MajorTheories Supporting Health Care Informatics

Download MajorTheories Supporting Health Care Informatics

Preview text

MajorTheories Supporting Health Care Informatics

Learning O biecnves

Upon completion of this chapter the reader will be able to:

1. List major theories used in health care



2. Describe how selected theories and models

explain and predict phenomena of importance

to health care informatics practitioners.

Use selected theories to analyze problems arid challenges encountered when using automation to support health care delivery.

Systems Theory
Characteristics of Systems Systems and the Change Process
Information Theories
Shannon and Weaver's Information-Communication Model Blum's Model
Learning Theories

Behavioral Theories Information Processing, or Cognitive Learning, Theories Adult Learning Theories Learning Styles
Change Theories
Planned Change Diffusion of Innovation Using Change Theories

Keq Terms
adult learning theories andragogy attributes
automated decision support system automated expert system automated information system behavioral learning theories boundary change theories

channel closed system cognitive learning theories concepts data diffusion of innovation dynamic homeostasis early adopters early majority encoder entropy

equitinality framework information innovators ,. knowledge laggards late majonty lead part learning learning styles model


Keq lerms-cont'd
negentropy noise open system phenomenon receiver

reverberation sender specialization subsystem supersystem

system target system theoretical model theory wisdom

Oi Web Connection
Go to the Web site at www.mosbycom/MERLIN/Englebardt/. Here you will find Web links and activities related to major theories supporting health care informatics.

theory explains the process by which cer­ A tain phenomena occur (Hawking, 1988). It
begins with an observation of the specific phenomena. An example of a phenomenon is that people frequently resist change. But why and how does this phenomenon occur? A theory related to this phenomenon would explain why people resist change and predict when and how they will demonstrate resistance.
The following is the four-stage process by which most theories develop:
A specific phenomenon is noted or observed. An idea is proposed explaining the de­ velopment of the phenomenon. 3 A model is developed co explain the operation of the phenomenon. Con­ cepts key to explaining the phenome­ non are identified, and the processes by which the concepts interact are described. ""· The model is tested, and as support­ ing evidence accumulates, a theory develops.

There is no single set of consistent criteria that can be applied to decide when a model becomes a theory. As a result, the terms are often used in­ terchangeably. In ocher words, it is possible for one reference to refer co a phenomenon as a the­ ory and for another reference to refer co the same phenomenon as a model. For example, one ref­ erence may refer to a communication theory and another reference may refer to a communication model, yet both references may be describing the same phenomenon. In addition, a theoretical modei is often used to explain a theory. A theo­ retical model is a description or figure used to help visualize a theory. It includes the concepts and interactions among the concepts operating within the theory.
The building blocks of a theory are called concepts. Concepts may be abstract, such as love, or concrete, such as fruit. Concepts provide structure to a theory. For example, in Figure 1-1 the relationship among four concepts is depicted. These four concepts and the location of the con­ cepts in the figure demonstrate the structure of the theory. The interactions among the concepts in a theory explain the function or operations of

Major Theories Supporting Health Care Informatics CHAPTER l S


I Open System Interacting With the Environment



----+ I


Pro cess

l._. . _....

o.(n, ufot�umtait on,

matter, and



'·••••••••••••••••••n•ou•o-HOUo '

that theory. For example, the electrical system of the heart is a concrete concept. Impulses travel through this system and produce a contraction of the atria and ventricles. The concept of the heart's electrical system and the description of how it functions provide a theory that can be used to explain how the heart beats.
Because a theory explains the what and how of a phenomenon, it can provide direction for planning interventions. Continuing the cardiac example, the cardiac impulse normally beg.ins in the sinoacrial (SA) node in the right atrium and travels across the atrioventricular (AV) node to the ventricles. In atrial fibrillation chis normal process is disrupted, and impulses arise at a rapid race from multiple sites in the atrial muscle. This can result in a fast ventricular response, or tachy­ cardia. Drugs that block or slow the rate of im­ pulse transmission at the AV node can be used to treat tachycardia caused by atrial fibrillation.
This is an example of using a theory to under­ stand and manage a problem. \ Health care informatics, as an applied field of study, incorporates theories from information science, computer science, and cognitive science, as well as from the wide range of sciences used in the delivery of health care. As a result, health care informatics specialists draw on a wide range of theories to guide their practice. This chapter f<;><=�ses on selected theories from a variety of dis­ ciplines that are of major importance to health

