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The Practice Specialty of Nursing Informatics

Carolyn Sipes / Carol J. Bickford

ABSTRACT

Nursing informatics is an established nursing specialty. All nurses employ information technologies and solutions in their practice. Informatics nurses are key persons in the design, development, implementation, and evaluation of these technologies and solutions and in the development and enhancement of the specialty’s body of knowledge.

This chapter addresses pertinent concepts, definitions, and interrelationships of nursing, nursing informatics, and healthcare informatics. The evolution of definitions for nursing informatics is presented. The recognition of nursing informatics as a distinct nursing specialty is discussed. Select models and theories of nursing informatics and supporting sciences are described. The identification of various sets of nursing informatics competencies is explained. A collection of international and national organizations of interest to informatics nurses is presented. This chapter also addresses components of the scope of practice and the standards of practice and professional performance for nursing informatics.

INTRODUCTION

Decision-making is an integral part of daily life. Good decisions require accurate and accessible data as well as skill in processing information. At the heart of nursing informatics (NI) is the goal of providing nurses with the data, information, and support for information processing to make effective nursing practice decisions in clinical care, research, education, administration, and policy development. Generation of knowledge and the application of wisdom also occur.

INFORMATICS NURSE/INFORMATICS NURSE SPECIALIST

An informatics nurse (IN) is a registered nurse who has an interest or experience in nursing informatics. Informatics nurse specialists (INSs) are registered nurses prepared at the graduate level (master’s degree or higher) in nursing informatics, informatics, or an informaticsrelated field. An INS functions as a graduate-levelprepared specialty nurse.

Foundational Documents Guide Nursing Informatics Practice

Nursing informatics practice and the development of this specialty have been guided by several foundational documents. These documents are listed in Table 16.1 and described in this section.

In 2001, the American Nurses Association (ANA) published the Code of Ethics for Nurses with Interpretive Statements, a complete revision of previous ethics provisions and interpretive statements that guide all nurses in practice, be it in the domains of clinical care, education, administration, or research. Nurses working in the informatics specialty are professionally bound to follow these provisions. Terms such as decision-making, comprehension, information, knowledge, shared goals, outcomes, privacy, confidentiality, disclosure, policies, protocols, evaluation, judgment, standards, and factual documentation abound throughout the explanatory language of the interpretive statements (American Nurses Association, 2001a). Although cited in the 2015 Nursing Informatics: Scope and Standards of Practice, Second Edition, that resource has been replaced with the contemporary 2015 Code of Ethics for Nurses with Interpretive Statements document that is available at: https://www.nursingworld.org/practice-policy/nursingexcellence/ethics/code-of-ethics-for-nurses/.

ANA’s Nursing: Scope and Standards of Practice, Second Edition (2010), referenced in the Nursing Informatics: Scope and Standards of Practice, Second Edition (American Nurses Association, 2015c), reinforced the recognition of nursing as a cognitive profession and provided the definition of nursing: “Nursing is 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” (p. 9). The exemplary competencies accompanying each of the 16 Standards of Professional Nursing Practice comprised of Standards of Practice and Standards of Professional Performance, reflected the specific knowledge, skills, abilities, and judgment capabilities expected of registered nurses at that time. The standards included data, information, and knowledge management activities as core work for all nurses. This cognitive work began with the critical-thinking and decision-making components of the nursing process that occur before nursing action can begin (American Nurses Association, 2010). Consult Nursing: Scope and Standards of Practice, Third Edition (American Nurses Association, 2015b) for the contemporary definition of nursing and revised standards of nursing practice and professional performance.

The nursing process provides a delineated pathway and process for decision-making. Assessment, or data collection and information processing, begins the nursing process. Diagnosis or problem definition, the second step, reflects the interpretation of the data and information gathered during assessment. Outcomes identification is the third step, followed by planning as the fourth step. Implementation of a plan is the fifth step. The final component of the nursing process is evaluation. The nursing process is often presented as a simplistic linear process with evaluation listed as the last step. However, the nursing process really is very iterative, includes numerous feedback loops, and incorporates evaluation activities throughout the sequencing. For example, evaluation of a plan’s implementation may prompt further assessment, a new diagnosis or problem definition, and decision-making about new outcomes and related plans.

The collection of data about the healthcare consumer, client, patient, management, education, or research situation is guided by a nurse’s knowledge base built on formal and informal educational preparation, evidence and research, and previous experiences. In healthcare, as in most areas of our lives, data, information, knowledge, and wisdom (DIKW) are growing at astronomical rates and demand increasing reliance on computer and information systems for collection, storage, organization and management, analysis, and dissemination. For example, in clinical nursing practice, consider the significant expansion in the amount and types of data that must be collected for legal, regulatory, quality, and other reasons. DIKW might include understanding of the following:

•   Genetic profiles, related to specific healthcare consumer health conditions

•   Information and knowledge about the healthcare environment and services, including data related to:

   billing and reimbursement

   health plans

   available formulary options

•   Standardized nursing terminologies and their capacity to contribute to codification, quantification, and evaluation of delivery of nursing care services (see Chapter 8, “Standardized Nursing Terminologies” for more detailed discussion)

Collecting data in a systematic, thoughtful way, organizing data for efficient and accurate transformation into information, and documenting thinking, decisions, and actions are critical to successful nursing practice. Nursing informatics is the nursing specialty that endeavors to make the collection, management, and dissemination of data, information, and knowledge—to support decisionmaking—easier for the practitioner and healthcare consumer, regardless of the domain and setting.

