Feb 23, 2024 NURS 6050 The Nurse Leader as Knowledge Worker Essay
NURS 6050 The Nurse Leader as Knowledge Worker Essay
NURS 6050 Assignment The Nurse Leader as Knowledge Worker
Introduction
This presentation will discuss the concept of a knowledge worker. It explains nursing informatics and discusses the role of a nurse leader as a knowledge worker. In addition, I will present the hypothetical scenario that might benefit from the collection and application of data. I will explore the data that can be used, how it might be collected, and the knowledge derived from the data.
Concept of a Knowledge Worker
A knowledge worker plays a key role in the organization in generating knowledge. They obtain, maneuver, interpret and apply information to carry out multidisciplinary, complex organizational work (Field & Chan, 2018). Besides, knowledge workers analyze data and use their expertise to address problems, generate ideas, and develop new products and services.
Knowledge work is often complex, and knowledge workers need certain skills, abilities, and acquaintance with factual and theoretical knowledge (Field & Chan, 2018). Therefore, knowledge workers must obtain, access, recall, and apply data, interact well with others, and have the ability and motivation to obtain and enhance these skills.
Knowledge workers’ roles include making decisions whereby they work with ideas. Their duties focus on intellectual rather than physical power and are characterized by non-repetitive tasks (Field & Chan, 2018). In addition, they use various methods and techniques to address problems and are authorized to decide what work methods to employ to complete their job tasks. Knowledge workers include: scientists, professionals, educators, and information system designers.
Nursing Informatics
Nursing informatics is a specialty that incorporates nursing science with analytical sciences and information management. It seeks to discover, define, manage, and convey data, information, and knowledge in nursing practice (Moore et al., 2020). Nursing informatics supports nurses, the interprofessional health care team, healthcare consumers, patients, and stakeholders in decision-making in various roles and settings to attain desired outcomes. It supports this through information structures, processes, and technology (Moore et al., 2020).
Nursing informatics skills are applied to:
Create data structures and software tools to support nursing practice (McGonigle & Mastrian, 2017).
Keep EHR in line with best practices for data management, processing, and organization.
Apply analytics in evaluating and facilitating nursing processes (McGonigle & Mastrian, 2017).
Facilitate communication among healthcare and IT professionals.
Train providers on the best use of EHRs and CDSS (McGonigle & Mastrian, 2017).
Peter Drucker, a management consultant and author, coined the term “knowledge worker” in his book The Landmarks of Tomorrow (1959). Knowledge workers, according to Drucker, are high-level workers who apply theoretical and analytical knowledge gained through formal training to develop products and services. Is this something you’ve heard before?
Nurses are highly educated professionals. What has changed since Drucker’s time are the methods for acquiring knowledge. The amount of data that can now be generated, as well as the tools used to access it, have evolved significantly in recent years, allowing healthcare professionals (among many others) to take on the role of knowledge worker in new and powerful ways.
Information science is mainly focused on input, processing, output, and feedback of data and information through the integration of information technology with the need to understand stakeholders’ perspectives engaged in the process and using IT are required (McGonigle & Mastrian, 2017). The essence of this discussion is to describe a scenario where data can be used to solve problems in healthcare.
Scenario
Access to medical records is essential for healthcare professionals in ascertaining that patients get the best care (McGonigle & Mastrian, 2017). A scenario of focus is immunizations in facilities where nurse practitioners work with different stakeholders like schools, parents and providers. These practitioners help organizations keep immunization records. The challenging part with the job occurs when families move across states without their immunization data and are not certain of a child having been immunized or not. Parents may have to connect with their past physicians or clinics, previous state’s immunization registry or the previous school. However, these struggles can be mitigated through the establishment of data sharing using a central hub or database for all information on vaccinations in the country or across states and organizations.
Presently, information on vaccine is collected using an online database called Immunization Information System (IIS) which tracks vaccines administered to patients. The database also offers information on the next vaccine (CDC, 2019). Using this hub, one can collect all data and create a central hub comprising of vaccine information from each entity. The existence of the central vaccine hub would enable providers to access records for their new patients and offer the necessary immunizations without any fear. Through the database, the professionals can monitor their patient’s vaccination history and make effective decisions and judgment concerning the types of vaccines that they can have or not.
