The “science and practice (that) integrates nursing and implementation of com­
Office of the National Coordinator (ONC) for Health Information Technology: The office at the fore­
front of the administration’s health IT efforts and is a resource to the entire health system 
to support the adoption of health information technology and the promotion of nationwide 
health information exchange to improve healthcare. ONC is organizationally located within 
the Office of the Secretary for the U.S. Department of Health and Human Services (HHS) 
Ohms law: V = I × R [Voltage = Current (I) (times) Resistance] describes the relationship between volt­

age, also called potential difference, which is the force that moves, or pulls, electrons through 
the wire. 
Oxyhemoglobin: The oxygenated hemoglobin (HbO
2) saturation is the ratio, expressed as a percentage 
of the amount of oxyhemoglobin relative to the total amount of hemoglobin in blood.

Glossary 409 
Personal health records (PHR):  is a personal copy of your health information so you can track, main­
tain, and make informed medical decisions. All doctors are required to provide this informa­
tion upon request. It is a subset of the EHR and usually contains personal information, medical 
tests, diagnoses, medications, allergies, and family history. 
Peukert’s law: The efficiency factor for discharging a battery. Batteries ratings are quantified between 
the relationship between capacity, current, and discharge time. Qp = capacity when discharged 
at 1 amp/hr, I = amount of current drawn, k is a constant around 1.3: t = Qp/I
k

k 
Pharmacy CDSS:  A system in widespread use and is usually integrated with E-prescription systems. It 
checks drug interactions, contraindications, allergies, dosage levels, and reports possible side 
effects. 
Picture archiving and retrieval system (PACS):  A storage and retrieval system for medical images. 
Positron emission tomography (PET):  A nuclear medicine medical imaging technique that produces 
a three-dimensional image or map of functional processes or metabolic activities in the body. 
objective is to increase the time for oxygen-carbon dioxide exchange as well as to facilitate re-

expansion of the alveoli on the next inspiration. 
Predictive analytics:  The practice of extracting information from existing data sets in order to deter­
the future. It forecasts what might happen in the future with an acceptable level of reliability, 
and includes what-if scenarios and risk assessment (www.webopedia.com). 
or shearing forces. 
Privacy rule:  A rule that sets federal standards to protect individuals personal health information 
(PHI) and limits to disclosure without patient authorization : Electronic Protected Health 
Information (ePHI). 
Public key encryption systems (PKE):  An asymmetric system that uses different keys to encrypt and 
decrypt.

decrypt. 
and out into the pulmonary artery. Normal pressures are 9–18 mmHg/ 6–12 mmHg. 
Radio Frequency Identification (RFD):  The wireless noncontact use of radio frequency electromag­
netic fields to transfer data, for the purposes of automatically identifying and tracking tags 
attached to objects. 
Regional Health Information Organization (RHIO):  o ft e n  us e d  in t e r c h an g e a b l y  wi th  an  HIE,  i s  a

Regional Health Information Organization (RHIO):  o ft e n  us e d  in t e r c h an g e a b l y  wi th  an  HIE,  i s  a 
group of companies, hospitals or organizations that have developed a system for seamless 
exchange of health information. 
Reference coordinate system (RCS):  The RCS is the spatial coordinate system in a DICOM frame of 
reference. 
HL7 Reference information model (RIM): is an object model that provides a pictorial representation of 
HL7 clinical data domains. It identifies the life cycle of message groups that are moved between 
domains of the model. It provides software developers with the architecture for information 
exchange between EHR in accordance with HL7 standards.

410 Glossary 
The Regenstrief Mapping Assistant (RELMA):  is a search tool for the LOINC clinical database. 
Retina: is a light-sensitive layer of tissue made up of photoreceptor cells located at the back of the eye. 
It is made up of rods that are used in peripheral vision, and cones, responsible for color vision. 
Sinoatrial node (SA): is located in the right atrium where the superior vena cava joins the atrial tissue; 
the SA node acts as the main pacemaker in the heart. 
Skin: Usually the first line of defense against microbes. Skin cells produce and secrete important anti­
microbial proteins, and immune cells can be found in specific layers of the skin.

microbial proteins, and immune cells can be found in specific layers of the skin. 
STAT: A medical abbreviation for urgent or rush. Something ordered as STAT must be done immediately. 
messages. 
Systemized Nomenclature of Medicine (SNOMED) Clinical Terms (CT):  The most comprehensive 
international medical classification available with 300,000 medical codes to support medical 
documentation, as of 2013. 
Systole: is the period of contraction of the ventricles of the heart in a single heart beat. Systole causes the 
ejection of blood into the aorta (left) and lungs (right ). During systole, arterial blood pressure 
reaches its peak, which is normally about 90–120 mm of mercury in humans. 
SVO

SVO
oxygen returned to the heart by the venous system. Normal SVO
2 is between 60% and 80%. 
Telehealth: is an all-inclusive term encompassing remote healthcare and all its support. 
Telemental health: Similar to the other “tele” definitions, it is defined as providing behavioral/mental 
health services, substance abuse, crisis intervention, and education remotely—services that are 
delivered using the Internet and wireless communications. 
Telemedicine: is the use of medical information exchanged from one site to another via electronic com­
munications to improve a patient’s clinical health status. It is the technology used for the deliv­
ery of remote clinical services.

ery of remote clinical services. 
Telesurgery: A robotic system that can perform surgeries remotely, also referred to as telepresence, with 
higher accuracy and smaller incisions, that reduce the postoperative recovery period. 
Thymus: T cells mature in the thymus, a small organ located in the upper chest. 
Tracheotomy: A surgical procedure to create an opening through the neck into the trachea. A tube is 
Transformer equation: An equation that relates to the turns of wire on the coil; that is, a coil is wire 
wrapped around a metal post a few thousand times. The equation relates the voltage between 
the first, primary coil, to the secondary coil: V
p/Vs = Np/Ns.

p/Vs = Np/Ns. 
Translational Bioinformatics:  The development analytic methods to optimize the transformation of 
health. 
Unified Medical Language System (UMLS):  A mapping system and toolset used to convert between 
different medical vocabularies. It is used by Medical Informatics developers. It contains 
approximately 5 million concepts names and 1 million concepts and relationships between 
names and terms. 
Urgent care center: is a broad term that is defined as “the provision of immediate medical service offer­
ing outpatient care for the treatment of acute and chronic illness and injury.”