INFORMATICS AND HEALTHCARE INFORMATICS

Informatics is a science that combines a domain science, computer science, information science, and cognitive science. Thus, it is a multidisciplinary science drawing from varied theories and knowledge applications. Healthcare informatics may be defined as “the integration of healthcare sciences, computer science, information science, and cognitive science to assist in the management of healthcare information” (Saba & McCormick, 2015, p. 232). Healthcare informatics is a subset of informatics, as is nursing informatics. Imagine a large umbrella named informatics comprised of many panels. Each panel represents a different domain science, one of which is healthcare informatics. The healthcare informatics panel could be comprised of many stripes depicting the composite of nursing informatics, dental informatics, public health informatics, etc.

Because healthcare informatics is a relatively young addition to the informatics umbrella, you may see other terms that seem to be synonyms for this same area, such as medical or health informatics. Medical informatics historically was used in Europe and the United States as the preferred term for healthcare informatics but now is evolving to be more clearly realized as a subset of healthcare informatics. Similarly, health informatics may reference informatics used in educating healthcare consumers and/or the general public. As healthcare informatics evolves, so will the clarity in definition of terms and associated scopes of practice.

Healthcare informatics addresses the study and management of healthcare information. A model of overlapping discrete circles could depict the integrated content most often considered representative of the multiple and diverse aspects of healthcare informatics. Healthcare informatics would be the largest encompassing circle surrounding smaller intersecting circles. These aspects include specific content areas such as information retrieval, ethics, security, decision support, patient care, project management including electronic health record (EHR) implementations, system life cycle (SLC) as a subcomponent of project management, evaluation, human– computer interaction (HCI) or user experience, standards, connected health/telehealth, healthcare information systems, imaging, knowledge representation, education, and information retrieval.

Nursing Informatics

Nursing informatics (NI), as a subset of healthcare informatics, shares common areas of science with other health professions and, therefore, easily supports interprofessional education, practice, and research focused on healthcare informatics. Nursing informatics also includes unique components, such as standardized nursing terminologies, that address the special information needs for the nursing profession and healthcare consumers. Nurses practice interprofessionally as well as independently when engaged in clinical and administrative nursing practice. Nursing informatics reflects this duality as well, moving through the continuum of integration and separation as situations and needs demand.

In 1985, Kathryn Hannah proposed a definition that nursing informatics is the use of information technologies in relation to any nursing functions and actions of nurses (Hannah, 1985). In their classic article on the science of nursing informatics, Graves and Corcoran presented a more complex definition of nursing informatics. Nursing informatics is a combination of computer science, information science, and nursing science designed to assist in the management and processing of nursing data, information, and knowledge to support the practice of nursing and the delivery of nursing care (Graves & Corcoran, 1989).

With the development of the first scope of practice statement for nursing informatics, ANA modified the Graves and Corcoran definition to identify nursing informatics as the specialty that integrates nursing science, computer science, and information science in identifying, collecting, processing, and managing data and information to support nursing practice, administration, education, research, and the expansion of nursing knowledge (American Nurses Association, 1994). The explication of the accompanying first standards of practice for NI followed in 1995 with ANA’s publication of the Standards of Practice for Nursing Informatics (American Nurses Association, 1995).

In 2000, the ANA convened an expert panel to review and revise the scope and standards of nursing informatics practice. That group’s work included an extensive examination of the evolving healthcare and nursing environments and culminated in the publication of the Scope and Standards of Nursing Informatics Practice (American Nurses Association, 2001b). This professional document included an expanded definition of nursing informatics that was then slightly revised in the 2008 Nursing Informatics: Scope and Standards of Practice to include wisdom:

Nursing informatics (NI) is a specialty that integrates nursing science, computer science, and information science to manage and communicate data, information, knowledge, and wisdom in nursing practice. NI supports consumers, patients, nurses, and other providers in their decision-making in all roles and settings. This support is accomplished through the use of information structures, information processes, and information technology. (American Nurses Association, 2008, p. 1)

Then, in 2015, ANA’s second edition of Nursing Informatics: Scope and Standards of Practice presented an updated definition:

Nursing informatics (NI) is a specialty that integrates nursing science with multiple information management and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice. NI supports nurses, consumers, patients, the interprofessional healthcare team, and other stakeholders in their decision-making in all roles and settings to achieve desired outcomes. This support is accomplished through the use of information structures, information processes, and information technology. (American Nurses Association, 2015c, pp. 1–2)

ANA has convened an expert group to review and revise the 2015 Nursing Informatics: Scope and Standards of Practice, Second Edition, which may result in further refinement of the current definition. Nursing: Scope and Standards of Practice, Third Edition, (American Nurses Association, 2015b) and the Code of Ethics for Nurses with Interpretive Statements (American Nurses Association, 2015a) will inform that discussion and development effort. These multiple definitions illustrate the dynamic, developing nature of this evolving nursing specialty. Development of different definitions and a healthy debate on those definitions promotes validation of key elements and concepts. A willingness to continue exploring possible definitions can prevent premature conceptual closure, which may lead to errors in synthesis and knowledge development.