care informatics. These theories are key to un­ derstanding and managing the challenges faced by health care informatics specialists. In analvz­ ing the selected theories, the reader will discover that understanding these theories presents certain challenges. Some of the theories overlap, differ­ ent theories are used to explain the same phe­ nomena, and sometimes different theories have the same name. All of these challenges can be found in the theories of information (see the In­ formation Theories section).
The one theory underlying all of the theories used in health care informatics is systems theory. Therefore chis is the first theory co be discussed in chis chapter.
A system is a set of related interacting parts en­ closed in a boundary ( Von Bertalanffy, 1975\. Examples of systems include computer systems, school systems, the health care system, and a per­ son. Systems may be living or nonliving. For ex­ ample, a person is a living system, whereas a computer is a nonliving system (Joos, Nelson. & Lyness, 1985).
Systems may be either open or closed. Closed systems are enclosed in an impermeable boundary and do not interact with the environment. An ex­ ample of a closed system is a chemical reaction en­ closed in a glass structure with no interaction with the environment outside the glass. Open systems are enclosed in semipermeable boundaries and do interact with the environment. This chapter fo­ cuses on open systems. Open systems can be used co understand technology and the people who in­ teract with the technology. Figure 1-1 demon­ strates an open system interacting wich the envi­ ronment. As shown in Figure 1-1, open systems take input {information/matter/energy) from the environment, process the input, and then return output to the environment. The output then be­ comes feedback to the system. Concepts from sys­ tems theory can be applied in understanding the way people work with computers in a health care

6 PR RT ONE Foundations of Health Care Informatics

organization. These concepts can also be used to analyze individual elements, such as software, or the total picture of what happens when systems interact.
A common expression in computer science is "garbage in, garbage out,'' or "GIGO." GIGO refers to the input-output process. The counter­ concept implied from this expression is that qual­ ity input is required to achieve quality output. Al­ though this expression usually is used when referring to computer systems, it can apply to any open system. Some examples include the role of a poor diet in the development of health problems or the role of informed, active participants in se­ lecting a health care information system. In these examples "garbage in" can result in "garbage out," or quality data can support quality output. Not only is quality input required for quality out­ put, but also the system must have effective pro­ cedures in place for processing these data. Sys­ tems theory provides a framework for looking at the input into a system, for analyzing how the system processes that input, and for measuring and evaluating the output from the system.
Characteristics of Systems
Open systems have three types of characteristics: I purpose, functions, and structure. The purpose is
the reason for the system's existence. The purpose of an institution or program is often stated in the mission statement. For example, the purpose of a bachelor of science in nursing (BSN) educa­ tional program is to prepare professional nurses. Often computer systems arc referred co or classi­ fied by their purpose. The purpose of a radiology system is to support the radiology department; the purpose of a laboratory system is to support the laboratory department. A scheduling system is used to schedule either clients or staff.
It is possible for a system co have more than one purpose. For example, a family system or a hos­ pital information system may have several dif-