Glossary 411 
Venous oxygen saturation (SvO 2) (range 65%–75%): Percentage of oxygen bound to hemoglobin in 
inside a part of the body. The most common sites are in the large veins in the lower leg and 
thigh. The danger is that when a clot breaks off and moves through the bloodstream as an 
embolism it can lodge in the lungs. 
Ventricular assist device:  A mechanical pump designed to support heart function and blood flow. 
Virtual private network (VPN):  allows you to send information securely over the internet as if it was

Virtual private network (VPN):  allows you to send information securely over the internet as if it was 
your own private network. It sets up a virtual point to point connection, that is, a permanent 
link between two users, using either dedicated connections, encrypting the traffic or virtual 
tunneling protocols that appear as public messages. 
Wireless medical devices: are defined as “any medical monitoring technology, worn or implanted, that 
gather physiological information.”

A 
ABG, see Arterial blood gases (ABG)
 
ACA, see Affordable Care Act (ACA)
 
ACLS, see Advanced cardiac life support (ACLS)
 
Acute coronary syndrome (ACS), 285
 
“Add_item_holder,” 376
 
“Add item.ht m l,” 376
 
Adenosine triphosphate (ATP), 168, 180, 184, 202–203
 
Advanced cardiac life support (ACLS), 286, 299
 
Advanced practice registered nurse (APRN), 148
 
Affordable Care Act (ACA), 2, 327, 329
 
CMS, meaningful use, 40– 41 
conditions, 38– 40
 
American Dental Association (ADA), 98, 331
 
American Health Information Management
 
Association (AHIMA), 50
 
American Medical Association (AMA) Ethics Groups
 
CEJA policy functions, 254–255
 
judicial functions, 254–255
 
Litigation Center, 255–256
 
medical ethics organization, 254
 
principles, published in 2001, 254–255
 
American Medical Informatics Association (AMIA)
 
core biomedical competencies, 8
 
specific core competencies
 
biological foundations, 9–10
 
human and social context, 9–10
 
procedural knowledge, 9–10

technological approach, 8– 9
 
American Nurses Association (ANA) of Ethics, 256–257 
American Recovery and Reinvestment Act (ARRA), 49
 
acceleration, 57
 
by Congress, 63
 
funding initiatives, 49
 
Incentive Reimbursement Program, 41
 
State Health Information Exchange Cooperative 
Agreement Program, 66
 
of 2009, U.S. EHRs
 
evolution and adoption, 28
 
HITECH Act, 37–38
 
Index
 
American Telemedicine Association (ATA), 142, 148
 
AMIA, see American Medical Informatics 
 
Analyze-7.5 fMRI imaging format
 
structure, 234
 
Voxel fMRI image elements, 234
 
Anatomy and Physiology (A&P) primer
 
brain, 197
 
cells, 203–204
 
digestive system, 207
 
eye, 202
 
gallbladder, 207
 
hearing, 204
 
heart
 
arrhythmia, 201
 
electrical system, 200–201
 
immune system
 
AIDS, 210
 
antibodies, 213
 
DAMPs, 211
 
leukocytes, 213–214
 
lymph system, 212

AIDS, 210
 
DAMPs, 211
 
neutrophils, 213–214
 
PAMPs, 211
 
white blood cells, 212–213
 
kidneys, 205
 
liver, 206
 
lungs
 
anatomy, 210
 
pulmonary capillary, 209
 
muscles, 199
 
neurons and nervous system, 
196–197
 
pancreas/diabetes, 205
 
spinal chord, 198
 
Application skeleton, 372
 
APRN, see Advanced practice registered
 
nurse (APRN)
 
ARRA, see American Recovery and 
Reinvestment Act (ARRA)
 
413

414 Index 
Arterial blood gases (ABG) 
femoral artery, 183
 
laboratory tests, 279
 
pulse oximetry, 181
 
Augmented diastolic, 272, 302
 
Automaticity, 178
 
B 
Bachelor’s in medical/biomedical informatics
 
bachelor’s degree, 12
 
BS programs, 11
 
credits, 13
 
employment prospects, 12
 
Batteries; see also Electrochemistry
 
classification, 172–173
 
energy density levels, 173
 
lithium ion, 170
 
medical sensors, 165
 
Peukert equation, 170, 172
 
standard clinical environments, 92
 
zero voltage, 168
 
Beer–Lambert law, 182
 
Big data in healthcare
 
body sensor network research
 
Big Data Algorithms, 189–190
 
BSN data, 189–190
 
data analysis, 191–192
 
data generation, 191–192
 
testing methodology, 190–191
 
definition, 189
 
Bioinformatics, 4, 8
 
Biomedical engineering, 5, 311,
 
314–315
 
Biomedical informatics (BMI)
 
ADA, 331
 
auto data entry, EHRs, 340
 
BMI predictive analytics ( see BMI predictive 
analytics)
 
categories and time frames, 330
 
CDC data, 330

ADA, 331
 
challenges, 6–7
 
curriculum
 
AMIA (see American Medical Informatics 
Association (AMIA))
 
NLN (see National League for Nursing 
Informatics (NLN))
 
distributed healthcare, 332
 
eDoctor, 333
 
EDRs, 331
 
EHR(2), 332–333
 
EHR(3), 334
 
energy-efficient light bulbs, 338
 
global integration, 339
 
HCAHPS score (see Hospital Consumer
 
Assessment of Healthcare Providers and 
Systems (HCAHPS) score)
 