Nursing Informatics as a Specialty

Characteristics of a nursing specialty include differentiated practice, a well-derived knowledge base, a defined research program, organizational representation, educational programs, and a credentialing mechanism. In early 1992, ANA recognized nursing informatics as a specialty in nursing with a distinct body of knowledge. Unique among the healthcare professions, this designation as a specialty provided official recognition that nursing informatics is indeed a part of nursing and that it has a distinct scope of practice.

The core phenomena of nursing are the nurse, person, health, and environment. Nursing informatics focuses on the information of nursing needed to address these core phenomena. Within this focus are the metastructures or overarching concepts of nursing informatics: data, information, knowledge, and wisdom. It is this special focus on the information of nursing that differentiates nursing informatics from other nursing specialties.

Nursing informatics is represented in international, national, regional, and local organizations. For example, there is a nursing informatics working group in the American Medical Informatics Association (AMIA) and in the International Medical Informatics Association (IMIA). Nursing informatics is part of the clinical section of the Healthcare Information and Management Systems Society (HIMSS). There are additional organizations such as the American Nursing Informatics Association (ANIA) and the American Academy of Nursing (AAN) Informatics and Technology Expert Panel (ITEP).

Increasingly, nursing school curricula include content, and sometimes complete courses, on information technologies in healthcare and nursing. In 1989, the University of Maryland established the first graduate program in nursing informatics. The University of Utah followed in 1990. Now there are several established in-person and online programs for graduate work as well as doctoral programs in nursing informatics.

Certifications That Support the NI Specialty

Following the publication of the first nursing informatics scope of practice and standards documents, the American Nurses Credentialing Center (ANCC) established a certification process and examination in 1995 to recognize those nurses with basic nursing informatics specialty competencies. The ANCC has used scholarship in nursing-informatics competencies and its own role-delineation studies to develop and maintain the nursing-informatics certification examination. The ANCC-designated NI contentexpert panel has oversight responsibility for the content of this examination and considers the current informatics environment and research when defining the testcontent outline. Application details and the test-content outline are available at https://www.nursingworld.org/our-certifications/informatics-nurse/.

Information for the HIMSS Certified Professional in Health Information and Management Systems (CPHIMS) and Certified Associate in Health Information and Management Systems (CAHIMS) certifications are available at https://www.himss.org/health-it-certification.

Other Certification Programs That Support the NI Role. As noted by McGonigle and Mastrian (2015), NI roles include those of project manager, consultant, educator, researcher, product developer, decision support/outcomes manager, advocate/policy developer, clinical analyst/system specialist, and entrepreneur. For example, the certification for:

Project manager is the Project Management Professional (PMP), supported by the Project Management Institute: https://www.pmi.org/certifications/types/project-management-pmp

Nurse Executive and Nurse Executive-Advanced (NE & NE-A):

https://www.nursingworld.org/our-certifications/nurse-executive-advanced

Nurse Educator–Certified Nurse Educator (CNE): http://www.nln.org/Certification-for-NurseEducators/cne.</

The Certified E-Discovery Specialist (CEDS) Certification is a new certification available at https://www.aceds.org/page/certification. The CEDS Certification covers the full spectrum of e-discovery including project management and planning, document review, data processing, ethics, international discovery, information management, and predictive coding.

Two other informatics-related certification programs are offered by the American Health Information Management Association (AHIMA). The first certification is as a registered health information administrator (RHIA). The RHIA manages patient health information and medical records, administers computer information systems, collects and analyzes patient data, and uses various classification systems and medical terminologies. The second AHIMA certification is as a registered health information technician (RHIT). In this specialty, professionals ensure the completeness and accuracy of patient data entered into computer systems and focus on coding of diagnoses and patient procedures.

Expanding interest and concern about information, Internet, and cybersecurity have spawned other certifications, such as Certified Information Systems Security Professional (CISSP) including the Healthcare Certified Information Systems Security Professional (HCISSP) described at https://www.isc2.org/Certifications/CISSP. The Certified Ethical Hacker (CEH) certification is described at https://www.eccouncil.org/programs/certifiedethical-hacker-ceh/. The CEH is a skilled professional who knows how to look for weaknesses and vulnerabilities in target systems and uses the same knowledge and tools as a malicious hacker, but in a lawful and legitimate manner to assess the security posture of a target system(s).

Models for Nursing Informatics

The foundations of nursing informatics are the core phenomena and nursing-informatics models. The core phenomena are data, information, knowledge, and wisdom and the transformations that each of these undergo.

