Topic and Rationale
For the healthcare sector, nursing informatics is vital. It helps to reduce the level of stress and chance of mistakes and align better information exchange. Moreover, using the newest approaches, it is possible to address the most nagging issues and find solutions to them. Thus, nurse understaffing, shortage, and turnover are the main problems of the modern healthcare sector. Moreover, the problem will become more significant in the future because of the aging population, burnout, and violence in healthcare (Haddad & Toney-Butler, 2022). Understaffing negatively impacts patients’ outcomes, meaning that there is a higher risk of missed treatments if understaffing exists (Metcalf et al., 2018). Lack of nurses might also be associated with higher mortality rates in units (Glette et al., 2017). For this reason, it is vital to find a potent solution that might help to address the negative tendency and eliminate it. AI is viewed as one of the possible tools to address turnover and reduce it (Burky, 2022). Technology can help automate most processes within healthcare, such as planning, reducing the time needed to hire, and improving retention rates (Burky, 2022). In such a way, the information provided above proves the relevance of the selected topic and its significance. The nursing shortage is linked to increased costs, lower nursing and client satisfaction, and retention (Haddad & Toney-Butler, 2022). The higher workload resulting from the decreased number of specialists leads to a higher chance of a mistake. For this reason, it is vital to understand how AI can be used to address the issue.
AI Impact on Staffing and Turnover
In general, it is expected that the implementation of AI will help to attain positive outcomes and successfully manage the problem of understaffing and turnover. For instance, using AI platforms, such as Works, it is possible to achieve several significant improvements in the staffing process (Burky, 2022). The program uses specific algorithms to analyze the needs for employees and shifts and offers numerous options to fill existing and future gaps (Burky, 2022). As a result, it is possible to expect enhanced interaction with potential candidates, their selection, hiring, and retaining. The hospitals will have a pool of potential candidates who can be used when a certain vacancy emerges (Bukry, 2022). It will be a significant step towards resolving the problem of understaffing and nursing shortage. Moreover, the timely staffing process initiated based on data provided by AI will help decrease the implicit cost of turnover. The reduced risks of adverse outcomes will help to save costs needed for their management and address patients’ dissatisfaction. Additionally, AI applications might analyze numerous employees’ applications and ensure the right candidates are selected for the right vacancies. It will help to create a positive and effective environment with higher engagement rates and reduced turnover intentions (Xiao et al., 2021). Finally, AI can optimize scheduling and time management, reducing stress and work overload.
At the same time, it is vital to consider potentially negative impacts. Reliance on technology reduces personal interaction, which might impact the atmosphere within a collective and cooperation between individuals (Chrisos, 2019). Moreover, AI lacks an understanding of the corporate culture, meaning that current accomplishments and interactions might be disregarded. It might impact the effectiveness of various leadership styles and cultural incorporation.
Nursing Informatics Skills Used for the Assignment
When working on the offered assignment, it was vital to use nursing informatics skills. To create the basis for the discussion, it was vital to perform an Internet search for credible data that can support the major arguments used in the paper. Moreover, nursing informatics implies an enhanced understanding of how knowledge can be extracted from the selected sources. Information from the selected peer-reviewed articles was employed to support the major assumptions and prove the importance of AI in healthcare. It required the ability to investigate the discovered source, find the main ideas, and rephrase them or quote when necessary. At the same time, it is inappropriate to cite other investigators’ ideas as it will not expand the existing body of knowledge. It means that they were integrated into the body of the paper to ensure the current research is relevant and offers fresh ideas. It also required the correct analysis of the level of evidence and facts related to practice to understand the latest tendencies and how they are essential for practice. It requires looking for other sources, comparing them, and performing an Internet search to guarantee the correctness and credibility of conclusions formulated in the course of research. Furthermore, the project required knowledge of innovation in technologies such as AI, their major peculiarities and how they are used to look for possible applications, and how they can improve the work of the healthcare sector. Finally, the assignment was performed by using critical and analytical skills necessary for constructing the argument by using available resources and evidence.
Pros and Cons of AI in Addressing Staffing Issues
However, when discussing the role of AI in addressing the problem of staffing, it is vital to consider both advantages and disadvantages that might be associated with integrating the solution. As stated previously, using innovations in healthcare leads to enhanced results and reduced burnout, which is attained due to several factors. First, improved planning and scheduling lead to lower pressure and workload, which is vital for outcomes. Second, timely staffing and hiring procedures contribute to better unit functioning, planning, and further evolution, which is also one of the evident pros of the proposed solution. In such a way, the positive alterations mentioned above lead to reduced burnout and turnover rates and help medical units to function effectively. At the same time, as with any technology, AI has some specific drawbacks that should also be considered while implementing it. First, AI applications cannot consider the existing organizational culture and the behavioral patterns peculiar to teams within a particular unit. It means that there is a high risk of deteriorated relations within a collective because of the lack of human factors and subjective attachments. Moreover, AI might fail to consider existing leadership issues and models while planning and making decisions about staffing (Chrisos, 2019). It might create the basis for problematic followership and the inability to align effective interaction between leaders and subordinates. In such a way, most disadvantages associated with the use of AI to address staffing issues are linked to the lack of personal aspects (Chrisos, 2019). It means that managers should be ready to perform additional measures to support high motivation levels among nurses and ensure they have positive relations with each other.
Conclusion and Future
Altogether, it is possible to admit that the healthcare sector experiences numerous challenges nowadays. Understaffing, burnout and high turnover rates are one of the most topical issues that impact the quality of care and patient outcomes. For this reason, their addressing and resolution are the primary tasks of specialists working within the sector. Under these conditions, nursing informatics can be viewed as an integral component of the sphere’s future. The examples provided above show that existing technologies can help to promote the positive change required at the moment. AI can help to address staffing issues in several ways. Platforms such as Works might process information about employees, their skills, and their experiences to ensure a hospital has a pool of specialists needed to fill existing gaps. Moreover, Ai is effective in planning and scheduling, which will reduce stress and burnout among nurses. As a result, technologies will save time for caring and building relations, which is essential for interpersonal relations. That is why it is vital to recommend focusing on technologies as the method to boost effectiveness within healthcare. Leaders should facilitate innovation integration as it is the way to minimize the number of mistakes because of the human factor and create the basis for future improvement. As one of the most promising technologies, AI should be broadly used in nursing due to its ability to address staffing and turnover issues. Resolving these problems will help to improve the quality of patient care and contribute to better outcomes. In conclusion, further investigation of how AI and technologies can be used in nursing is necessary. It will help perform tasks requiring analysis of big amounts of data and providing accurate solutions.
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.
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.