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The central hub or database can offer a host of knowledge and ideas to providers. For example, healthcare professionals can see the coverage levels in different parts or areas and assess the potential of any disease outbreaks (Nagle et al., 2017). The professionals can also see how effective the communities have attained a herd immunity that works to stop or reduce the spread. For instance, millions of people are now vaccinated against the Coronavirus disease of 2019 (COVID-19); either for the first dose or both. The implication is that providers are using information from a central database or hub to evaluate the vaccination status of different people and assess the percentage of those immunized against COVID-19. Community immunity or herd immunity occurs when a significant number of people in a targeted population get vaccinated against a certain disease. Through this approach, it becomes difficult for a disease to spread to unvaccinated individuals.
Nurse leaders can use clinical reasoning and judgment from this knowledge since patients would not miss the expected vaccine doses and also ensure that those who have received do not have extra and unnecessary doses. Through this knowledge, nurse leaders will have the ability to identify contraindications and notices concerning certain vaccines into patients’ systems (Nagle et al., 2017). The providers would also be aware of the locational changes of patients and the need to integrate their vaccination history for effective monitoring and tracking of conditions.
Conclusion
Informatics remains a critical part of effective care delivery and nurse leaders should integrate data to make informed and effective decisions, especially in connection to vaccinations. Having a central hub is essential in developing a sharing and information exchange platform for providers and patients to enhance vaccination success across states, especially at this time. The scenario demonstrates the need for healthcare providers to work collaboratively to develop acceptable models to share health information.
References
Centers for Disease Control and Prevention (CDC) (2019). About Immunization Information
Systems. https://www.cdc.gov/vaccines/programs/iis/about.html
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge,
(4th ed.) Burlington, MA: Jones & Bartlett Learning.
Nagle, L., Sermeus, W., & Junger, A. (2017). Evolving role of the nursing informatics specialist.
In J. Murphy, W. Goossen, & P. Weber (Eds.), Forecasting Competencies for Nurses in the Future of Connected Health, 212–221. Clifton, VA: IMIA and IOS Press
Discussion: The Application of Data to Problem-Solving
My current healthcare organization attends to numerous patients diagnosed with chronic illnesses such as cardiovascular diseases, diabetes, and cancer. The risk factors for most of these conditions can be identified early through screening and mitigated or approached taken to reduce the impact of the disease. Healthcare data can be potentially useful in predicting a patient’s risk for a disease such as Type 2 Diabetes, which has been a major concern due to its associated morbidity and mortality. The Electronic Health Record (EHR) can be used to collect a patient’s data including, their past medical history, family, social history, and lifestyle practices (Dash et al., 2019). The data can be collected on the initial contact with a patient, and health providers should be advised to take a comprehensive patient history in the first contact.
The data can be used to predict a patient’s degree of risk to a particular chronic illness such as diabetes. For instance, health providers can identify risk factors for diabetes such as the history of overweight, obesity, or high blood pressure, positive family history of diabetes, sedentary lifestyle, smoking, and excessive alcohol consumption. The data can guide health providers to make data-driven decisions to enhance a patient’s outcomes such as, requesting additional screenings or providing patient education on weight management and adoption of healthy lifestyles (Dash et al., 2019). Furthermore, for patients diagnosed with diabetes, the health provider can access the data in the EHR to monitor their treatment plans and guide on pharmacological management to promote better outcomes.
A nurse leader can use patient data from EHR to strategically plan and lead the healthcare team in developing treatment plans for patients. Nurse leaders can also analyze patients’ data from different demographic groups and identify what factors limit patients from achieving the desired health outcomes (McGonigle & Mastrian, 2017). Furthermore, the data can be used to form knowledge on ways to enhance clinical practice and new ways to provide patient care, to enhance health outcomes.
References
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 54. https://doi.org/10.1186/s40537-019-0217-0
McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.
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