Models are representations of some aspect of the real world, show perspectives of a selected aspect, and may illustrate relationships. Models evolve as knowledge about the selected aspect changes and are dependent on the worldview of those developing the model. It is important to remember that different models reflect different viewpoints and are not necessarily competitive; that is, there is no one, right model.

A clinical-information-system (CIS) model shows how modelling can be used to organize different concepts into a logical whole. The purpose of this model is to depict system components, influencing factors, and relationships that need to be considered when attempting to capture the complexities of professional nursing practice.

Select models are presented here to provide further perspectives on nursing informatics, to demonstrate the different views of scholars and practitioners describing the same thing, and to show that nursing informatics is an evolutionary, theoretical, and practical science. Again, remember that there is no one right model and the models presented here are not exhaustive of the possible perspectives of nursing informatics.

Graves and Corcoran’s seminal work included a model of nursing informatics. Their model placed data, information, and knowledge in sequential boxes with one-way arrows pointing from data to information to knowledge. The management processing box was directly above, with arrows pointing in one direction from management processing to each of the three boxes (Graves & Corcoran, 1989). The model is a direct depiction of their definition of nursing informatics.

In 1986, Patricia Schwirian proposed a model of nursing informatics intended to stimulate and guide systematic research in this specialty. Her concern was over the sparse volume of research literature in nursing informatics. The model provided a framework for identifying significant information needs, which, in turn, can foster research. In this model, there were four primary elements arranged in a pyramid with a triangular base: the raw material (nursing-related information), the technology (a computing system comprised of hardware and software), the users surrounded by context, and the goal (or objective) toward which the preceding elements were directed. Bidirectional arrows connected the three base components of raw material, user, and computer system to form the pyramid’s triangular base. The goal element was placed at the apex of the pyramid to show its importance. Similarly, all interactions between the three base elements and the goal were represented by bidirectional arrows (Schwirian, 1986).

Turley, writing in 1996, proposed another model in which the core components of informatics (cognitive science, information science, and computer science) were depicted as intersecting circles. In Turley’s model, nursing science was a larger circle that completely encompassed the intersecting circles. Nursing informatics was the intersection between the discipline-specific science (nursing) and the area of informatics (Turley, 1996).

McGonigle and Mastrian (2012) developed the foundation of knowledge model. The base of this model showed data and information distributed randomly. From this base, transparent cones grew upward and intersected. The upward cones represented acquisition, generation, and dissemination of knowledge. Knowledge processing was represented by the intersections of these three cones. Feedback circled and connected all of the cones. The cones and feedback circle were dynamic in nature (McGonigle & Mastrian, 2012).

In 2015, McGonigle and Mastrian expanded on the model as a framework for NI Practice. The three overarching standards of NI practice were incorporation of theories, concepts and principles from appropriate sciences into informatics practice; the integration of ergonomics and human–computer interaction (HCI) into the informatics care plan; and the systematic determination of the social, legal, and ethical impact of an informatics solution within nursing and healthcare. Evolving NI roles included those of project manager, consultant, educator, researcher, product developer, decision support/outcomes manager, advocate/policy developer, clinical analyst/system specialist, and entrepreneur (McGonigle & Mastrian, 2015).

The Empowerment Informatics Framework (EIF) model provides a framework where nurses use technology to (a) guide chronic illness interventions through the integration of patient self-management and nursing informatics, (b) focus on self-management research, and (c) promote ethical technology use by practicing nurses. The model is used to guide intervention design as well as evaluation and support nurses’ ethical use of technology to guide nursing practice using technology that prioritizes patient needs (Knight & Shea, 2014). The EIF framework supports both quantitative and qualitative research where the inclusion of new self-management interventional goals can provide unique measurable outcomes. When patients subjectively define health outcomes—along with systemslevel objective outcome measurements—this provides a new way of looking at and delivering patient-centered care. This perspective supports informatics nurses in advocating for a patient-focused approach in the application of theory and evidence to patient self-management (Knight & Shea, 2014).

Theories and Other Models Supporting Nursing Informatics

A theory is a scholarly, organized view of some aspect of the world (reality). Theories can describe, explain, predict, or prescribe selected phenomena within this reality. The concepts within a theory are interrelated. Testing of these relationships through research is how theories gain or lose supporting evidence (Karnick, 2013). A profession needs theories to build evidence for the existence of a unique body of knowledge (Bond et al., 2011).

Theories can be classified as grand, middle-range, and situation-specific or practice theories. Grand theories are broad in scope and the most complex of the three classifications. Practice theories are the most specific of the three and usually provide prescriptions or directions for practitioners. Middle-range theories are somewhere in the middle of these two ends—they are more specific than grand theories but not as prescriptive as practice theories.

Theories are part of an interrelated, circular triad: research, theory, and practice. For example, research leads to the development of theory, which can be applied to practice. Alternatively, practitioners can raise questions about clients and/or activities related to clients, which leads to research that generates theory. As pointed out earlier, theory generates research for testing. Validation of a theory can guide practice.

