Multifactorial Medication Mishap RCA
In the present instance, a fifty-year-old healthy man made a medication error. Utilizing a Root Case Analysis (RCA) is both recommended and advantageous because it allows for not only the precise identification of what went wrong but also the utilization of the information to reconcile the issue and provide medical personnel with guidance and education to ensure that the incident does not occur again.
Root cause analysis aids in determining what, how, and why an event occurred, thereby preventing its recurrence. 2004. (Rooney and Vanden Heuvel. p. 45). The objective of the RCA isn’t really to see a problem with an individual in any case, but by recognizing and taking out any blunders that might cause unfavorable impacts, get quality consideration for future circumstances.
NSG 468 Assignment 4 Multifactorial Medication Mishap RCA
Additionally, the RCA can be utilized to identify products that are performing well. To put it plainly, “a RCA takes a gander at every one of the reasons something happened that are not promptly self-evident, instead of zeroing in on a solitary reason” (Zulkowski, 2018. para. 1).
Data collection, casual factor charting, root cause identification, and recommendation generation and implementation are all essential steps in the RCA process. Without adequate data collection, it would be impossible to comprehend, analyze, and address any underlying causes. The casual factor charting is important because it gives an investigator a way to keep the information they collect organized so they can identify possible solutions to the problem.
NSG 468 Assignment 4 Multifactorial Medication Mishap RCA
Another step, root cause identification, can be carried out following these actions. The causes of the incident are determined in this step. At last, proposal age and execution can happen to guarantee that the variables won’t be rehashed.
There are different apparatuses that can be utilized too in these circumstances. One of these is the Failure Modes and Effects Analysis (FMEA), which can be used in advance of any negative events. It is a “quality administration procedure for recognizing known as well as potential disappointment modes inside a framework, cycle, item as well as administration before they happen with the goal that proactive moves would be feasible to be made” (Shaker, et al., 2019. para 1).
NSG 468 Assignment 4 Multifactorial Medication Mishap RCA
Using this tool, weaknesses can be found in advance, allowing for changes to be made immediately. This helps us achieve our goal of avoiding situations that could harm our patients, their families, and even our employees. The Plan-Do-Study-Act (PDSA) tool is another one that works very well. It gives people the chance to find problems in their system, plan how to fix them, and then test and put the plans into action to see if they work. Change must be accepted through the use of this tool.
The organizations above and below the area implementing the cycle need to be in agreement and willing to accept the results for PDSA cycles to be successful (Ungvarsky, 2019, para. 10). Involving these devices in regular practice to comprehend issues when, and even previously, they happen and afterward tracking down the right method for guaranteeing the issues are fixed and won’t happen again is basic to keep patients safe and get quality consideration.
Reference:
Rooney J.J., Vanden Heuvel, L.N. (2004) Root cause analysis for beginners. Quality Basics, July 2004. Retrieved from
http://asq.org/quality-progress/2004/07/quality-tools-rootcause-analysis-for-beginners.pdf
Shaker, F., Shahin, A., & Jahanyan, S., (2019) Developing a two-phase QFD for improving FMEA: An integrative approach. International Journal of Quality & Reliability Management, 36(8), 1454-1474. Retrieved from
https://doi.org/10.1108/IJQRM-07-2018-0195
Ungvarksy, J.(2019). PSDA cycle. Salem Press Encyclopedia of Health. Retrieved from
Zulkowski, K. (2018) Root cause analysis: An effective QI tool. World Council of Enterostomal Therapists Journal, 38(1), 35-39. Retrieved from
