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.
Reference: Drucker, P. (1959). The landmarks of tomorrow. New York, NY: HarperCollins Publishers.
Resources
Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.
WEEKLY RESOURCES
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 original discussion
The Application of Data to Problem-Solving
Late diagnosis of sepsis in hospitalised adult patients is a common issue in my healthcare organisation. Access to real-time clinical information via electronic health records (EHRs) and clinical decision support systems would be especially advantageous to this scenario (Chen et al., 2023). Vital signs, lab values (lactate, WBC count), medication administration, nursing assessment, patient history, etc. would all be included. They may be gathered automatically, for example using bedside monitoring systems, laboratory interfaces and nurse documentation in the EHR (Hants et al., 2023).
These would be consolidated in a shared dashboard that enables nurses and nurse leaders to recognise any trends that signify early signs of deterioration in sepsis. Patterns could be detected using informatics tools and an alert could be raised if abnormal findings are detected simultaneously (Adegoke, 2024). Digital health systems and clinical decision support systems are shown to have positive effects on nursing decision making and patient safety outcomes (Christensen & Rotegård, 2023). Furthermore, mobile technologies and machine learning systems can improve the quality of timely decision making and provide evidence-based, targeted interventions (Glanville et al, 2023).
The information gained from this information may be used to find patients who are at risk earlier, to recognize patterns that lead to a precipitous change in the patient’s condition, and to learn which interventions are most effective. Nurse leaders would interpret alerts, prioritize patient care, allocate staff and apply evidence-based protocols, using their clinical reasoning and clinical judgment. Informatics also makes a contribution to the creation of learning health systems that strive to continuously enhance patient levels of care using an ongoing analysis of data (van Velzen et al., 2023). Through the process of converting raw data into knowledge, nurse leaders can help to create better patient outcomes, decrease mortalities, and increase organizational quality improvement efforts.