HHS mandates, 331
 
in hospitals, 332
 
intelligent assistants, 339
 
intelligent medical kiosks, 334
 
intelligent vehicles, 338
 
and IT, 2
 
LIFE record, 338
 
long term distributed healthcare, 333
 
Medicare and Medicaid reimbursement, 331
 
meteorology, 338
 
Microsoft office suite, 332
 
nomenclature
 
definition, 2
 
descriptors, 4–5
 
organization of topics, 2–3
 
syntax, 4
 
nonhospital medical devices, 332

syntax, 4
 
150-year life span, 339
 
physicians access, 333
 
political uncertainties, 331–332
 
predictions (see Predictions)
 
predictive analytics, 340
 
analysis of results, 337
 
contributing factors, 335
 
cost factors, 335
 
intangible cost factors, 336–337
 
mandate factors, 335–336
 
PCF, 335
 
predictive factors, 334–335
 
requirements and optional concentration, 7
 
sociological advances, 340
 
stem cell research, 339
 
stimulus individually, 322
 
thermostat, 338
 
transportation, 338
 
universal medical access, 340
 
Windows 7-8 operating systems, 332
 
Biomedical predictive analytics
 
BMI, 325
 
cost factors (predictive weights), 327
 
external mandates, 327–328
 
HITECH, 325
 
intangible costs, 328
 
PCFs, 325–327
 
UFT, 325
 
Biometrics
 
architecture, 133–134
 
DNA scanner, 133
 
fingerprint scanner, 132–133
 
iris scanners, 132
 
Blood pressure

UFT, 325
 
air speed and altitude, 284
 
central vein, 279
 
patient’s ECG rhythm, 300
 
systolic/diastolic and mean, 272
 
Blood type and products, 216–217, 273
 
BMI, see Biomedical informatics (BMI)

415 Index 
Body sensor networks (BSN), 186
 
Bone marrow, 212–213
 
Braden scale, 285
 
Brain stem, 17, 197
 
C 
Cardiac arrest, 201, 286, 299
 
Cardiac index (CI), 272
 
Cardiac myocyte, 177–178
 
Cardiac output (CO), 183, 272–273
 
Cardiac rhythm, 272, 300
 
Cardiogenic shock, 272
 
Cardiothoracic intensive care unit (CTICU),
  
299–300 
Cascading Style sheet (CSS)
 
add_item.css, 390–391
 
class name, 382
 
element’s ID, 382
 
history.html, 389–390
 
HTML tag name, 383
 
medical-based application, 381
 
processing power, 386
 
profile page, 384–385
 
properties, 392
 
settings.css page, 386–388
 
toggle_edit_info element, 388
 
user interfaces, 381
 
web application, 383
 
CCOW,  see Clinical context management 
specifications (CCOW) 
CCR,  see Continuity of care record (CCR) 
CCRN,  see Critical care registered nurse (CCRN) 
CDA,  see Clinical document architecture (CDA) 
CDSS,  see Clinical decision support system (CDSS) 
CEJA,  see Council on Ethical and Judicial Affairs 
(CEJA)

(CEJA)
 
Center for Disease Control (CDC), 326, 330, 334
 
Centers for Medicare and Medicaid Services (CMS), 40
 
reimbursement, 270
 
and TJC, 277
 
zero tolerance, 302
 
Central lines, 262–263
 
Central venous pressure (CVP), 272
 
Cerebellum, 197
 
Cerebral cortex, 197
 
Chest tubes, 281
 
Chief Information Office (CIO), 316
 
CIS,  see Clinical information system (CIS)
 
CLEF,  see Conference and Labs of the Evaluation 
Forum (CLEF) 
Clinical context management specifications (CCOW), 
86–87 
Clinical decision support system (CDSS)
 
artificial intelligence software, 264
 
expert systems, 264
 
HL7 , 72–73
 
neur
 al networks (see Neural networks) 
pharmacy, 74
 
Clinical document architecture (CDA), 87
 
Clinical information system (CIS), 25, 293, 314
 
Clinical nurse specialist (CNS), 5–6, 158
 
Clinical research informatics, 5
 
CMS, see Centers for Medicare and Medicaid

CMS, see Centers for Medicare and Medicaid 
Services (CMS) 
CNS, see Clinical nurse specialist (CNS) 
CODIS, see Combined DNA Index System 
(CODIS) program 
Cognitive systems
 
AI paradigms, 76
 
and crowd-based expert systems, 75
 
structured representations, 76
 
Combined DNA Index System (CODIS) program
 
candidate matches , 133
 
database, 133
 
FBI, 133
 
matching algorithm, 133
 
sex offenders, 133
 
Communications, interoperability
 
electronic health information, 108
 
HL7 and medical vocabularies, 82
 
ISO TC 215, 91
 
medical communications standards, 84
 
NCPDP, 85
 
OSI, 90
 
C
omputed axial tomography (CAT), 235–236 
Computed tomography (CT), 226, 235–236 
Conference and Labs of the Evaluation Forum (CLEF) 
GNU Image-Finding Tool, 244, 247
 
LIRE, 244
 
Consumer health informatics, 5
 
Context Management Specification (CCOW), 86–87
 
Continuity of Care Record (CCR)
 
electronic CCRs, 52

LIRE, 244
 
features, 52–53
 
healthcare setting, 52
 
HL7 message/CDA, 52
 
patient’s health status, 52
 
Continuous positive airway pressure (CPAP), 272
 
Continuous renal replacement therapy (CRRT), 273
 
Core measures, 285, 290, 302
 
Council on Ethical and Judicial Affairs (CEJA), 
253–255 
CPAP, see Continuous positive airway pressure (CPAP) 
CPT, see Current procedural terminology (CPT) 
Critical care registered nurse (CCRN) 
da Vinci Surgical System, 147
 
eligibility criteria, 148
 
hysterectomies and pros, 146
 
tele-ICU/e-ICU, 146
 
Critical care unit, EHR
 
blood products, 273
 
HACs, 274
 
IV infusion, 272–273

416 Index 
MAP, 272
 
medical and nursing care, 274
 
urine drainage, 273
 
ventilator, 272
 
Cross match, 273
 
CRRT,  see Continuous renal replacement 
therapy (CRRT) 
CSS,  see Cascading Style sheet (CSS) 
Current procedural terminology (CPT) 
HCPCS, 104–105 
medical procedures, 102
 
CVP,  see Central venous pressure (CVP)
 