ferent purposes. One of the purposes of a hospi­ tal information system is to provide interdepart­ mental communication. Another purpose is to maintain a census that can be used to bill pa­ tients for services rendered.
One of the first steps in selecting a computer system in a health care organization is to iden­ tify the purpose(s) for that system. There may be a tendency to minimize this step on che basis of the assumption that everyone already agrees on the purpose of the system. Taking the time to specify the purpose helps to ensure that the rep­ resentatives from the clinical, administrative, and technology domains agree on the reasons for se­ lecting a system and understand the scope of the project. Purpose answers the question, "Why se­ lect a system?"
Functions, on the other hand, focus on the ques­ tion, "How will the system achieve its purpose?" Functions are sometimes mistaken for purpose. However, it is important to clarify why a system is needed and then to identify what functions the system will carry out. Functions are activities that a system carries out to achieve its purpose. For example, a hospital information system may achieve the interdepartmental communication purpose by maintaining an eMail program, as well as a program for order entry and results re­ porting. Each time an order is entered into the system, it is communicated to the appropriate department. Each time a department has results to report, they are communicated back to the clinical unit or appropriate health care provider.
When a computer system is being selected, the functions are carefully identified and defined in writing. These are listed as functional specifica­ tions. Functional specifications identify each function and describe how that function will be performed.
Systems are structured in ways that allow them to perform their functions. Structure follows

Major Theories Supporting Health Care Informatics CH R PTER 1 7

function. Note how health care teams are orga­ nized. The organizational structure varies with the purpose of the organization and the func­ tions that are co be performed. The organization of a nursing staff on a clinical unit demonstrates this concept. They may be organized using the concept of team nursing, primary nursing, or case management. In each case the purpose is to provide patient care. The staff is structured to ensure that the functions necessary for nursing care are completed.
Structure Conceptualization Two different models can be used to conceptualize the struc­ ture of a system. These are hierarchical and web. Both models are in operation at the same time. The first model discussed is the hierarchical model. Figure 1-2 demonstrates this model. ln this figure each computer is part of a local area network (LAN). The LA,.'\.!s join together to form a wide area network (WAt"i) that is connected to the mainframe computer. The mainframe is the lead computer, or lead part.
In an analysis of the hierarchical model, the term system may refer to any level of the struc­ ture. In Figure 1-2 an individual computer may be referred co as a system,or the whole diagram may be considered a system. Three terms are used to indicate the level of reference. These are subsystem, target system, and supersystem. A subsystem is any system within the target system. For example,if the target system is an LAN, each computer is a subsystem. The supersystem is the overall structure in which the target system ex­ ists. If the target system is an LAN,then Figure 1-2 represents a supersystem.
The second model for analyzing the structure of a system is the web model. The interrelation­ ships among the different LANs function like a web. Laboratory data may be sent to the phar­ macy, and at the same time the clinical unit data collected by nursing,such as weight and height, may be senc to each department needing these ?ata. The web model can also be applied to liv­ mg systems. Note the processes whereby various

body systems interact with each other. In health care informatics much of the work is accom­ plished in task groups corresponding to body systems. Although someone is in charge of the task group,the relationships and communication among the members of the group flow in a web pattern. As these examples demonstrate, a sys­ tem includes structural elements from both the web and the hierarchical model.
Structure Characterization Boundary, attri­ butes, and environment are three concepts used to characterize structure. The boundary of a sys­ tem forms the demarcation between the target system and the environment of the system. In­ put flows into the system by moving across the boundary, and output flows into the environ­ ment across this boundary. Understanding boundary concepts assists in the development of health care information systems. For example, one of the techniques used in developing health care information systems is to divide the health care delivery system into modules or subsys­ tems. This process helps to establish the bound­ aries of a project. In Figure 1-2 each LAN is .1 target system. Each computer in the diagram represents a subsystem that can be automated. For example, a health care institution may be planning for a new pharmacy information sys­ tem. The new pharmacy system becomes the tar­ get system. However, the pharmacy system in­ teracts with other subsystems within the total system. As the task group goes about the work of selecting the new pharmacy system, it will need to identify the functional specifications needed to automate the pharmacy and the func tional specifications needed for the pharmacy system to interact with the other systems in the environment. Clearly specifying the target sys­ tem and the other systems in the environment will assist in defining the scope of the project. By defining the scope of the project,it becomes pos­ sible to focus on the task at hand while planning for the integration of this computer system with other systems in the institution.