Theories related to and supportive of nursing informatics are numerous. These theories include—but are not limited to—information, cognitive, computer science, systems, change management, organizational behavior, management, and group dynamics. Many of the theories and concepts provide the organizational framework applicable to the project management process and other roles now identified with NI.

Nursing Theories. Nursing theories are about nursing practice—a nurse’s interactions or relationships with individuals, families, groups, communities, or populations (also known as patients, clients, healthcare consumers)—focused on applying the nursing process. Grand nursing theories discuss nursing practice in broad terms, providing different worldviews of how, when, and why nurses relate to patients, clients, and healthcare consumers. Middle-range nursing theories might describe a particular phenomenon of interest to nurses, explain how one phenomenon relates to one or more other phenomena, or predict how a phenomenon affects nurses and others. Any nursing theory might be useful for an informatics nurse, since informatics nurses work with individuals, groups, and communities. It is beyond the scope of this chapter to examine particular theories and how they can be applied. Informatics nurses are encouraged to consult the numerous texts on nursing theory. An overview of the main theories and models that are applicable to NI and project management as well as other processes are listed in Table 16.2.

Novice to Expert. Benner’s theory is based on the 1980 Dreyfus Model of Skills Acquisition (Dreyfus & Dreyfus, 1980, as cited in Benner, 1984/2001) which maintains that nurses advance through five stages in their professional development but may return to an earlier stage if they move to a different practice. Patricia Benner’s Novice-toExpert Theory (1984/2001) supports a framework that knowledge development is required for skills acquisition in nursing practice. Patricia Benner and other nurse educators adapted this model—also known as the stages of clinical competence—to explain how nursing students and professional nurses acquired nursing skills based on knowledge development and experience:

•   Novice: Little experience follows rules provided for each situation and is not flexible in real-life situations.

•   Advanced beginner stage: Some experience can make some decisions regarding correct actions.

•   Competent stage: With 2 to 3 years experience, a learner is able to tell what is important and what is not important in assessing a given situation.

•   Proficient practitioner: Proficient practitioner can see a situation in terms of the larger setting or environmental situation based on experience—use intuition in decision-making.

•   Expert intuitively understands a situation and immediately connects action to this understanding (Ajay, 2003).

Change Management Theories. Change processes entail not only structures and ways of doing tasks, but also the performance, expectations, and perceptions of all involved parties. The informatics nurse specialist (INS) has a unique understanding of the nursing issues that can affect the change process, and thus, as the primary change agent, is in a key position to facilitate positive implementation outcomes, such as the implementation of clinical information systems (CIS) in healthcare settings. While there are many models and theories of planned change, two of the most frequently used to provide a framework for change management are Lewin’s theory of planned change—also known as force field analysis—and Rogers’ diffusion of innovations model.

Lewin’s basic planned-change model has three stages: unfreezing, moving, and refreezing. Unfreezing involves overcoming inertia and dismantling the existing mindset. Defense mechanisms or resistance patterns must be mitigated or bypassed. Measuring the perceptions of those who will experience the change is an important part of this stage. Applying the force field analysis process, the change agent must uncover barriers or rewards that will influence unfreezing or changing a behavior—that is, what is important to the people or WIIFM (what’s in it for me?).

In the second stage, called moving, the behavioral change occurs. Typically, this stage is a period of confusion. People are aware that the old ways are being challenged but do not yet have a clear picture of how to replace the old ways. The third—final—stage is “refreezing.” A new mind-set has formed, and the comfort level is returning to previous levels (Wells, Manuel, & Cunning, 2011).

Rogers’ diffusion of innovation is a process for communicating how, why, and at what rate new ideas and technologies spread through cultures and was formalized in a 1962 book called Diffusion of Innovations. Rogers identified five specific groups of innovation adopters: innovators, early adopters, early majority, late majority, and laggards. The distribution (or percentage of each category in a population) approximates a bell curve. Each adopter’s willingness and ability to adopt an innovation would depend on their awareness, interest, evaluation, trial, and adoption. Rogers also presented characteristics for each category of adopter (Rogers, 2003).

Rogers identified characteristics of an innovation that most affect the rate of adoption—defined as either positive or negative. These characteristics are relative advantage, compatibility, complexity, trialability, and observability. Positive characteristics include the following:

•   Relative advantage—refers to the degree to which an innovation is perceived as better than the idea it replaces

•   Compatibility—the degree to which an innovation is perceived as being consistent with existing values, past experiences, and needs of potential adopters

•   Trialability—the degree to which an innovation may be tried out or experimented with

•   Observability—the degree to which the results of an innovation are visible to others

Rogers defined complexity as a negative characteristic. It is the degree to which an innovation is perceived as difficult to understand and use. In summary, Rogers asserted that innovations perceived by potential adopters as having greater relative advantage, compatibility, trialability, and observability, and less complexity will be adopted more rapidly than other innovations (Rogers, 2003).