Cyber security for medical devices
 
FDA warnings, 136
 
healthcare facilities, 136
 
morphine drips and chemotherapy, 137
 
pacemakers/medical delivery systems, 136
 
systems/monitors, 135
 
D 
Danger-associated molecular patterns (DAMPs), 211
 
Data acquisition, medical sensors 
blood pressure, 180–181 
electrical conduction system, heart ( see Electrical  
conduction system, heart) 
neurons
 
architecture, 183
 
electrotonic spread, 184–185
 
and signal transmission, synapses, 
183–184 
sodium–potassium pumps, 184
 
pulse oximetry ( see Pulse oximetry)
 
sensors, 176
 
Data mining
 
definition, 221
 
drug effectiveness and treatment, 218
 
in healthcare

large data sets, 194
 
NSF and NIH research initiatives, 189
 
smart health data transmission projections, 195
 
telemedicine technologies, 195
 
Decision support systems (DSS), 85
 
Defense in depth
 
analogy, 129
 
information assurance, 130–132
 
nonrepudiation, 129
 
strategies, 129–130
 
Dependent variable, 325
 
Depolarization, 178
 
Diastole, 180, 200
 
DICOM,  see Digital Imaging and Communications in 
Medicine (DICOM) 
Digital/computed radiography
 
digital panoramic x-rays, 240, 242
 
film-based system, 239
 
x-ray sensors, 239
 
yearly radiation dosages, 240–241
 
Digital Imaging and Communications in Medicine 
(DICOM), 53, 55, 66, 82
 
architecture, 226
 
conformance, data flow diagrams, 
227–228
 
data dictionary, 232
 
data structures and encoding
 
nested value elements, 231
 
overlay data encoding, 232

227–228
 
message service elements, 232–233
 
object-oriented data models and service classes
 
generic code, 228–229
 
image data elements, 230
 
image metadata, 230
 
IODs, 229
 
orientation, 3D space, 230
 
reference coordinate system, 230
 
preliminary imaging standards, 224, 226
 
standard facilitates interoperability, 227
 
terms, 227
 
Digital medical image processing 
architecture, 247–248 
dimensionality reduction, signals in mapping, 
248–249
 
feature extraction, 247
 
principal component analysis, 247–248
 
Distributed healthcare
 
cost–benefit trade-offs, 151
 
mHealth devices, 152
 
UCAO
A, 151
 
Document-type definition (DTD), 107–108 
E 
ECC, see Excitation–con traction coupling (ECC)
 
EHRs, see Electronic health records (EHRs)
 
EHR-S Functional Model (FM), 85
 
EKG, see Electrocardiogram (EKG)
 
Electrical and chemical conduction primer

conventional current flow, 167–168
 
electrochemistry ( see Electrochemistry)
 
electron current flow, 168
 
fiber optics, 174–175
 
Ohm’s law, 167–168
 
isotopes, 165
 
physical atoms, 165
 
standard model, elementary particles, 166–167
 
uranium isotopes and fission chain reaction, 
165–166 
Electrical conduction system, heart 
action potential
 
in cardiac nerves, 177
 
EKG, 176
 
excitation–contraction coupling, 177–178

417 Index 
ATP, 180
 
cardiac conduction system
 
definition, 178
 
intermodal pathways, 178–179
 
Electrocardiogram (EKG), 201
 
Electrochemistry
 
batteries
 
alkaline batteries (ZnMnO
2), 173
 
battery energy density levels, 173
 
“battery memory effect,” 172
 
classification, 170
 
and electrons, 171
 
lead–acid batteries, 172
 
lithium ion batteries (Li-ion), 173
 
nickel–iron rechargeable batteries (NiFe), 172
 
nickel–zinc rechargeable battery (NiZn), 172
 
conductors
 
electrons moving through wire, 
170–171
 
lithium ion battery, 170–171
 
valence electrons, 168–169
 
inductive charging
 
current circuit and coils, 174–175
 
definition, 174
 
physical connection, 173
 
Electrolytes, 170, 172, 273
 
Electronic dental records (EDRs), 331
 
Electronic health records (EHRs)
 
adoption statistics
 
implementation statistics, 57–58
 
Medicare and Medicaid reimbursement, 57
 
American Journal of Critical Care , 295
 
architecture
 
DICOM, 53

DICOM, 53
 
Health Level 7 Reference Information Model, 54
 
HIT, 55
 
ISO, 53
 
ISO seven-layer communication model, 
53–54
 
model, 55
 
system specifications, 56–57
 
Children’s Hospital of Pittsburgh, 294
 
CIS, 293
 
CMS, 270
 
computer-based systems, 270–271
 
Contemporary OB/GYN state, 295
 
Critical Care Nurse , 294
 
Crucial Conversations about Optimal Design, 294
 
data entry
 
barcode sticker, 60
 
hospitals and smaller practices, 57–58
 
human-centered input data, 60
 
LOINC codings, 60
 
manual flow sheets, 59
 
SNOMED CT, 60
 
user interfaces, 59
 
code screen, 299
 
computer-based, 297
 
device–EHR communication, 298
 
life-support devices, 298
 
loose-leaf-type paper, 296–297
 
paper-based, 298
 
rehabilitation/long-term acute care centers, 299
 
self-checkout registers, 297
 
standardization, 297
 
wish list , 298

evidence-based project, 293
 
Hands-on Automated Nursing Data System, 292
 
implementation, 46
 
implications, 295–296
 
information systems and services, 105
 
and interoperable biomedical information systems 
and services, 84
 
IOM, 270
 
knowledge page, 294
 
lifestyle choices, 49
 
messaging architecture, 109
 
nursing priorities
 
computer-based capability, 288
 
data entry, 290–291
 
data retrieval, 291–292
 
paper system, 287
 
patient’s hemodynamic status, 
287–288
 
reports, 290–291
 
Online Journal of Nursing Informatics , 292
 
patient care activities, 271
 
patient’s journey, 46
 
prototype, 46
 
regu
latory agencies, 293
 
Research with Information Technology, 295
 
review and document information, 294
 
synthesis, 49
 
taxonomy
 
CCR, 52–53
 
PHR, 49–51
 
timeline, 48
 
in 2025
 
bar-code scanning, 300–301

taxonomy
 
CCR, 52–53
 
PHR, 49–51
 
in 2025
 
controlled multispectral radiation, 302
 
CTICU, 299–300
 
ECG, 300
 
HCAAPS score, 301
 
hospitalization, 301
 
postoperative period, 301
 
tablet-to-tablet communication link, 303
 
vital signs and parameters, 302
 
voice-recognition feature, 300
 
UMLS definition, 114
 
in United States
 
ACA (see Affordable Care Act (ACA))
 
ARRA of 2009, 37–38

418 Index 
HIPAA (see Health Insurance Portability and 
Accountability Act (HIPAA))
 
mainframe evolution, 28
 
VistA, 28
 
vital signs and hemodynamic parameters, 271
 
Electronic medical record (EMR)
 
hospitals and smaller practices, 58
 
patient information, 49
 
Electronic medication administration record (eMAR),
 
275, 277, 291, 299–300
 
Electronic prescribing (e-prescribing)
 