8 PRAT OIIE Foundations of Health Care Informatics
AGURE 1-2 j Hierarchical Information System Model


Managed care


Administrative LAN

.' 0


::::: ..=.. :::::

L__ _---10


Cardiology Departmental LAN


Unit 6-E Clinical units LAN

Major Theories Supporting Health Care Informatics CHAPTER 1 9

When health care information systems are be­ ing planned, attributes of the system must be identified. Attributes are the properties of the parts or components of the system. They are the terms used to describe a system. For example, the attributes of a person include hair color, weight, and intelligence quotient (IQ). Computer hardware attributes are usually referred to as specifications. An excellent example of a list of attributes or specifications can be seen in adver­ tisements or the owner's manual for computer hardware. These include such things as the amount of random access memory (RAM), the size of the hard drive, and even the size of the case covering the computer. Another example of a list of attributes can be seen on an intake or pa­ tient assessment form for a health care setting. The form lists the attributes of interest. A com­ pleted form describes the individual patient's ex­ pression of these attributes.
Attributes and the expression of those attri­ butes play a major role in the development of databases. Field names are a list of the attributes of interest for a specific system. The datum in each cell is the individual system's expression of that attribute. A record lists the attributes for each individual system. The record can also be seen as a subsystem of the total database system. A complete discussion of databases can be found in Chapter 3.
Systems and the Change Process
Both living and nonliving systems are constantly in a process of change. Six concepts are helpful in understanding the change process. These are dynamic homeostasis, entropy, negentropy, spe­ cialization, reverberation, and equifinality. Dy­ namic homeostasis refers to the processes used by a system to maintain a steady state or bal­ ance. An excellent example is the fluctuations seen in normal body chemistry. Blood levels of normal blood elements begin the drift down or up. Through a feedback loop the body begins co produce more of the decreasing elements and

eliminate the excess elements. As the blood level changes, the feedback loop kicks in to reverse the process.
Chapter 10 discusses the life cycle of an infor­ mation system. One of the stages in this life cycle is maintenance. .Maintenance includes a number of activities that function to keep the system op­ erating. Organizations that experience rapid or extensive change experience increased stress be­ cause the dynamic homeostasis of the organiza­ tion is challenged. People working within chang­ ing organizations will attempt to maintain a steady state. The result can be seen as resistance to change. An informatics example is the intro­ duction of automation or the introduction of a new computer system that stresses the dynamic homeostasis of the organization. Managing change and thereby decreasing the stress experi­ enced by individual users, as well as the stress ex­ perienced by the organization as a whole, is a major piece of the work accomplished by the health care informatics specialist.
Entropy is the tendency of all systems to break down into their simplest parts. As they break down, the systems becomes increasingly disorganized or random. In data transmission, entropy measures the loss of information when a signal is transmitted. Entropy is demonstrated in the tendency of all systems co wear out. It is the tendency of all living systems to reach the point of death. Even with maintenance, a health care information system will reach a point where it must be replaced.
Negentropy is the opposite of entropy. This 1s the tendency of living systems to grow and be­ come more complex. This is demonstrated in the growth and development of an infant, as well as in the increased size and complexity of today's health care system. With the increased growth and complexity of the health care system there has been an increase in the size and complexity of health care information systems.
As systems grow and become more complex, they divide into subsystems and then subsubsys­ tems. This is the process of differentiation and