Along with the concept of different categories of innovation adopters, Rogers proposed a five-stage model for the diffusion of innovation:

•   Stage 1 is knowledge—learning about the existence and function of the innovation.

•   Stage 2 is persuasion—becoming convinced of the value of the innovation.

•   Stage 3 involves the adopter making a decision— committing to the adoption of the innovation.

•   Stage 4 is implementation—putting it to use.

•   Stage 5 is confirmation—the ultimate acceptance (or rejection) of the innovation (Rogers, 2003).

How does this theory apply to the work of an informatics nurse? Understanding the social forces and attitudes underlying innovation diffusion is critical for effective management of the process of implementing an informatics innovation, such as a new or replacement healthcare information system. Because of the investment of time, energy, and economic and human resources in implementing an information system, organizations, especially leadership, must be aware of the human elements influencing successful implementation and subsequent adoption. To be adopted, innovations must appeal to people. People must see something in an innovation that they like, need to make their workflows work more efficiently, or want.

Information Science. Information science focuses on the gathering, manipulation, classification, storage, and retrieval of recorded knowledge. Information science can be socially oriented, focused on humans and machines, and closely linked to communications and human behavior. Information science tries to understand problems from the perspective of the stakeholders and applies information and technology as needed to solve the problems. Three important branches of information science are information retrieval, human–computer interactions from the perspective of knowledge manipulation, and information handling within a system (human or machine).

For classic information theory, a central concern has been the engineering problem of the transmission of information over a noisy channel. The decisive event that established the discipline of information theory, and brought it to immediate worldwide attention, was the publication of Shannon’s classic paper, A Mathematical Theory of Communication, in the Bell System Technical Journal in 1948 (Shannon, 1948). Soon after this publication, Weaver coauthored with Shannon a book titled The Mathematical Theory of Communication (1949). This work introduced the concept of the communication channel. This communication channel consists of a sender (a source of information), a transmission medium (with noise and distortion), and a receiver (whose goal is to reconstruct the sender’s messages).

Other core concepts include encoding and decoding. Encoding transforms the content via encryption and compression techniques to preserve the information, makes it unreadable, and uses less digital storage or transmission bandwidth. The receiver has to decode the message. Shannon and Weaver, for the first time, introduced the qualitative and quantitative model of communication as a statistical process underlying information theory.

Communication. Communication theory uses these information science core concepts and additional principles to analyze information transfer and the effectiveness and efficiency of communications. Within a communication model, Bruce Blum presented a taxonomy, with definitions, of the central concepts of data, information, and knowledge concepts adopted by NI.

•   Data is defined as discrete entities that are described objectively without interpretation— sometimes referred to as being “raw.”

•   Information is data that are interpreted, organized, structured, or processed so that it can be displayed or presented for human use (Blum, 1985).

•   Knowledge is information that has been synthesized so that interrelationships of data and information are identified and formalized.

Many informatics theorists have added the concept of Wisdom to Blum’s theory (Matney, Brewster, Sward, Cloyes, & Staggers, 2011). Think of wisdom as the appropriate use of knowledge in managing and solving problems. As noted earlier, these terms are on a continuum of simple to complex, beginning with data and proceeding toward wisdom. The DIKW framework is one of the core conceptual frameworks for the practice of nursing informatics. However, in order for the framework to be effective, nurses must define knowledge, within EHRs, to accurately capture the context of nursing practice (Matney, 2013).

Systems Theory. Systems theory relates to the properties of systems as a whole and focuses on the organization and interdependence of relationships within a system. A system is any set (group) of interdependent or temporarily interacting parts. Parts are systems themselves and are composed of other parts which may be open or closed. An open system can be influenced by events outside of the actual or conceptual boundaries. Open systems usually have semipermeable boundaries that may restrict the exchange of selective components but allow free exchange of all other components as it interacts with the surrounding environment. Information systems and people are usually considered open systems, although there can be closed systems within these open systems. A closed system has an impermeable boundary and does not interact with the surrounding environment.

The basic model of a system is one of inputs crossing the boundary, processing of the input through the system (throughput), and the emergence through the system boundary of some kind of output. Along with this basic model, there are other common elements to every open system. These are feedback, control, environment, and goal.

Systems are constantly changing. There are six key concepts related to understanding system change: dynamic homeostasis, entropy, negentropy, specialization, reverberation, and equifinality. Dynamic homeostasis preserves the character of a system through its growth. From an organizational perspective, look at this concept by considering that open organizational systems use internal review processes to modify their environmental scanning, input, transformation, and output processes in order to adapt to the changing environment, while still staying focused on their core competency. These modifications lead to quantitative and qualitative growth of an organization’s ability to respond to future events. The same processes hold true for organizational programs and projects such as an information system implementation.