Center for Medicare and Medicaid Services, 65–66
 
CMS, 65
 
medication errors, 64
 
MMA, 64
 
Electronic protected health information (ePHI); 
see also HIPAA Security Rule
 
healthcare organizations, 32
 
patient confidentiality, 31
 
Electrotonic spread
 
membrane potential, 184
 
voltage-gated channels, 183, 185
 
eMAR, see Electronic medication administration 
record (eMAR) 
EMR, see Electronic medical record (EMR) 
Encryption 
PKE, 134–135 
symmetric key, 134
 
End diastolic pressure, 302
 
Endotracheal tube, 272, 302
 
ePHI, see Electronic protected health

ePHI, see Electronic protected health 
information (ePHI)
 
Episodic vs. dynamic documentation, 272
 
Ethical medical situations
 
AMA code of medical ethics, 257
 
AMA Ethics Groups, 254–256
 
AMA patient care and student education, 
262–263
 
ANA code, 256–257
 
CDSS (see Clinical decision support system (CDSS))
 
definition, 252
 
Hippocratic Oath, 252–253
 
impaired drivers ( see Reporting impaired drivers)
 
medical students
 
clinical setting, 261
 
fellow students, 259
 
physicians gifts, industry, 260–261
 
resident questions order, physician, 263–264
 
surgical placebo, 259–260
 
trainees, procedure performance, 262–263
 
Excitation–contraction coupling (ECC), 177–178 
Expert systems, 75–76
 
architecture, 188
 
cognitive systems, 189
 
computerized applications, 188
 
inference engines, 188
 
F 
Fast Healthcare Interop erability Resources 
(FHIR), 86–87

F 
(FHIR), 86–87 
Federal Drug Administration (FDA), 135–136 
FHIR, see Fast Healthcare Interoperability 
Resources (FHIR) 
FIO
2, see Fraction of inspired oxygen (FIO 2) 
FMRI, see Functional magnetic resonance 
imager (fMRI)
 
Forward-chaining inference (FCI), 75, 188
 
2), 302
 
Functional magnetic resonance imager (fMRI), 238
 
G 
GNU image finding tool (GIFT), 244
 
Go-live decision, 320
 
H 
HACs, see Hospital acqu ired conditions (HACs) 
Health and Human Services (HHS), 149, 327–329
 
administrative simplification, 31
 
components, 31–32
 
fraud and abuse prevention, 32
 
HIPAA Privacy Rule, 32–33
 
HIPAA Security Rule ( see HIPAA Security Rule)
 
medical liability reform, 32
 
Health and Information Management Systems 
Organization (HIMSS), 57, 82, 92
 
Healthcare Common Procedure Coding System
 
(HCPCS), 104–105

Healthcare Information and Management Systems 
Society (HIMSS), 88, 92–93
 
Healthcare IT skills
 
biomedical engineering, 315
 
CIO and leadership team, 316
 
clinical informatacists, 316
 
competing forces, 316–317
 
development/programming, 316
 
hardware and software
 
interface programming, 315
 
software support, 315
 
technical staff, 315
 
project management, 314–315
 
security and asset protection, 316
 
telecommunications, 316
 
Health informatics, 4, 91
 
Health information exchange (HIE)
 
ONC, 66
 
patient demographics data, 66
 
types, 66–67
 
Health (HITECH) Act, 46, 325–326, 331
 
initial start-up costs, 28
 
U.S. EHRs, 37–38

Index 419 
Health Insurance Portability and Accountability Act 
(HIPAA), 46, 95, 331
 
components, 62
 
healthcare provider, 51
 
PACS system, 244
 
Privacy Rule entities, 51
 
Title II security framework, 46
 
U.S. EHRs
 
components, 29–30
 
group healthcare guidelines and 
enforcement, 37
 
health insurance reform, 31
 
HHS (see Health and Human Services (HHS))
 
ICD, 28
 
implementation dates, components, 28–29
 
tax simplification, 37
 
U.S. medical records, 46
 
Health Level 7 International (HL7)
 
communication protocols, 85
 
Communications Standards Categories, 
85–86
 
DSS, 85
 
IPV6 and routing packets, 85
 
ISO seven-layer model, 85–86
 
NCPDP, 85
 
standards nomenclatures, 85
 
angina, 215
 
blood types, 216–217
 
blood vessel diseases, 214
 
cancer, 217
 
cardiac catheterization test, 215
 
coronary artery, 215–216
 
coronary balloon angioplasty, 215–216
 
EKG, 215
 
stent placement, 216
 
Heart failure, 6, 272, 285
 
Hemodialysis, 279
 
Hemoglobin, 181–182

EKG, 215
 
HHS, see Health and Human Services (HHS)
 
HIE, see Health information exchange (HIE)
 
Hierarchical Data Format (HDF4/HDF5), 235
 
HIMSS, see Health and Information Management
 
Systems Organization (HIMSS) 
HIPAA, see Health Insurance Portability and 
Accountability Act (HIPAA) 
HIPAA Privacy Rule
 
ePHI, 32
 
NCVHS, 33–34
 
HIPAA Security Rule 
administrative safeguards
 
assigned security responsibility, 35
 
definition, 33
 
security management process, 33, 35
 
workforce security, 36
 
components, 33
 
technical safeguards, 36–37
 
exceptions, 124–125
 
healthcare operations, 125
 
HHS OCR, 124
 
privacy rule, 122, 124
 
public health, 125
 
regulations, 124
 
research, 126
 
“History.html,” 376
 
HITECH Act, see Health Information Technology for 
Economic and Clinical Health (HITECH) 
Act