lO PART ONE Foundations of Health Care Informatics

specialization. Note how the human body begins as a single cell and chen differentiates into differ­ ent body systems, each wich specialized pur­ poses, strucrnres, and functions. This same process occurs with health care delivery systems, as well as with health care information systems. As chis process occurs, a lead part emerges. The lead part is at che top of the hierarchy. Lead pares play primary roles in organizing and maintain­ ing vertical and horizontal data/information flow. Changes to the lead part can have a major impact a<.:ross the total system. For example, if the chief information officer leaves che organiza­ tion, the impact is much more significant than if a beginning-level systems analyst moves to an­ other organization. If the mainframe in Figure 1-2 were to stop functioning, the impact would be much more significant than if an individual computer on one of che LANs were co stop func­ tioning. Understanding the role of the lead part can be key co developing the security and disas­ ter plan for a health care information system.
Change within any part of the system will be reflected across the coral system. This is referred to as reverberation. Reverberation is reflected in the intended and unintended consequences of sys­ tem change. When planning for a new health care information system, the team will attempt to iden­ tify the intended consequences or expected bene­ fits co be achieved. Although it is often impossible to identify a comprehensive list of unintended consequences, it is important for rhe team to con­ sider che reality of unintended consequences. The potential for unintended consequences should be discussed during the planning stage; however, these consequences will be more evident during the testing stage chat precedes implementation, or "go live." Often, unintended consequences arc not considered until after go live, when they be­ come obvious. For example, eMail may be suc­ cessfully introduced to improve communication in an organization. However an unintended con­ sequence can be an increased workload resulting from irrelevant eMail messages.
Equi.finality refers to the ability of open sys­ tems to reach the same end state by starting at

different initial states and by using different means. For example, several hospitals may be implementing new hospital information systems. The staff in che various hospitals may or may not be experienced in using chis type of software. The hospitals may select from several different approaches for training the staff. Some may use clinical staff and develop superusers. Others may hire outside consultants to do all the training. Ochers may use information technology or staff development personnel co do the training. No matter what the initial knowledge level of the personnel or the training approach used, each of these hospitals has the potential to effectively train staff and experience a successful imple­ mentation. In other words, there is no one cor­ rect way to manage many of the challenges in­ herent in health care informatics.
All systems change and in the process interact with the environment. This interaction is shown in Figure 1-1. Input into the system consists of en­ ergy, information, and matter. This input is then processed and results in output. Understanding this process as it applies to informatics involves an understanding of information theories.
The term information has several different mean­ ings (Information, 2000). An example of this can
be seen in Box 1-1. Juse as the term information
has more than one meaning, the term informa­ tion theory refers to more than one theory. This chapter examines two theoretical models of in­ formation theories: Shannon and Weaver's infor­ mation-communication model and Blum's model.
Shannon and Weaver's Information-Communication Model
Information theory as a formal theory was born in 1948 with the publication by Claude Shannon of the landmark paper "A Mathematical Theory of Communication" (Shannon, 1948).
The concepts in this model are presented in Figure 1-3. The sender is the originator of the

MajorTheories Supporting Health Care Informatics CHAPTER 1 11

. AGUHE�f: I Information-Communication Model

f- ---,MI I



.-��c- a_ _:�ne_l�� o e c o de


�- - _ __ -�� �,

4l:I=- Noise Definitions of Information
in·for-ma·tion noun Pronunciation: "in-f&r-'mA-sh&n
1. The communication or reception of knowl­ edge or intelligence
2. a. Knowledge obtained from investigation, study, or instruction
b. The attribute inherent in and communi­ cated by one of two or more alternative sequences or arrangements of some­ thing (as nucleotides in DNA or binary digits in a computer program) that pro­ duce specific effects
c. (1) A signal or character (as ma com­ munication system or computer) repre­ senting data (2) Somethmg (as a mes­ sage, experimental data, or a picture)

which justifies change in a consuuct (as a plan or theory) that represents physi­ cal or mental experience or another construct d. A quantitative measure of the content of information; specifically: a numerical quantity that measures the uncertainty in the outcome of an experimenc to be pedormed 3. The act of informing agamst a person 4. A formal accusation of a crime made by a prosecuting officer as distinguished from an indictment presented by a grand jury
From Information. In Merriam- Webster online: ,\,ferriam- Webster's collegiate dictionary. (2000). Re· trieved October 8, 2000, from the World Wide Web:

message. The encoder converts the content of the message to a code. The code can be letters, words, music, symbols, or a computer code. For example, the modem on a computer acts as an encoder when it converts a file from a digital form to an analog form so that it can be sent over telephone lines that carry analog sound waves. The telephone line is the channel. A chan· nel carries the message. Examples of channels in­ clude sound waves, telephone lines, and paper. Each channel has its own physical limitations in t�rms of the size of the message that can be ear­ ned. Noise is anything that is not part of the

message but occupies space on the channel and is transmitted with the message. Some examples of noise include static on a telephone line and back ground sounds in a room. The decoder converts the message co a format that can be understood by the receiver. When one is listening co a phone call, the telephone is a decoder. It converts the analog signal back into sound waves, which are understood as words by the person listening. The person listening to the words is the receiver.
Shannon, one of the authors of the Shannon and Weaver information-communication theory. was a telephone engineer. He was not concerned

12 PART ONE Foundations of Health Care Informatics

with the semantic meaning of the message but rather with the technica.1 problems involved in signal transmission across a communication channel or telephone line. He used the concept of entropy to explain and measure the amount of information in a message. The amount of in­ formation in a message is measured by the ex­ tent that the message decreases entropy. The unit of measurement is a bit. A bit is represented by a 0 (zero) or a 1 (one). The two sides of a coin can be used to explain this concept. If a coin is thrown into the air, it may land on either of two possible sides: heads up or tails up. This can be coded as 1 for heads up and O for tails up. Using this approach, the message concerning which side is up is transmitted with 1 bit. If there were four possible states, additional bits would be needed to transmit the message. For example, if the message could be north, south, east, or west, it might be coded 00 for north, 11 for south, 01 for east, or 10 for west. Computer codes are built on this concept. For example, how many bits are needed to code the letters of the alpha­ bet? What other symbols are used in communi­ cation and must be included when developing a code?
Warren Weaver, from the Sloan-Kettering In­ stitute for Cancer Research, provided the inter­ pretation for understanding the semantic mean­ ing of a message (Shannon & Weaver, 1949). He used Shannon's work to explain the interper­ sonal aspects of communication. For example, if the speaker is a physician who uses medical terms that are not known to the receiver (the pa­ tient), there will be a communication problem caused by the method used to encode the mes­ sage. However, if the patient cannot hear well, he or she may not hear all of the words in the message. In this case the communication prob­ lem is caused by the patient's ear, which is having difficulty converting the sound waves into neu­ rological impulses that the brain can decode.
The communication-information model pro­ vides an excellent framework for analyzing the effectiveness and efficiency of information trans-

fer and communication. For example, a physician may use a computerized order entry system to en­ ter orders. Several questions illustrate the infor­ mation transfer process. Is the order entry screen designed to capture and code all of the key ele­ ments for each order? Are all aspects of the mes­ sage coded in a way that can be transmitted and decoded by the receiving computer? Does the message that is received by the receiving depart­ ment include all of the key elements in the mes­ sage sent? Does the screen design at the receiver's end make it possible for the message to be de­ coded or understood by the receiver?
These questions demonstrate three levels of communication that can be used in analyzing communication problems (Hersh, 1996). The first level of communication is the technical I level. Do the system's hardware and software function effectively and efficiently? The second level of communication is the semantic level. ./ Does the message convey meaning? Does the re­ ceiver understand the message that was sent by the sender? The third level of communication is the effectiveness level. Does the message produce { the intended result at the receiver's end? For ex­ ample, did the physician order one medication but the patient received a different medication with a similar spelling? Some of these questions require a more in-depth look at how health care information is produced, transferred, and used. Bruce Blum's definition provides a framework for this more in-depth analysis.
Blum's Model
Bruce L. Blum developed a definition of infor-1 mation from an analysis of the accomplishments in medical computing. In his analysis Blum iden­ tified three types of health care computing appli­ cations. He grouped applications according to the objects that they processed: data, informa­ tion, or knowledge. He defined data as uninter­ preted elements, such as a person's name, weight, or age. Information was defined as a collection of data that has been processed and then dis-

Preparing to load PDF file. please wait...

0 of 0
MajorTheories Supporting Health Care Informatics