While there are many definitions of entropy, all seem to point in the same direction—entropy is a measure of the degree of disorder in a system or breaking down into the smallest parts. In communication theory, entropy is a measure of the loss of information in a transmitted message. Negentropy is the reverse of entropy and means things become more ordered, structured, organized. Specialization is a specific focus on areas such as NI. Reverberation is the idea that when one part of a system changes, other parts of the system are affected. The effects on other parts of the system can lead to expected and unexpected consequences. Equifinality is the principle by which a system can get to the same end (or goal) from various different routes. That is, the same inputs can result in the same outputs but by different processes. If you (as a subsystem) are required to obtain a book via input from the system (e.g., a course on informatics), you may return to the system with the book (a form of output) that you may have picked up from a friend, a bookstore, or a library.

Behavioral and Social Sciences. The study of behavior is the focus of the behavioral and social sciences. These two terms are often combined or used interchangeably when examining how people act alone (as individuals) and with others. Behavior can include emotions, cognition, and motivation. Social processes and acts can be status (demographic, economic, or cultural), levels of social context, and biosocial interactions (Office of Behavioral and Social Sciences, 2010). Current increasing emphasis on identifying, tracking, and addressing social and behavioral determinants of health have created interesting challenges and opportunities for the healthcare informatics community.

Organizational Behavior. Organizational behavior is a distinct field focused on the study of organizations where organizations are examined, using methods drawn from economics, sociology, political science, anthropology, and psychology. Both individual and group dynamics in an organizational setting are studied, as well as the nature of the organizations themselves. Organizational behavior is becoming more important in the global economy as people with diverse backgrounds and cultural values learn to work together effectively and efficiently. A healthy organization reflects a balance among the participants of autonomy, control, cooperation, and collaboration. Understanding how organizations behave, and how a specific organization behaves, can guide planning for information system implementations.

Management Science. Management science uses mathematics and other analytical methods to help make better decisions, generally in a business context. While often considered synonymous with operations research (OR), management science is differentiated from OR by a more practical, rather than academic, orientation. More frequently, knowledge and application of management science are expected of the INS.

Management science processes involve using rational, systematic, science-based techniques to inform and improve decisions of all kinds. Naturally, the techniques of management science are not restricted to business applications but may be applied to military situations, clinical decision support, public administration, charitable groups, political groups, or community groups. Some of the methods within management science—especially relevant to the INS—are decision analysis, optimization, simulation, forecasting, game theory, graph theory, network problems, transportation-forecasting models, mathematical modeling, and queuing theory, as well as many others.

Group Dynamics. Group dynamics is a social science field that focuses on the nature of groups. Urges to belong or to identify may make for distinctly different attitudes (recognized or unrecognized), and the influence of a group may rapidly become strong, influencing or overwhelming individual activities.

Within any organization, formal and informal groups apply different degrees of pressure on individuals. Informal groups have a powerful influence on the effectiveness of an organization, even subverting its formal goals. But the informal group’s role is not limited to resistance. The impact of the informal group upon the larger formal group depends on the norms that the informal group sets. Thus, the informal group can make the formal organization more effective, too.

Bruce Tuckman (1965) proposed a four-stage model, called Tuckman’s stages, for a group. Tuckman’s model states that the ideal group decision-making process should occur in four stages:

•   Forming (pretending to get on or get along with others)

•   Storming (letting down the politeness barrier and trying to get down to the issues even if tempers flare up)

•   Norming (getting used to each other and developing trust and productivity)

•   Performing (working in a group to a common goal on a highly efficient and cooperative basis)

Others. Chaos, cognitive, and computer science theories are important to the development and application of the NI role, knowledge, and competencies. Application and integration of such theories are required as the specialty evolves to include more and higher-level responsibilities in the high-technology driven healthcare environments foundational to today’s clinical practice.

COMPETENCIES

Benner’s framework described above is based on the concept that to become competent in a skill requires knowledge and experience. Benner (1984/2001) proposed that “experience-based skill acquisition is safer and quicker when it rests upon a sound educational base” (p. 6) and is related to the years of experience in the field of nursing, including specialty practice areas. This desired change in skills involves the evolution from a novice level to advanced beginner to competent to proficient to, finally, an expert level. Every nurse must continually exhibit the capability to acquire and then demonstrate specific skills, beginning with the very first experiences. Most individuals can be described as novices having no experience, then are expected to begin developing competencies through knowledge acquisition and by performing tasks that refine their skills. The advanced beginner can marginally demonstrate acceptable performance, having built on lessons learned in an expanding experience base. Individuals at these levels often need oversight by teachers or experienced colleagues to help structure the learning experience and support appropriate and successful workplace decision-making and action (Benner, 2004).

Increased proficiency over time results in enhanced competencies reflecting mastery and the ability to cope with and manage many contingencies. Continued practice, combined with additional professional experience and knowledge, allows the nurse to evolve to the proficient level of appreciating the rules and maxims of practice and the nuances that are reflected in the absence of the normal picture. The expert has the capacity to intuitively understand a situation and immediately target the problem with minimal effort or problem solving (Benner, 2004).