Act 
HL7 , see Health Level 7 International (HL7) 
HL7 Decision Support Services 
Arden syntax for medical logic systems, 72
 
fuzzy data sets, 72–73
 
HL7 Reference Information Model (RIM)
 
class diagram, 88
 
EHR design process, 87–88
 
high-resolution link, 88
 
identifiers, 88
 
UML, 87
 
HL7 with Embedded SNOMED
 
CERNER electronic health record system, 110
 
codes in tables, 110
 
Health Level 7 header, 112
 
hierarchies, 111
 
HL7 message architecture, 108
 
HL7 message structure, 108
 
medical documentation, 110
 
Medical Subject Headings cardiovascular 
disease, 109
 
medical systems/electronic health records, 109
 
physiology, 111
 
SNOMED CT codes, 112
 
Hospital acquired conditions (HACs), 274, 285, 289,
 
296, 301
 
Hospital Consumer Assessment of Healthcare 
Providers and Systems (HCAHPS) score
 
Hospital Compare website, 330

296, 301
 
in March 2008, 328
 
penalties, 329
 
VBP and CMS, 329
 
Hospitalized patient
 
bar-code scanning, 277
 
computer-based system, 277
 
diagnosis and admission, 274
 
medication administration, 275–276
 
nursing activities
 
cardiothoracic intensive care unit, 280
 
cardstock Kardex, 284
 
computer-based system, 281
 
continuous medication infusions, 281
 
flow sheet, 281–282
 
foldout-type documents, 279
 
free-form Nursing Notes, 281

I 
420 Index 
loose-leaf paper, 279
 
pacemaker documentation, 284
 
pain documentation, 283
 
Stat Medications, 280
 
time-consuming searches, 283
 
ventilators-machines, 279
 
paper medication administration record, 
275–276
 
physiologic parameters documenting, 278–279
 
time-sensitive documentation, 275
 
Hospital Readmission Reduction Program 
(HRRP), 329
 
Hospital Value-Based Purchasing (VBP) Program, 329
 
HRRP, see Hospital Readmission Reduction 
Program (HRRP)
 
Hypertext Markup Language (HTML)
 
alt attribute, 370
 
Body tag, 368
 
Div, 368–369
 
Doctype tag, 367
 
Head tag, 368
 
Html5 Language Reference, 377–379
 
IMG, 370
 
inputs, 370–372
 
LIs, 369–370
 
SRC attribute, 370
 
text editor, 367
 
ULs, 369
 
IABP, see Intra-aortic ba lloon pump (IABP)
 
ICD, see International Statistical Classification of 
Diseases and Related Health Problems (ICD)
 
ICD clinical modification (CM), 99
 
IEEE Standards Association (SA), 91–92

IHE, see Integrating the Healthcare Enterprise (IHE)
 
IHTSDO, see International Health Terminology 
Standards Development Organization 
(IHTSDO)
 
Image Cytometry Standard (ICS), 235
 
Imaging
 
CAT (see Computed axial tomography (CAT))
 
CLEF, 244, 247
 
computed/digital radiography ( see Digital/
 
computed radiography)
 
description, 224–225
 
digital processing ( see Digital medical 
image processing)
 
Doppler effect, 239
 
fMRI (see Functional magnetic resonance 
imager (fMRI))
 
ImageCLEF tools, 244, 247
 
medical formats ( see Medical imaging formats)
 
MRI (see Magnetic resonance imaging (MRI))
 
PACS system (see Picture Archiving and Retrieval 
system (PACS))
 
PET (see Positron emission tomography (PET))
 
radio pharmacology, 247–248
 
SPECT (see Single-Photon Emission Computed 
Tomography (SPECT))
 
teleradiology, 244, 246

ultrasound (see Ultrasound)
 
x-rays (see X-rays)
 
Immune system response, 211–212
 
Independent variable, 248, 324–325
 
Inductive charging, 165, 173–175
 
Inference engines
 
cognitive systems, 76
 
and diagnosis support system, 71
 
FCI, 75
 
rules and facts, 75
 
steps, 75–76
 
Information Object Definitions (IODs), 229, 231
 
Information technology domains
 
biomedical engineering, 314
 
business (nonclinical) applications, 313
 
clinical applications, 313
 
infrastructure, 312–313
 
integration, 313–314
 
physicians, nurses, therapists and informatics, 314
 
security, 313
 
strategic planning, 312
 
telecommunications, 314
 
Infusion pump, 137, 273, 278–279, 289
 
Inpatient Prospective Payment System (IPPS), 329
 
Institute of Medicine (IOM), 270
 
Institutional review board (IRB), 126
 
Integrating the Healthcare Enterprise (IHE)

data sharing guidelines, 93
 
emergency room, 92
 
four-step development methodology, 93
 
healthcare industry, 92
 
Interdisciplinary plan of care (IPOC)
 
CMS and TJC, 277
 
computer-based systems, 278
 
paper-based form, 278
 
roadmap, 277–278
 
International Health Terminology Standards 
Development Organization (IHTSDO), 
84–85, 97–98
 
International Organization for Standardization (ISO)
 
categories and subcategories, 90
 
ISO TC 215, health informatics, 91
 
and OSI, 90
 
International Statistical Classification of Diseases and 
Related Health Problems (ICD)
 
ICD (9–10), 66
 
ICD10
 
classification categories, WHO, 113–114
 
HL7 header messages, 112
 
ICD11
 
features, 98
 
inputs and needs, 98

Index 421 
U.S. ICD Clinical Modification, 99
 
U.S. ICD10 Procedure Coding System, 100
 
Interoperability
 
communications, 82, 84
 
mapping tools, 84
 
vocabularies, 84
 
Intra-aortic balloon pump (IABP), 272–273, 302
 
IPOC,  see Interdisciplinary Plan of Care (IPOC)
 
IT project management
 
contracting and security review, 319
 
environment build, 319
 
funding, 319
 
go-live decision, 320
 
kickoff, 319
 
market place analysis, 318–319
 
period of acceptance, 320
 
policy and procedure development, 320
 
testing, 319
 
training, 320
 
workflow analysis, 319
 
IT sphere of influence
 
change agent, 311
 
communicator, 310
 
decision maker, 311
 
educator, 311
 
facilitator, 311
 
implementer, 312
 
listener, 312
 
risk taker, 312
 
J 
data types, 395–396 
function parameters 
scripts.js, 397
 
types, 396
 
global variables, 394–395
 
JQuery, 398–399
 
local variables, 394
 
scripts.js file, 396
 
K 
Korotkoff sounds, 200
 
L 
Laboratory Code Set Distribution (LCSD), 92

K 
 
L 
 
Layered Image File Format (LIFF), 235
 
“LIFE record” (LIFEr), 338–339
 
Logical Observation Identifiers Names and Codes 
(LOINC)
 
coding scheme, 101
 
observations/discrete measurements/collections, 101
 
SNOMED CT, 101
 
Lucene Image Retrieval (LIRE), 244
 
Lymphatic system, 212
 
M 
Magnetic resonance ima ging (MRI), 236–238 
MAP, see Mean arterial pressure (MAP) 
Mapping tools 
UMLS (see Unified Medical Language 
System (UMLS))
 
vocabularies and concepts, 84
 
Mean arterial pressure (MAP), 282
 
Medical apps for remote healthcare, 152
 
Medical Classification Systems, 95
 
Medical Databases
 
MEDLINE/PubMed, 105–106
 
MesH, 106–107
 
Medical imaging formats
 
Adobe (PSD) file images, 235
 
Analyze data format ( see Analyze-7.5 fMRI 
imaging format) 
DICOM (see Digital Imaging and Communications 
in Medicine (DICOM))
 
