brief overview of nursing informatics' theories

1. NURSING INFORMATICS
IS A SPECIALTY WITHIN NURSING THAT INTEGRATES NURSING SCIENCE,
COMPUTER SCIENCE, AND INFORMATION SCIENCE

2. One of the most compelling definitions of the discipline states: “Nursing informatics
science and practice integrates nursing, its information and knowledge and their
management with information and communication technologies to promote
the health of people, families and communities worldwide” (International Medical
Informatics Association – Nursing Working Group, 2010).
Theory is one of the fundamental blocks of each
scientific discipline. It is impossible to imagine biology
without the theory of Evolution, or physics without the
theory of Relativity. Nursing informatics, a relatively
new discipline, is also thirsty for its own theory.

3. Theory applied to informatics
Lewin’s Change Theory
Theory is an important component of robust nursing informatics knowledge, a fact that is
sometimes overlooked in both education and practice. A theory focus continues in this issue with
a look at the oldest, simplest, yet robust and applicable change management theory, Kurt
Lewin’s Change Theory.
Kurt Lewin’s Change Management Theory, is a time-tested, easily applied field theory that is often
considered the epitome of change models, suitable for personal, group and organizational change.

4. Kurt Lewin, (1890 – 1947) a Gestalt social psychologist, has been acknowledged as the
“father of social change theories” since several contemporary models are at least loosely
based on Lewin’s work. He is also lauded as the originator of social psychology, action
research, as well as organizational development.
Lewin’s change theory is a ‘planned
change’ guide that consists of three
distinct and vital stages:
 Unfreezing Stage
 Moving to a New Level or Change Stage
 Refreezing.Stage

5. Unfreezing
The first stage involves finding a method of making it possible for people to let go of an old pattern that
was counterproductive in some way. This is the stage where the desire to change occurs, or at least the
recognition that change is needed. An example is moving from a paper based documentation system to an
electronic system, in an organization where paper trails have become unmanageable and archaic.
Unfreezing the present Forces that maintain current behavior are reduced through
analysis of the current situation. Imperatives for change are realized through dialogue
and re-educational activities such as team building, personal development, and brain-
storming. The more transparent and inclusive the process is, the more readily people
move through the unfreezing stage.

6. Moving to a new level or Change
The second stage involves a process of change–in thoughts, feelings, behavior, or all three, that is in
some way more liberating or more productive than doing things the old way. During this stage, the
people involved (change target group) are convinced that the new way is better than the old.
Having analyzed the present situation, new structures and processes are put in place to achieve the
desired improvements. This is the most time-consuming, costly, yet productive stage as far as
tangible results go.
Refreezing
The third and final stage consists of establishing the change as a new habit or process, so that it now
becomes the “standard operating procedure” or status quo. Without some process of refreezing, it is
easy to backslide into the old ways of doing things. Rewards, support, and champion leadership
continue to be important through this stage, which is essentially ongoing until the next major change
is needed.
The changes implemented are ‘frozen’ in place to ensure that they become part of normal working
procedures. This is done by establishing supportive mechanisms such as policies, rewards, ongoing
support, and a solid orientation to the new system for incoming personnel.

7. Force Field Analysis
Lewin extended his theory by including “force field analysis” which offers direction for diagnosing
situations and managing change within organizations and communities. Lewin assumed that in any
situation there are both driving and restraining forces that influence any change that may occur.
According to Lewin’s theory, human behavior is caused by forces – beliefs, expectations, cultural
norms, and the like – within the “life space” of an individual or society. These forces can be positive,
urging us toward a behavior, or negative, propelling us away from a beneficial behavior as illustrated
bellow:

8. Driving Forces
Driving forces are forces that influence a situation, pushing in a particular
direction: they tend to initiate a change and keep it going. In terms of
improving productivity in a work group, pressure from a supervisor,
incentives, frustration with the current way of doing things (such as paper
documentation) and competitive or social demands are examples of
potential driving forces.
Restraining Forces
Restraining forces are forces that act to restrain or decrease the driving
forces – they make it difficult to move a change forward. Apathy,
prohibitive cost, hostility, technology illiteracy and poor maintenance of
equipment are examples of restraining forces which can inhibit change
and may restrict productivity.

9. Equilibrium
Equilibrium is the status quo or the present level of productivity, and can be disrupted or fortified by
changes in the relationship between the driving and the restraining forces.

10. So before a change occurs, the force field is in equilibrium between forces favourable to change and those
resisting it. Lewin spoke about the existence of a quasi-stationary social equilibrium, which needed to be
shifted during the change process, but then reestablished at a new level once the change had been refrozen.
For change to happen the status quo, or equilibrium must be upset – either by adding conditions favorable
to the change or by reducing resisting forces.
The force field analysis integrates with Lewin’s three stage theory of change as one works towards
unfreezing the existing equilibrium, moving towards the desired change, and then freezing the change at
the new level so that a new equilibrium exists that resists further change.