Staggers, Gassert, and Curran are most often cited as the first published research identifying the informatics competencies necessary for all nurses (Staggers, Gassert, & Curran, 2001). Their conceptual framework included computer skills, informatics knowledge, and informatics skills as the informatics competencies. Their research, however, only identified informatics competencies for four levels of nurses: beginning nurse, experienced nurse, informatics specialist, and informatics innovator. The comprehensive list of 304 competencies posed a significant challenge for professional development and academic faculties wishing to address each of the competencies when preparing curricula and then teaching educational programs for all skill levels.

Sipes (2016) and other authors maintain that “in today’s high-tech world, expectations of the healthcare industry are that all nurses will have informatics competencies, including project management skills which are critical for improved quality outcomes and safety for patients. This is not only true for nurses in clinical practice management roles but administration, nurse executives, educators, policy development, NI, other leadership, such as INS roles as well” (p. 1.). Project management knowledge and skills applicable to the roles of nurses, informatics nurses, and INSs include assessment, planning, implementation, and evaluation follow-up. Within each domain, requirements include knowledge and skills such as communication, collaboration, ethics, quality of practice, and leadership previously discussed in this chapter (Sipes, 2016). These competencies are also associated with the standards of practice described in Nursing Informatics: Scope and Standards of Practice, Second Edition (American Nurses Association, 2015c) discussed later in this chapter.

Nursing informatics has evolved beyond the definition of data management defined early on by Staggers, Gassert, and Curran, but is still considered by many as the primary and only skill of an informatics nurse specialist. McGonigle, Hunter, Sipes, and Hebda (2014) suggested that even today “there is a lack of understanding of exactly what nursing informatics is in the way of skills needed or how they can and should be applied to practice” (p. 324). Further competencies-definition work was completed by the workgroup that developed the 2008 NI scope and standards document. Their review of the literature culminated in a two-page matrix that included delineation by computer and information literacy (American Nurses Association, 2008).

The Technology Informatics Guiding Educational Reform (TIGER) initiative moved from an invitational conference to volunteer task forces, also known as collaboratives, to systematically develop key content related to discrete topics, including nursing informatics competencies. The TIGER collaborative on competencies focused on the minimum set of informatics competencies needed by every nurse. These competencies are organized into three categories: basic computer skills, information literacy, and information management (The TIGER Initiative, n.d.).

The National League for Nursing (NLN) has developed a set of competencies for nursing educators. These may be found on the NLN Web site (http://www.nln.org/professional-development-programs/competencies-for-nursing-education/nurse-educatorcore-competency). Carter-Templeton, Patterson, and Russell’s 2009 study presents an updated summary and analysis of other work done on developing nursinginformatics competencies. These authors noted variation in content, presentation, and audience among the sets of competencies reviewed.

Instruments to assess perceived levels of NI competence are emerging in the scholarly literature. Yoon, Yen, and Bakken (2009) described the validation of an instrument titled the Self-Assessment of Nursing Informatics Competencies Scale. This scale incorporates selected items from the work of Staggers, Gassert, and Curran along with items addressed in a specific NI curriculum (Yoon et al., 2009). In 2013, Hunter, McGonigle, and Hebda published the results of validity and reliability testing of an online self-assessment tool for all nurses entitled TIGER-based Assessment of Nursing Informatics Competencies (TANIC). TANIC incorporates all of the competencies identified by the TIGER Institute (Hunter, McGonigle, & Hebda, 2013). The advanced level 3 and level 4 competencies identified by Staggers, Gassert, and Curran were organized into an online instrument by McGonigle, Hunter, Hebda, and Hill. This self-assessment instrument for informatics nurse specialists, titled Nursing Informatics Competencies Assessment Level 3 and Level 4 (NICA L3/L4©), has demonstrated reliability and validity (McGonigle, Hunter, Hebda, & Hill, 2013). The tools have been operationalized in academic specialty informatics courses to analyze and improve informatics competencies through additional research (Sipes et al., 2016).

Another competency tool is the HIMSS-funded HITComp (Health Information Technology Competencies) tool developed for international use for eHealth and digital skills research, educational development, skills assessment, and career progression. Although the tool inconsistently defines the different roles of what nurses do across countries, there is value in the lessons learned from international collaboration (Sipes et al. 2017).

ORGANIZATIONS AS RESOURCES

Many organizations have emerged to provide information resources and value-added membership benefits that support those individuals interested in healthcare and nursing informatics. Clinical specialty and other professional organizations have also appreciated the evolving healthcare-information-management focus and have established organizational structures such as informatics sections, divisions, workgroups, or special-interest groups. Some have incorporated informatics and information system technology initiatives in strategic plans with dedicated staffing and ongoing financial support. In many instances, informal networking groups have evolved into international organizations with hundreds of members connected via the Internet.

The diverse nature, purposes, and activities of the multiple informatics organizations provide opportunities and resources for everyone interested in nursing informatics. Information about a few of these organizations is provided here. The information for each group was adapted from each group’s Web site. Only national or international informatics-related organizations with nursing groups are included. The groups presented here are accessible to individual nurses for more information and/or participation. This content is in no way an exhaustive presentation. To learn more about these organizations and others, consult the Internet, informatics colleagues, and the scholarly literature. A list of these organizations is presented in Table 16.3.

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