applying nursing informatic to your work practice and utilizing DIKW

How does the concept of wisdom in nursing informatics compare to the concept of professional nursing judgment?

ORDER A PLAGIARISM FREE PAPER NOW

What is DIKW and how do you “use” it in your practice(Rehab unit/imfection control)? The conceptual framework underpinning the science and practice of NI centers on the core concepts of data, information, knowledge, and wisdom, also known as the DIKW paradigm. As an aside, it is important to note that this paradigm is not exclusive to nursing, and is in fact used by others who work with data and information. When we assess a patient to determine his or her nursing needs, we gather and then analyze and interpret data to form a conclusion. This is the essence of nursing science. Information is composed of data that were processed using knowledge. Knowledge is the awareness and understanding of a set of information and ways that information can be made useful to support a specific task or arrive at a decision. When we apply previous knowledge to data, we convert those data into information, and information into new knowledge—that is, an understanding of which interventions are appropriate in practice. Thus information is data made functional through the application of knowledge. Wisdom is the appropriate application of knowledge to a specific situation. In the practice of nursing science, one expects actions to be ultimately directed by wisdom. Wisdom uses knowledge and experience to heighten common sense and insight to exercise sound judgment in practical matters. Data: 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. Examples include patient’s medical diagnosis (e.g. International Statistical Classification of Diseases [ICD-9] diagnosis #428.0: Congestive heart failure, unspecified) or living status (e.g., living alone, living with family, living in a retirement community, etc.). A single piece of data, known as datum, often has little meaning in isolation. 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.” For example, a combination of patient’s ICD-9 diagnosis #428.0 “Congestive heart failure, unspecified” and living status “living alone” has a certain meaning in a context of an older adult. Knowledge: Information that has been synthesized so that relations and interactions are defined and formalized; it is a 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.” For healthcare professionals, the combination of different information clusters, such as the ICD-9 diagnosis #428.0 “Congestive heart failure, unspecified” + living status “living alone” with an additional information that an older man (78 years old) was just discharged from hospital to home with a complicated new medication regimen (e.g., blood thinners) might indicate that this person is at a high risk for drug-related adverse effects (e.g., bleeding). • Wisdom: An appropriate use of knowledge to manage and solve human problems (ANA, 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. Benner (2000) presents wisdom as a clinical judgment integrating intuition, emotions, and the senses; using the previous examples, wisdom will be displayed when the homecare nurse will consider prioritizing the elderly heart failure patient using blood thinners for an immediate intervention, such as a first nursing visit within the first hours of discharge from hospital to assure appropriate use of medications (para. 2). Reflect on the examples given by Topaz and create your own application example the DIKW scenario. In the 2015 Nursing Informatics: Scope and Standards of Practice, Ramona Nelson offers a graphic depiction of the DIKW paradigm in NI and how it relates to the evolution of information systems, decision support systems, and expert systems to support clinical practice. Her model indicates that as one moves from data to information to knowledge to wisdom, there is increasing complexity (shown as the X-axis) and increasing interactions and relationships (shown as the Y-axis). Information systems are shown at the intersection of data and information, decision support systems are depicted at the intersection of information and knowledge and expert systems, the most complex of the systems, reside at the intersection of knowledge and wisdom (Figure 6-1). The development of informatics tools to support nursing practice will continue to evolve as we develop more and better understanding of these complex relationships. “The addition of wisdom raises new and important research questions, challenging the profession to develop tools and processes for classifying, measuring, and encoding wisdom as it relates to nursing and informatics education. Research in these directions will help clarify the relationship between wisdom and the intuitive thinking of expert nurses. Such research will be invaluable in building information systems to better support healthcare practitioners in decisionmaking” (ANA, 2015, p.6). Figure 6-1 The Relationship of Data, Information, Knowledge, and Wisdom Copyright Ramona Nelson. Used with the permission of Ramona Nelson, President, Ramona Nelson Consulting at ramonanelson@verizon.net. All rights reserved. Central to the development of robust expert systems is the agreement on and use of standard terminologies that accurately codify and capture the nature of nursing in these electronic systems. Consider that physician contributions to the health of a patient have been codified for some time, i.e., ICD-10. What if we were able to code and thus capture nursing contributions in a similar way? This would help to highlight the specific nursing contributions to patient outcomes. Capturing and Codifying the Work of Nursing There are major efforts under way—internationally through the International Council of Nurses’ (2013) International Classification of Nursing Practice (ICNP) and in many other initiatives among and within countries—in which nurses are attempting to standardize the language of nursing practice (Hannah, White, Nagle, & Pringle, 2009). These efforts are particularly important in the face of the development of EHRs and HIE (health information exchanges) stimulated by the HITECH Act of 2009. The capacity to encourage and enforce consistent nomenclatures that reflect the practice of nurses is now possible. Standardized language gives both the nursing profession and healthcare delivery systems the capability to capture, codify, retrieve, and analyze the impact of nursing care on client outcomes. For example, with the use and documentation