Using Failure Mode, Effect and Criticality Analysis to improve safety in the cancer treatment prescription and administration process

Journal of Pharmaceutical Policy and Practice(2023)

引用 0|浏览11
暂无评分
摘要
Background Administering cancer drugs is a high-risk process, and mistakes can have fatal consequences. Failure Mode, Effect and Criticality Analysis (FMECA) is a widely recognized method for identifying and preventing potential risks, applied in various settings, including healthcare. The aim of this study was to recognize potential failures in cancer treatment prescription and administration, with a view to enabling the adoption of measures to prevent them. Methods This study consists of a FMECA. A team of resident doctors in public health at the University of Padua examined the cancer chemotherapy process with the support of a multidisciplinary team from the Veneto Institute of Oncology (an acknowledged comprehensive cancer center), and two other provincial hospitals. A diagram was drafted to illustrate 9 different phases of chemotherapy, from the adoption of a treatment plan to its administration, and to identify all possible failure modes. Criticality was ascertained by rating severity, frequency and likelihood of a failure being detected, using adapted versions of already published scales. Safety strategies were identified and summarized. Results Twenty-two failure modes came to light, distributed over the various phases of the cancer treatment process, and seven of them were classified as high risk. All phases of the cancer chemotherapy process were defined as potentially critical and at least one action was identified for a single high-risk failure mode. To reduce the likelihood of the cause, or to improve the chances of a failure mode being detected, a total of 10 recommendations have been identified. Conclusions FMECA can be useful for identifying potential failures in a process considered to be at high risk. Safety strategies were devised for each high-risk failure mode identified.
更多
查看译文
关键词
Patient safety,Proactive management,Chemotherapy administration,Cancer treatment
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要