In the case study, a patient was misidentified with another patient with a similar name. As a result of a series of small errors, a costly and dangerous procedure was performed on a wrong patient. In order to identify the reason for the matter root cause analysis can be applied. According to Latino, Latino, and Latino (2019), and why something happened. The process of root caused analysis includes three steps: data root because analysis consists of three aspects, which are identifying what, how collection, cause charting, and root cause identification (Latino et al., 2019). These steps are followed by generation of recommendations.
Data Collection and Analysis
Data collection and analysis for root because analysis is difficult to overestimate. Without adequate practices of data collection, it would be impossible to reconstruct the events of the past and conduct root cause analysis. Reliable information about actions and inactions that led to the emergence of a problem is crucial for answering the first question of root cause analysis. Data analysis helps to answer two other questions by carefully assessing every aspect of the event. One of the most common mistakes of data analysis is trying to identify one central cause of the event (Latino et al., 2019). In real-world situations, there are usually several reasons for mistakes in the process of care. Thus, willing to find one major reason may limit the measures for preventing such mistakes in the future (Latino et al., 2019).
Avoiding the Latent Medical Error
In order to understand what preventative measures should have been used, it is critical to understand the root caused of the problem and find adequate strategies for addressing it. The analysis of the case study demonstrates that no single action led to the problem; instead, it is a series of failures that led to the emergence of the problem. The defences that failed include communication, protocols for patient identification, teamwork within services, coordination between services, and informed consent process. Thus, addressing any of the problems may have led to avoiding the problem. Measures that may have prevented the issues include on-the-job training about the importance of patient identification protocols. Additionally, the promotion of a safety culture that encourages the staff to recognize and report unsafe conditions may have helped to improve all the defenses mentioned above.
Preventing Human Mistakes
Humans make mistakes for a variety of external and internal reasons. Some of the reasons for human mistakes include the lack of knowledge due to inconsistent training, increased stress, work overload, lack of careful job instructions, and sicknesses. While mistakes may occur regardless of how well the system works, quality management can help avoid recurrent mistakes and minimize the occurrence of mistakes in general.
The mistakes described in the case scenario may have been prevented if the managers utilized the robust process improvement (RPI) method, which is a systematic approach to problem-solving. RPI is a combination of several practices, including lean, six sigma, and change management. In other words, workplace culture should be based on the principles of continuous improvement that aims at reducing inconsistencies in the performance. The improvements need to be made based on the results of root cause analysis that suggests possible interventions for avoiding the problem in the future. Each of the recommendations needs to be carefully evaluated and implemented using best practices if found relevant.
References
Latino, M. A., Latino, R. J., & Latino, K. C. (2019). Root cause analysis: Improving performance for bottom-line results. CRC Press.