Problem Background
Nurse understaffing and turnover is one of the central problems for the modern healthcare system in the US. Moreover, nurse shortage is expected to grow considerably in the nearest future due to aging population, aging workforce, nurse burnout, and violence in healthcare settings (Haddad & Toney-Butler, 2022). The problem forces scholars and nurse managers to look for ways for addressing the problems. One of the most innovative ways to address the problem of nurse turnover was the center of the attention in a recent article featured by Fierce Healthcare, which stated that AI can help healthcare managers to automate and optimize HR processes to reduce the time needed to hire and increase retention rates (Burky, 2022). First, this paper focuses on selection and justification of the topic. Second, it provides arguments about how the topic will impact the nurses practice. Finally, the paper discusses how informatics skills and knowledge were used in the process of developing the paper.
Topic Selection
The primary topic of this paper is nurse understaffing and how it can be addressed. Nurse understaffing is a significant bother for the current healthcare system, as it is associated with negative outcomes for various stakeholders. First, nurse understaffing negatively affects patient outcomes, which is of central importance in patient-centered care. Glette et al. (2017) stated that insufficient number of nurses might be associated with increased patient harm and mortality. Kiekkas et al. (2019) concluded that insufficient nurse staffing is associated with a higher incidence of hypoxemia and arterial hypotension. Metcalf et al. (2018) surveyed hospital managers and revealed a significant correlation between the number of missed treatments and staffing of front-line employees. In other words, the effects of nurse understaffing on patient health and safety is negative.
Second, nurse understaffing is associated with increased costs due to both explicit and implicit costs. The explicit costs include the cost of hiring and training of new employees, while implicit costs include the productivity loss associated with decreased number of employees during the hiring process and the drops in the quality of care associated with increased number of medical error (Haddad & Toney-Butler, 2022). Finally, nurse understaffing negatively affects nurse satisfaction and retention (Burky, 2022; Haddad & Toney-Butler, 2022). Decreased number of nurses leads to increased workload of nurses, which leads to stress, lack of work-life balance, and burnout (Burky, 2022; Haddad & Toney-Butler, 2022).
The problem of nurse understaffing and turnover became even more pertinent due to the COVID-19 pandemic. The pandemic added to the stressors that lead to nurse turnover, including increased workplace violence and deteriorating work-life balance among nurses (Burky, 2022). Therefore, the problem of nurse turnover and understaffing need to be addressed using all the available methods. Using high-tech solutions, such as artificial intelligence (AI) and internet of things (IoT). The article by Burky (2022) discusses one of the possible solutions to the problem by discussing the us of AI to select candidates and moderate HR practices to reduce stress of nurses and turnover.
Impact on Practice
Utilization of AI is expected to help nurse managers to optimize interaction process with the staff. According to Burky (2022), Trusted Health’s nurse staffing platform based on AI, called Works, has several improvements for the hiring process. First, the platform automatically sorts through nursing shifts to determine which shifts need hiring (Burky, 2022). The platform uses predictive algorithms to determine the need for new employees as soon as it emerges. As a result, the platforms allow to start the hiring process timely to prevent staff-related problems (Burky, 2022). A timely-started hiring process can help to decrease the implicit cost of turnover, which is associated with lost productivity of the workforce.
Second, the AI algorithms help to find the right candidates for the right jobs. The platform sorts through resumes and skills of the potential hires to find the best placement for them (Burky, 2022). As a result, newly-hired nurses have higher person-environment fits, which is crucial for solving the problem of nurse shortage. According to Xiao et al. (2021), higher person-environment fit leads to increased workplace satisfaction and reduced turnover intentions in healthcare employees. Thus, AI-based software can help to improve nurse retention rates.
Finally, the proposed solution is also expected to optimize the scheduling process altogether, which is expected to have a twofold effect on nurse turnover. On the one hand, automatic scheduling will reduce the time nurse managers spend on scheduling, which will free their time for other HR-related activities, such as improving employee morale and organizational commitment (Burky, 2022). On the other hand, the schedules will be created based on rigorous quantitative data, which will increase the effectiveness of workforce (Burky, 2022). As a result, the hospitals will be able to use the full potential of the workforce.
While there are clear positive sides of HR automation associated with using AI, there are some drawbacks of the system. In particular, increased HR automation leads to decreased subjective and personal contact (Chrisos, 2019). Algorithms cannot measure the culture and accomplishments of employees, which can be seen only by a human being (Chrisos, 2019). Thus, utilization of AI for improving nurse hiring and retention has limited use.
Use of Nurse Informatics
Nurse informatics skills were used in several ways while working on the assignment. First, nurse informatics includes understanding how knowledge can be extracted from online sources. Several relevant evidence-based peer-reviewed research articles were used to support the argument in the present paper. Nurses are required to review recent evidence concerning their practice to keep their knowledge up-to-date. Therefore, nursing informatics skills are crucial to maintain a high level of expertise in patient care. This assignment demonstrated that the author of the paper can use nursing informatics skills to search for relevant research that support the argument of the paper. Additionally, this assignment required the knowledge in the latest innovation in the digital world, such as AI, IoT, machine learning, and real-time data utilization to acquire in-depth understanding of the topic under analysis Without such knowledge, it would be impossible to realize the importance and benefits of implementation of AI technology in nurse management discussed by Burky (2022).
References
Burky, A. (2022). From finding the right candidates to keeping them, how hospitals are using AI to address workforce needs. Fierce Healthcare. Web.
Chrisos, M. (2019). What Are the Positive and Negative Impacts of Automation in HR? TechFunnel. Web.
Glette, M.K., Aase, K., & Wiig, S. (2017). The relationship between understaffing of nurses and patient safety in hospitals—A literature review with thematic analysis. Open Journal of Nursing, 7, 1387-1429. Web.
Haddad, L., & Toney-Butler, T. (2022). Nursing Shortage. StatPearls. Web.
Kiekkas, P., Tsekoura, V., Aretha, D., Samios, A., Konstantinou, E., Igoumenidis, M.,… Fligou, F. (2019). Nurse understaffing is associated with adverse events in postanaesthesia care unit patients. Journal of clinical nursing, 28(11-12), 2245-2252.
Metcalf, A., Wang, Y., & Habermann, M. (2018). Hospital unit understaffing and missed treatments: Primary evidence. Management Decision, 56(10), 2273-2286. Web.
Xiao, Y., Dong, M., Shi, C., Zeng, W., Shao, Z., Xie, H., & Li, G. (2021). Person–environment fit and medical professionals’ job satisfaction, turnover intention, and professional efficacy: A cross-sectional study in Shanghai. PloS one, 16(4), e0250693. Web.