11. The goal of the change agent(s) is to support the driving forces to move beyond equilibrium and outweigh the
impact of any restraining forces. This provides support in moving through the unfreezing – changing –
refreezing stages of change.
Although Lewin’s change management theory was developed decades ago, it continues to offer a reliable and
viable model for informatics-related changes.

12. Diffusion of Innovation Theory
Diffusion of Innovation (DOI) Theory, developed by Everett Rogers in 1962, is one of the
oldest social science theories. It originated in communication to explain how, over time,
an idea or product gains momentum and diffuses (or spreads) through a specific
population or social system.

13. The end result of this diffusion is that people, as part of a social system, adopt a new idea,
behavior, or product. Adoption means that a person does something differently than what they
had previously (i.e., purchase or use a new product, acquire and perform a new behavior, etc.).
The key to adoption is that the person must perceive the idea, behavior, or product as new or
innovative. It is through this that diffusion is possible.

14. Researchers have found that people who adopt an innovation early have different characteristics
than people who adopt an innovation later. When promoting an innovation to a target
population, it is important to understand the characteristics of the target population that will
help or hinder adoption of the innovation.
There are five established adopter categories, and while the majority of the general population
tends to fall in the middle categories, it is still necessary to understand the characteristics of the
target population. When promoting an innovation, there are different strategies used to appeal to
the different adopter categories.

15. Five established adopter categories
1. Innovators - These are people who want to be the first to try the innovation. They are
venturesome and interested in new ideas. These people are very willing to take risks, and are
often the first to develop new ideas. Very little, if anything, needs to be done to appeal to this
population.

16. 2. Early Adopters
- These are people who represent opinion leaders. They enjoy leadership roles, and
embrace change opportunities. They are already aware of the need to change and so are
very comfortable adopting new ideas. Strategies to appeal to this population include how-
to manuals and information sheets on implementation. They do not need information to
convince them to change.

17. 3. Early Majority
- These people are rarely leaders, but they do adopt new ideas before the average person. That
said, they typically need to see evidence that the innovation works before they are willing to adopt
it. Strategies to appeal to this population include success stories and evidence of the innovation's
effectiveness.

18. 4. Late Majority - These people are skeptical of change, and will only adopt an innovation
after it has been tried by the majority. Strategies to appeal to this population include
information on how many other people have tried the innovation and have adopted it
successfully.

19. 5. Laggards
- These people are bound by tradition and very conservative. They are very skeptical of
change and are the hardest group to bring on board. Strategies to appeal to this population
include statistics, fear appeals, and pressure from people in the other adopter groups.

20. Diffusion of Innovation Theory

21. The stages by which a person adopts an innovation, and whereby diffusion is accomplished,
include
• awareness of the need for an innovation,
• decision to adopt (or reject) the innovation,
• initial use of the innovation to test it, and
• continued use of the innovation.

22. There are five main factors that influence adoption of an innovation, and each of these factors is at
play to a different extent in the five adopter categories.
1. Relative Advantage - The degree to which an innovation is seen as better than the idea, program, or
product it replaces.
2. Compatibility - How consistent the innovation is with the values, experiences, and needs of the
potential adopters.
3. Complexity - How difficult the innovation is to understand and/or use.
4. Triability - The extent to which the innovation can be tested or experimented with before a
commitment to adopt is made.
5. Observability - The extent to which the innovation provides tangible results.

23. Limitations of Diffusion of Innovation Theory
There are several limitations of Diffusion of Innovation Theory, which include the following:
 Much of the evidence for this theory, including the adopter categories, did not originate in public health
and it was not developed to explicitly apply to adoption of new behaviors or health innovations.
 It does not foster a participatory approach to adoption of a public health program.
 It works better with adoption of behaviors rather than cessation or prevention of behaviors.
 It doesn't take into account an individual's resources or social support to adopt the new behavior (or
innovation).

24. This theory has been used successfully in many fields including communication,
agriculture, public health, criminal justice, social work, and marketing. In public
health, Diffusion of Innovation Theory is used to accelerate the adoption of important
public health programs that typically aim to change the behavior of a social system.
For example, an intervention to address a public health problem is developed, and the
intervention is promoted to people in a social system with the goal of adoption (based
on Diffusion of Innovation Theory). The most successful adoption of a public health
program results from understanding the target population and the factors influencing
their rate of adoption.

25. The Data-Information-Knowledge-Wisdom framework (DIKW)
Nursing informatics was created by the merge of three well established scientific fields: Information science,
Computer science and Nursing science.
Historically, the development of the DIKW framework was urged by a search for a new theoretical model
explaining the emerging field of Nursing Informatics in 1980-90s. In their seminal work, Graves and Corcoran
(1989) defined that data, information, and knowledge are fundamental concepts for the discipline. Their
framework was widely accepted by the international nursing community

26.  Data: are the smallest components of the DIKW framework. They are commonly
presented as discrete facts; product of observation with little interpretation (Matney
et al., 2011). These are the discrete factors describing the patient or his/her
environment.
 Information: might be thought of as “data + meaning” (Matney et al., 2011).
Information is often constructed by combining different data points into a
meaningful picture, given certain context. Information is a continuum of
progressively developing and clustered data; it answers questions such as “who”,
“what”, “where”, and “when”.