HDF4/HDF5, 235

ICS, 235
 
LIFF, 235
 
NetCDF, 235
 
NIfTI data format ( see Neuroimaging Informatics
 
Technology Initiative (NIfTI)) 
Medical informatics; see also Biomedical 
informatics (BMI)
 
American College of Medical Informatics, 4
 
bachelor’s program, 7
 
degree programs, 24–26
 
older designation, 2
 
Medical Literature Analysis and Retrieval System 
(MEDLINE), 105–106
 
Medical logic modules (MLMs), 72
 
Medical sensors
 
A&P primer (see An
 atomy and Physiology 
(A&P) primer)
 
big data (see Big data in healthcare)
 
biological organisms, 164
 
data acquisition (see Data acquisition, 
medical sensors) 
data mining, health care ( see Data mining) 
electrical and chemical conduction ( see Electrical 
and chemical conduction primer)
 
expert systems, 188–189
 
exponential growth, 164
 
heart disease ( see Heart disease)
 
primer, 164

sodium–potassium pump, 218
 
wireless devices ( see Wireless medical devices)
 
Medical Subject Headings (MesH), 
106–107
 
Medicare Modernization Act (MMA), 64
 
Medicare Prescription Drug Benefit, 64
 
Medication Administration Record (MAR), 68, 70, 275, 
277, 280, 284

422 Index 
mHealth
 
HHS, 149
 
NIH, 149
 
NSF and NIH projects, 151
 
Miniclinics
 
ACA, 156–157
 
certification criteria, 157–158
 
miniclinics, 157
 
PAs and RNs, 156
 
MLMs, see Medical logic modules (MLMs) 
Mobile applications development
 
android platform, 350
 
camera, 352
 
check for Java, 354
 
Cordova, 359–365
 
creating a folder structure to create an 
application, 352
 
default browser, 354
 
device capabilities
 
accelerometer, 352
 
connectivity, 352
 
geolocation, 351
 
gyroscope, 352
 
hardware sensors, 351
 
touch, 351
 
HTML/CSS/JavaScript, 350
 
“JAVA_HOME,” 356
 
Node.js, 359
 
PHR directory, 353
 
semi-colon, 358
 
using PhoneGap, 350–351
 
Mobile tools, physicians
 
EHR implementation, 158
 
Mobile MIM/Merge iConnect, 158
 
Productivity Apps, 
159–160 
third-party companies, 158
 
Motor cortex, 197
 
MRI, see Magnetic resonance imaging (MRI)
 
N 
National Ambulatory Medical Care Survey
 
(NAMCS), 326
 
National Committee on Vital and Health Statistics

N 
 
National Committee on Vital and Health Statistics 
(NCVHS), 33–34
 
National Council for Prescription Drug Programs
 
(NCPDP), 82, 85, 93–95
 
National Drug Code (NDC), 101–102
 
National Institutes of Health (NIH)
 
behavioral and social dimensions, 149
 
methodological advantages, 150
 
National League for Nursing (NLN) informatics
 
health IT tools, 11
 
definition, 11
 
information technology curriculum, 11
 
technology-rich environment, 10
 
National Patient Safety Goals (NPSGs), 317
 
National Science Foundation (NSF), 150
 
Nationwide Health Information Network (NHIN), 
66–67
 
Nationwide Inpatient Sample (NIS) database, 
265, 267
 
Navigation, EHR
 
central console, 68
 
demographics, 68
 
discharge orders, 70
 
MAR, 68
 
orders, 70
 
patient list, 68, 70
 
NCPDP, see National Council for Prescription Drug 
Programs (NCPDP) 
NCVHS, see National Committee on Vital and Health 
Statistics (NCVHS)

Network Common Data Form (NetCDF), 235
 
Neural networks
 
Boundary Box method, 265
 
Code of Ethics, 267
 
computer-aided diagnosis, 264
 
definition, 264
 
NIS, 265–266
 
superposition theory vs. nonlinear system, 
264–265 
Neuroimaging Informatics Technology 
Initiative (NIfTI)
 
neuroimaging tools, 233–234
 
organization efforts, 234
 
NHIN, see Nationwide Health Information Network 
(NHIN) 
NIH, see National Institutes of Health (NIH) 
Nursing documentation 
altitude/blood pressure, 284–285
 
computer-based documentation system, 284
 
head-to-toe approach, 285
 
paper records, 286
 
screening tools and risk assessments, 285
 
vital signs, 286–287
 
NLN (see National League for Nursing (NLN) 
informatics)
 
science and practice, 4
 
O 
Office of the National C oordinator (ONC)
 
eHealth Exchange, 67

O 
 
enhanced privacy–security, 56
 
for Health Information, 49
 
Office of the National Coordinator (ONC) for Health 
Information Technology, 40
 
Ohms law, 165, 168
 
Open Systems Interconnection (OSI), 90
 
Oxygen saturation, 181, 183, 272
 
Oxyhemoglobin, 182

Index 423 
P 
PACS, see Picture archiv ing and retrieval 
system (PACS)
 
PAP, see Pulmonary artery pressure (PAP)
 
Pathogen-associated molecular patterns (PAMPs), 211
 
PEEP, see Positive end expiratory pressure (PEEP)
 
Peritoneal dialysis, 279
 
Personal health information (PHI), 42, 51, 62, 122, 
125–128 
Personal health records (PHR)
 
benefits, 51
 
Blue Cross and Blue Shield, 52
 
individual’s health information, 51
 
patient-generated lists, 50
 
provider dispute resolutions, 50
 
types, 51–52
 
PET, see Positron emission tomography (PET)
 
Peukert’s law, 170, 172
 
Pharmacy CDSS, 74
 
PHR, see Personal health records (PHR)
 
