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The term “knowledge worker” was first coined by management consultant and author Peter Drucker in his book, The Landmarks of Tomorrow (1959). Drucker defined knowledge workers as high-level workers who apply theoretical and analytical knowledge, acquired through formal training, to develop products and services. Does this sound familiar?
Nurses are very much knowledge workers. What has changed since Drucker’s time are the ways that knowledge can be acquired. The volume of data that can now be generated and the tools used to access this data have evolved significantly in recent years and helped healthcare professionals (among many others) to assume the role of knowledge worker in new and powerful ways.
In this Assignment, you will consider the evolving role of the nurse leader and how this evolution has led nurse leaders to assume the role of knowledge worker. You will prepare a PowerPoint presentation with an infographic (graphic that visually represents information, data, or knowledge. Infographics are intended to present information quickly and clearly.) to educate others on the role of nurse as knowledge worker.
To Prepare:
Review the concepts of informatics as presented in the Resources.
Reflect on the role of a nurse leader as a knowledge worker.
Consider how knowledge may be informed by data that is collected/accessed.
The Assignment:
Explain the concept of a knowledge worker.
Define and explain nursing informatics and highlight the role of a nurse leader as a knowledge worker.
Include one slide that visually represents the role of a nurse leader as knowledge worker.
Your PowerPoint should Include the hypothetical scenario you originally shared in the Discussion Forum. Include your examination of the data that you could use, how the data might be accessed/collected, and what knowledge might be derived from that data. Be sure to incorporate feedback received from your colleagues’ responses.
My week 1 discussion Post:
In the given scenario, a patient with a history of skin cancer visits a healthcare facility for ongoing treatment and management. It is geared toward tapping the documented medical data of the past concerning the patient for the better health care services: past medical history, previous treatments, biopsy results, medication records, and genetic information. Such informative data will be important in realizing the state of the patient’s condition, therefore monitoring the progression of his disease and, in turn, tailoring an effective treatment regime.
The data could be collected from various sources such as electronic health records (EHRs), patient health history forms, pathology reports, and previous clinical notes. This would centralize information using an EHR system that allows health providers to retrieve and update information regarding a patient in real time (Chelladurai & Pandian, 2022). The same system, therefore, can integrate information from specialists and other health providers in the past who could offer a more comprehensive view of the patient’s health. From the clinical perspective, Data analysis can reveal patterns in cancer recurrence and the efficacy of treatments. This information can be leveraged to improve patient outcomes.
This data provides valuable knowledge regarding the best practices for managing skin cancer in similar cases. For instance, previous damage to the patient would greatly inform the current and future intervention results. The nurse leader interpreting such information can work by the ‘clinical reasoning and judgment’ in the context of what the implications are for the health, prognosis, potential side effects of the therapies, or for that matter, the state-of-the-art practice of skin cancer management (Klenke-Borgmann et al., 2022). Through synthesizing all the information together, the nurse leader develops a care plan explicitly suited to favor maximum outcomes for the patient, hence the heavy role of the contribution it makes within healthcare and serving as a vital contribution to the body of nursing knowledge.
References
Chelladurai, U., & Pandian, S. (2022). A Novel Blockchain-Based Electronic Health Record Automation System for Healthcare. Journal of Ambient Intelligence and Humanized Computing, 13(1), 693-703.
Klenke-Borgmann, L., Cantrell, M. A., & Mariani, B. (2020). Nurse Educators’ Guide to Clinical Judgment: A Review of Conceptualization, Measurement, and Development. Nursing Education Perspectives, 41(4), 215-221.
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