Your unit data reflect an upward trend in blood administration errors. Is this likely an individual failure or a system failure? Which performance improvement theory or model would you use to address it?
Solution
Errors in the medical field significantly impact the patient’s health and the healthcare facility’s overall reputation; therefore, it is important and highly recommended that all healthcare providers deliver the best services to mitigate the risk of medical errors. Blood administration errors are a type of medical error that hinders the health and well-being of the patient; therefore, when there is an upward trend in this problem, it is essential to take the necessary actions to stop it. An increase in the risk of blood administration errors over a period is likely to be a system error because the system does not change over this period (Hawkins & Morse, 2022). Therefore, this is more a system than a human error and requires a proper performance improvement model to identify the cause and supply the necessary methods to manage the problem.
The best performance improvement model is the root cause analysis, which identifies the problem, gathers data, analyzes the data, develops the solutions, and offers monitoring and evaluation. In this model, the organization or hospital will determine and address the underlying cause of the blood administration errors without shifting blame to the healthcare personnel managing the patients in the healthcare facilities (Singh et al., 2024). In the first phase of this model, the team leading this performance improvement initiative will identify the problem and highlight its nature and scope. With this, they will gather and analyze the data using diagrams to highlight the possible causes. Developing and implementing solutions is the fourth step in helping address the identified problems satisfactorily. Monitoring and evaluating the solutions is the last phase and helps determine whether the solutions effectively address the issue.
References
Hawkins, S. F., & Morse, J. M. (2022). Untenable expectations: nurses’ work in the context of medication administration, error, and the organization. Global qualitative nursing research, 9, 23333936221131779. https://doi.org/10.1177/23333936221131779
Singh, G., Patel, R. H., Vaqar, S., & Boster, J. (2024). Root cause analysis and medical error prevention. In StatPearls [internet]. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK570638/