Physician assistants (PAs), 148, 156–157, 274
 
Picture archiving and retrieval system (PACS)
 
DICOM format, 242
 
HIPAA, 244–245
 
IBM (WebSphere) DB2 query, 242
 
Oracle architecture, 242–243
 
XML query code example, 242
 
PKE, see Public key encryption (PKE) systems 
Positive end expiratory pressure (PEEP), 
272, 302

272, 302
 
Positron emission tomography (PET), 239–240
 
Predictions
 
Apollo Missions 11–20, 324
 
biomedical analytics ( see Biomedical predictive 
 
Cold War, 322
 
future directions, 323
 
metrics, 324–325
 
national pride, 322
 
negative forces, 322, 324
 
sample of positive nonlinear factors, 322
 
space exploration, 324
 
Predictive analytics, 46, 324–325
 
Predictive confidence factors (PCFs), 325– 327, 334
 
Pressure ulcer, 270, 274, 285, 293
 
Privacy board, see  Institutional review board (IRB)
 
Privacy rule
 
ePHI, 124
 
HIPAA Title II security, 124
 
PHI, 122
 
Public key encryption (PKE) systems, 131, 134–135
 
Pulmonary artery pressure (PAP), 272, 302
 
ABG, 183
 
Beer’s law, 182
 
Lambert–Bouguer law, 182
 
light wavelengths, 182
 
limitations, 181
 
oxygen saturation monitoring, 181
 
R

R 
Radio frequency identification (RFD), 302
 
Radio pharmacology, 247–248
 
Reference coordinate system (RCS), 21, 230
 
Regenstrief LOINC Mapping Assistant (RELMA), 101
 
Regional Health Information Organization (RHIO), 67
 
Registered nurses (RNs), 146, 148, 156, 293
 
RELMA,  see Regenstrief LOINC Mapping 
Assistant (RELMA) 
Reporting impaired drivers
 
New Jersey Driver License regulations, 258
 
patient and public safety, 257
 
and physicians, 258–259
 
Retina, 132, 202
 
RFD,  see Radio frequency identification (RFD)
 
RHIO,  see Regional Health Information 
Organization (RHIO) 
RxNav, 116–117 
RxNorm 
clinical drugs, 101
 
vs. NDC, 102–103
 
S 
Security;  see also HIPAA Title II
 
administrative controls and safeguards, 
127–128
 
breach notification rule, 128
 
civil and criminal penalties, 128–129
 
encrypted PHI, 128
 
management process

127–128
 
information system activity, 35
 
risk analysis, 33, 35
 
risk management, 35
 
sanction policy, 35
 
third-party vendor’s security, 122
 
Transaction Codes (Title II), 129
 
Sepsis, 285
 
“Settings_screen” div, 375
 
Single-Photon Emission Computed Tomography 
(SPECT) imaging technique, 238
 
Sinoatrial node (SA), 200
 
SKE, see Symmetric key encryption (SKE)
 
SNOMED CT, see Systemized Nomenclature of 
Medicine Clinical Terms (SNOMED CT) 
Stakeholder analysis
 
decision makers, 317
 
execution, IT projects, 318
 
funding, 318
 
needs, 317
 
politics, 317

424 
Stroke
 
heart attack, 46
 
National Institute of Neurological Disorders, 233
 
real-time analysis, 49
 
Symmetric key encryption (SKE), 134
 
Systemized Nomenclature of Dentistry (SNODENT),
 
98, 331
 
Systemized Nomenclature of Medicine Clinical Terms 
(SNOMED CT)
 
data architecture, 97
 
EHR architecture ( see Electronic health records 
(EHRs))
 
Development Organization, 97–98
 
procedures, 64
 
Systole
 
blood pressure, 180
 
heart muscle, 180
 
T 
Telehea lt h
 
DICOM, 140
 
EHRs, 140
 
field, 140–141
 
Telemedicine
 
applications, 142
 
ATA, 142
 
cost-effectiveness, 142
 
liability and malpractice, 142
 
Medicare Telehealth Services and 
Billing Codes, 143
 
and Telecare, 142
 
Telemental health, 148–149
 
Teleradiology, 244, 246
 
Telesurger y
 
da Vinci system, 144
 
Haptic Force Feedback, 144, 146
 
The Joint Commission (TJC), 270
 
Thymus, 208, 212
 
Tidal volume, 272
 
TJC, see The Joint Commission (TJC)

“Toggle edit” button, 375
 
Transformer equation, 174
 
Translational bioinformatics, 4
 
U 
UCM, see Urgent Care Medicine (UCM)
 
Ultrasound, 239
 
UMLS, see Unified Medical Language System (UMLS)
 
Index 
Unified field theory (UFT), 325
 
Unified Medical Language System (UMLS)
 
Lexical tools, 116
 
Metathesaurus, 115–116
 
Semantic types, 115–116
 
Urgent Care Association of America (UCAOA), 151
 
Urgent Care Certification Criteria, 155–156
 
Urgent Care Medicine (UCM)
 
Facilities Statistics, 155
 
medical service offering, 152
 
On-Demand Medical Consultation Apps, 153–154
 
U.S. Initiatives
 
ARRA, 63
 
EHR implementation and reimbursement, 60
 
e-prescribing (see Electronic prescribing 
(e-prescribing))
 
HIPAA, 62
 
“meaningful use,” 63, 65
 
meaningful use Stage 2, 63–64
 
U.S. Medical Records,  see Electronic health

HIPAA, 62
 
U.S. Medical Records,  see Electronic health 
records (EHRs) 
V
 
Venous oxygen saturation (SvO 2), 183, 279, 300
 
Venous thromboembolism (VTE), 285, 289–290
 
Ventilator, 183, 272, 275, 300
 
Ventricular assist device, 6, 142, 273
 
Veterans Health Information Systems and Technology
  
Architecture (VistA), 28
 
Virtual medical records, 87
 
Virtual private network (VPN), 135
 
VistA,  see Veterans Health Information Systems and 
Technology Architecture (VistA) 
VPN,  see Virtual private network (VPN) 
VTE,  see Venous thromboembolism (VTE) 
W 
Wireframe, 372–379 
Wireless medical devices
 
Bluetooth, 185–186
 
BSN, 186
 
definition, 185
 
integrated data capture modeling, 187–188
 
spectrum, 187
 
Workforce security, 36
 
X
 
X-rays, 235