of standardized client assessments, including risk measures, interventions based on best practices, and consistently measured outcomes within different care settings and across the continuum of care, there will be an ability to demonstrate more clearly the contributions and impact of nursing care through the analysis of EHR outputs. Additionally, clinical outcomes can be further understood in the context of care environments, particularly implications related to the availability of human and material resources to support care delivery. The standardization of clinical inputs and outputs into EHRs will eventually provide a rich knowledge base from which practice and research can be enhanced, and will inform better administrative and policy decisions (Nagle, White, & Pringle, 2010). Rutherford (2008) echoed these same sentiments: A standardized nursing language should be defined so that nursing care can be communicated accurately among nurses and other health care providers. Once standardized, a term can be measured and coded. Measurement of the nursing care through a standardized vocabulary by way of an ED [electronic documentation] will lead to the development of large databases. From these databases, evidence-based standards can be developed to validate the contribution of nurses to patient outcomes. (para. 5) Thede and Schwiran (2011) identified the benefits of using standardized terminology as (1) better communication among nurse and other healthcare providers, (2) increased visibility of nursing interventions, (3) improved patient care, (4) enhanced data collection to evaluate nursing care outcomes, (5) greater adherence to standards of care, and (6) facilitation of assessment of nursing competency (para. 2). Think about this. Some EHRs measure height in feet and inches, others in centimeters. Weight may be measured in pounds or kilograms. If we want to compare patient data from multiple EHRs in several different healthcare institutions to develop a model to predict the onset of Type II diabetes, these disparate measures will not translate well. Some EHRs force data collection into coded database fields, and these data are more easily analyzed for trends than that same data recorded as free text. Clinicians used to recording data (charting) as text may resist the use of the coded data fields typically presented as dropdown menus in the EHR. As Skrocki (2013) pointed out, “Data interoperability is hindered when clinicians utilize free text documentation. Although text data can be searched with a specific word or word phases, it does not allow for optimal data sharing. When an organization transfers data to another organization, standardized codified data allows for better data interpretation” (p. 77). Although significant progress has been made in this standardization work, it is still evolving. Box 6-1 discusses standardizing terminologies in nursing; it was contributed by Nicholas Hardiker (2011), a leader in the development of standardized languages that support clinical applications of information and communication technology. BOX 6-1 THE NEED FOR STANDARDIZED TERMINOLOGIES TO SUPPORT NURSING PRACTICE Nicholas Hardiker Agreement on the consistent use of a term, such as “impaired physical mobility,” allows that term to be used for a number of purposes: to provide continuity of care from care provider to care provider, to ensure care quality by facilitating comparisons between care providers, or to identify trends through data aggregation. Since the early 1970s, there has been a concerted effort to promote consistency in nursing terminology. This work continues today, driven by the following increasing demands placed on health-related information and knowledge: • Accessibility: It should be easy to access the information and knowledge needed to deliver care or manage a health service. • Ubiquity: With changing models of healthcare delivery, information and knowledge should be available anywhere. • Longevity: Information should be usable beyond the immediate clinical encounter. • Reusability: Information should be useful for a range of purposes. Without consistent terminology, nursing runs the risk of becoming invisible; it will remain difficult to quantify nursing, the unique contribution and impact of nursing will go unrecognized, and the nursing component of electronic health record systems will remain at best rudimentary. Not least, without consistent terminology, the nursing knowledge base will suffer in terms of development and in terms of access, thereby delaying the integration of evidence-based health care into nursing practice. External pressures merely compound this problem. For example, in the United States, the Health Information Technology for Economic and Clinical Health (HITECH) Act, signed in January 2009, provides a financial incentive for the use of electronic health records; similar steps are being taken in other regions. The HITECH Act mandates that EHRs are used in a meaningful way; achieving this goal will be problematic without consistent terminology. Finally, the current and future landscape of information and communication technologies (e.g., connection anywhere, borderless communication, Web-based applications, collaborative working, disintermediation and reintermediation, consumerization, ubiquitous advanced digital content [van Eecke, da Fonseca Pinto, & Egyedi, 2007]) and their inevitable infiltration into health care will only serve to reinforce the need for consistent nursing terminology while providing an additional sense of urgency. This box explains what is meant by a standardized nursing terminology and lists several examples. It describes in detail the different approaches taken in the development of two example terminologies. It presents, in the form of an international technical standard, a means of ensuring consistency among the plethora of contemporary standardized nursing terminologies, with a view toward harmonization and possible convergence. Finally, it provides a rationale for the shared development of models of terminology use—models that embody both clinical and pragmatic knowledge to ensure that contemporary nursing record systems reflect the best available evidence and fit comfortably with routine practice. (McGonigle 110-113) McGonigle, Dee. Nursing Informatics and the Foundation of Knowledge, 4th Edition. Jones & Bartlett Learning, 20170317. VitalBook file. The citation provided is a guideline. Please check each citation for accuracy before use.
Purchase answer to see full attachment