• Xue Chen, Xinyu Li, Yu Liu, Gaoqiong Yao, Jiadan Yang, Juan Li, and Feng Qiu.
• Department of Pharmacy, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
• J Eval Clin Pract. 2021 Oct 1; 27 (5): 1134-1142.

AimsTo utilize lean six sigma (LSS) and failure model and effect analysis (FMEA) to prevent dispensing errors in a Chinese teaching hospital.MethodsMedication errors (MEs) reported to the China Core Group of the international network for the rational use of drugs (INRUD) by pharmacists at the hospital were collected. Following LSS methodology, the data analysis was structured according to define, measure, analyse, improve, and control (DMAIC) phases, and typical LSS tools (Pareto diagrams, brainstorming sessions) were used to determine the risk factors leading to dispensing errors. FMEA was applied to generate the risk priority numbers (RPNs) of MEs events, and key medications targeted for error prevention strategies were identified through quantitative analysis of the impacts of failure. Finally, corrective measures to prevent MEs were implemented and monitored for efficacy.ResultsBefore the implementation of this programme, a total of 603 cases of dispensing errors were reported from the Year 1 to Year 6, reaching an average rate of incidence of 0.33 cases per 10 000 medication orders delivered, and no difference was found between these years (P = .9424). There was also no difference as location, error type, contributing factors, cause classification were considered. We then determined the real cause behind dispensing errors, and a total of 67 medications were targeted for specific error prevention strategies. One year after intervention, progress had been achieved in the following aspects: the incidence rate of dispensing errors was significantly decreased compared with the previous years (0.19, P = .007). Simultaneously, the incidence rate of dispensing errors occurred in outpatient pharmacy (0.04, P = .0008), with junior pharmacists (0.15, P = .0258), with LASA medications (0.06, P = .0319), as well as with memory-based errors were significantly decreased (0.03, P = .0191).ConclusionThe combination of LSS and the FMEA tool can be an efficient approach for helping reduce MEs in pharmacy dispensing.© 2020 John Wiley & Sons, Ltd.

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