FMEA法在PIVAS抗肿瘤药物调配全流程风险管理中的应用

Application of FMEA Method in Risk Management of the Entire Process of PIVAS Antitumor Drugs Formulation

关键词:  失效模式与效应分析  静脉用药集中调配中心  抗肿瘤药物  风险管理

Key words:  Perform Failure Mode and Effects Analysis  Pharmacy Intravenous Admixture Service  Antitumor Drugs  Risk Management

摘要:

目的 提高静脉用药集中调配中心（PIVAS）抗肿瘤药物的调配质量，保障临床用药安全有效。方法 对PIVAS抗肿瘤药物调配全流程进行失效模式与效应分析（FMEA），找出风险点并计算其风险优先值（RPN)，将RPN值较高的风险点列为优先改善对象，提出改进措施并对改善结果进行评价。结果 在PIVAS抗肿瘤药物调配全流程中，共找出16个需优先改善的风险点，研究团队从医嘱审核、临床宣教、环境监测、打包下送和滴注时间管理等几个主要方面对其进行整改。经过干预后，16个高风险点的RPN值总和由808降至318，全部降低为低风险，降幅达60.6％。医嘱差错件数、调配差错次数、环境监测不达标次数及配送差错次数等经改进后均显著下降（P＜0.05）。结论 将FMEA应用于PIVAS抗肿瘤药物调配全流程风险管理，能够有效提高抗肿瘤药物的调配质量，降低差错。

Abstract:

OBJECTIVE Improve the dispensing quality of antitumor drugs in pharmacy intravenous admixture service（PIVAS）, and ensure the safety and effectiveness of clinical medication. METHODS Perform Failure Mode and Effects Analysis (FMEA) on the entire process of PIVAS antitumor drugs formulation, identify risk points and calculate their Risk Priority Value (RPN). List high-risk points with high RPN values as priority improvement targets, propose improvement measures, and evaluate the improvement results. RESULTS In the entire process of PIVAS antitumor drugs dispensing, a total of 16 risk points that need to be prioritized for improvement were identified. The research team rectified them from several main aspects, including medical order review, clinical education, environmental monitoring, packaging and delivery, and drip time management. After intervention, the total RPN values of 16 high risk points decreased from 808 to 318, all of which were reduced to low-risk, with a decrease of 60.6%. Among them, the number of errors in medical orders, the number of errors in the dispensing process, unsuitable environmental requirements, and delivery errors have been significantly improved after improvement (P<0.05). CONCLUTION Applying FMEA to the entire process risk management of PIVAS antitumor drug admixture can effectively improve the quality of anti-tumor drug formulation and reduce error rates.