27. Knowledge: is information that has been synthesized so that relations and interactions are defined
and formalized; it is build of meaningful information constructed of discrete data points (Matney et
al., 2011). Knowledge is often affected by assumptions and central theories of a scientific discipline
and is derived by discovering patterns of relationships between different clusters of information.
Knowledge answers questions of “why” or “how”.
Wisdom: is an appropriate use of knowledge to manage and solve human problems (American
Nurses Association, 2008; Matney et al., 2011). Wisdom implies a form of ethics, or knowing why
certain things or procedures should or should not be implemented in healthcare practice. In nursing,
wisdom guides the nurse in recognizing the situation at hand based on patients’ values, nurse’s
experience, and healthcare knowledge. Combining all these components, the nurse decides on a
nursing intervention or action.

28. The boundaries of the DIKW framework components are not strict; rather, they are interrelated and
there is a “constant flux” between the framework parts. Simply put, data is used to generate
information and knowledge while the derived new knowledge coupled with wisdom, might trigger
assessment of new data elements

29. INFORMATION THEORY
Contemporary information theory has its roots in the development of telephony. During the middle of last
century, an engineer at Bell Telephone Laboratories, Dr. Claude E. Shannon, innovated information
theory by extending the mathematical observations of Boltzmann, Szilard, von Neumann, and Wiener in
the area of physics, quantum mechanics, and particle physics (Weaver, 1949). Dr. Shannon, however,
applied the theory to communication technology, introducing entropy to the theory (Nelson, 2002;
Weaver, 1949)

30. Weaver, who worked at the Sloan-Kettering Institute for Cancer Research, adopted Shannon’s technical
message transmission observations and adapted them with his understanding of the semantics of a
messages meaning (as cited in Nelson, 2002).
Shannon and Weaver’s Information and Communication Model details both the components of a message
and the requirements of delivery.
The data is also stored along the communication pathway for future retrieval and delivery when the patient
presented again. Though this example satisfies Shannon, if the intended recipient were blind, the
information shown on a computer screen would be meaningless, according to Weaver, and would indicate a
limitation to overcome.

31. Evaluating hospital information systems developed, in part, from the Shannon and Weaver model, Bruce
I. Blum (1986) conducted analysis of object (data, information, and knowledge) processing in both
hospital and ambulatory care settings.
He concluded that system designs should reflect the artificial delineation between these three types of
objects and that these systems will benefit practitioners and patients by improving the overall health care
process.
Blum (1986) called for the “integration of existing systems with medical knowledge and knowledge-
based paradigms” in order to have a positive impact on health care delivery in the coming decades.

32. Information theory is concerned with the adaptability of a message through a particular channel for optimum
transmission. In health informatics, as Blum (1986) points out, information theory can be a benefit by
improving
“[1)] structure — the capacity of the facilities and the capacity and qualification of the personnel and
organization,
[2)] process — the changes in the volume, cost and appropriateness of activities,
[3)] outcome — the change in health care status attributed to the object being evaluated” (p. 794).
The major challenges, however, would be initial implementation and acceptance (Blum, 1986).

34. Historical Background of Electronic Health Records
An electronic record composed of health information regarding an individual patient that exists as part of
a complete system designed to provide access to, and management of, such information.
The EHR is developed and managed by the health facility or provider. The term Electronic Health
Record has largely replaced the older “Electronic Medical Record.
Electronic Health Record (EHR)

35. Recognizable efforts in the development of EHR are distinguished by the Nicholas E. Davis Awards of
Excellence Program whose history describes the improvement of EHR in different settings.
The Computer-Based Patient Record Institute (CPRI), founded in 1992. It was an organization
representing all the stakeholders in healthcare, focusing on the clinical applications of information
technology.
It was among the first nationally based organizations to initiate and coordinate activities to facilitate and
promote the routine use of Computer-Based Patient Records (CPRs) throughout healthcare.
The Nicholas E. Davies Awards of Excellence Program

36. The CPRI group on CPR Systems Evaluation developed the CPR project evaluation criteria in 1993
which became the basis in assessing accomplishments of CPR projects and provided the Foundation
of Nicholas E. Davies Awards Excellence Program

37. The Healthcare Information Management Systems Society
Vision - Advancing the best use of information and management systems for the betterment
of health care
Mission - To lead change in the healthcare information and management systems field
through knowledge sharing, advocacy, collaboration, innovation, and community affiliations
Nowadays the Nicholas E. Davies Awards Excellence Program is managed by the Healthcare
Information Management Systems Society, and has the following program objectives:
The Healthcare Information and Management Systems Society (HIMSS) is the healthcare
industry's membership organization exclusively focused on providing global leadership for the
optimal use of healthcare information technology (IT) and management systems for the
betterment of healthcare.

38. Thank you!