Yuanyuan Jiang1, Hongmin Jiang2, Siyi Ding1, Qin Liu1. 1. Department of Clinical Laboratory, Second Xiangya Hospital, Central South University, Changsha, PR China. 2. Department of Clinical Laboratory, Second Xiangya Hospital, Central South University, Changsha, PR China. Electronic address: 1026622941@qq.com.
Abstract
BACKGROUND: Timely delivery of correct results has long been considered as the goal of quality management in clinical laboratory. With increasing workload as well as complexities of laboratory testing and patient care, the traditional technical adopted like internal quality control (IQC) and external quality assessment (EQA) may not enough to cope with quality management problems for clinical laboratories. We applied failure mode and effects analysis (FMEA), a proactive tool, to reduce errors associated with the process beginning with sample collection and ending with a test report in a clinical chemistry laboratory. Our main objection was to investigate the feasibility of FMEA in a real-world situation, namely the working environment of hospital. METHODS: A team of 8 people (3 laboratory workers, 2 couriers, 2 nurses, and 1 physician) from different departments who were involved in the testing process were recruited and trained. Their main responsibility was to analyze and score all possible clinical chemistry laboratory failures based on three aspects: the severity of the outcome (S), the likeliness of occurrence (O), and the probability of being detected (D). These three parameters were multiplied to calculate risk priority numbers (RPNs), which were used to prioritize remedial measures. Failure modes with RPN≥200 were deemed as high risk, meaning that they needed immediate corrective action. After modifications that were put, we compared the resulting RPN with the previous one. RESULTS: A total of 33 failure modes were identified. Many of the failure modes, including the one with the highest RPN (specimen hemolysis) appeared in the pre-analytic phase, whereas no high-risk failure modes (RPN≥200) were found during the analytic phase. High-priority risks were "sample hemolysis" (RPN, 336), "sample delivery delay" (RPN, 225), "sample volume error" (RPN, 210), "failure to release results in a timely manner" (RPN, 210), and "failure to identify or report critical results" (RPN, 200). The corrective measures that we took allowed a decrease in the RPN, especially for the high-priority risks. The maximum reduction was approximately 70%, as observed for the failure mode "sample hemolysis". CONCLUSIONS: FMEA can effectively reduce errors in clinical chemistry laboratories.
BACKGROUND: Timely delivery of correct results has long been considered as the goal of quality management in clinical laboratory. With increasing workload as well as complexities of laboratory testing and patient care, the traditional technical adopted like internal quality control (IQC) and external quality assessment (EQA) may not enough to cope with quality management problems for clinical laboratories. We applied failure mode and effects analysis (FMEA), a proactive tool, to reduce errors associated with the process beginning with sample collection and ending with a test report in a clinical chemistry laboratory. Our main objection was to investigate the feasibility of FMEA in a real-world situation, namely the working environment of hospital. METHODS: A team of 8 people (3 laboratory workers, 2 couriers, 2 nurses, and 1 physician) from different departments who were involved in the testing process were recruited and trained. Their main responsibility was to analyze and score all possible clinical chemistry laboratory failures based on three aspects: the severity of the outcome (S), the likeliness of occurrence (O), and the probability of being detected (D). These three parameters were multiplied to calculate risk priority numbers (RPNs), which were used to prioritize remedial measures. Failure modes with RPN≥200 were deemed as high risk, meaning that they needed immediate corrective action. After modifications that were put, we compared the resulting RPN with the previous one. RESULTS: A total of 33 failure modes were identified. Many of the failure modes, including the one with the highest RPN (specimen hemolysis) appeared in the pre-analytic phase, whereas no high-risk failure modes (RPN≥200) were found during the analytic phase. High-priority risks were "sample hemolysis" (RPN, 336), "sample delivery delay" (RPN, 225), "sample volume error" (RPN, 210), "failure to release results in a timely manner" (RPN, 210), and "failure to identify or report critical results" (RPN, 200). The corrective measures that we took allowed a decrease in the RPN, especially for the high-priority risks. The maximum reduction was approximately 70%, as observed for the failure mode "sample hemolysis". CONCLUSIONS: FMEA can effectively reduce errors in clinical chemistry laboratories.