National Central University, Jhongli, Taoyuan County Taiwan, Republic of China.
J Med Syst. 2012 Dec;36(6):3967-74. doi: 10.1007/s10916-012-9868-5. Epub 2012 Jul 8.
Failure mode and effects analysis (FMEA) can be employed to reduce medical errors by identifying the risk ranking of the health care failure modes and taking priority action for safety improvement. The purpose of this paper is to propose a novel approach of data analysis. The approach is to integrate FMEA and a mathematical tool-Data envelopment analysis (DEA) with "slack-based measure" (SBM), in the field of data analysis. The risk indexes (severity, occurrence, and detection) of FMEA are viewed as multiple inputs of DEA. The practicality and usefulness of the proposed approach is illustrated by one case of health care. Being a systematic approach for improving the service quality of health care, the approach can offer quantitative corrective information of risk indexes that thereafter reduce failure possibility. For safety improvement, these new targets of the risk indexes could be used for management by objectives. But FMEA cannot provide quantitative corrective information of risk indexes. The novel approach can surely overcome this chief shortcoming of FMEA. After combining DEA SBM model with FMEA, the two goals-increase of patient safety, medical cost reduction-can be together achieved.
失效模式与影响分析(FMEA)可以通过识别医疗保健失效模式的风险排名,并采取优先行动来提高安全性,从而减少医疗错误。本文旨在提出一种新的数据分析方法。该方法是将 FMEA 和一种数学工具——基于松弛的衡量(SBM)的数据包络分析(DEA)整合在一起,应用于数据分析领域。FMEA 的风险指标(严重度、发生度和检出度)被视为 DEA 的多个输入。通过医疗保健的一个实例说明了该方法的实用性和有效性。作为提高医疗服务质量的系统方法,该方法可以提供风险指标的定量纠正信息,从而降低失效的可能性。为了提高安全性,可以将这些新的风险指标目标用于目标管理。但是,FMEA 无法提供风险指标的定量纠正信息。新方法肯定可以克服 FMEA 的这一主要缺点。将 DEA SBM 模型与 FMEA 相结合后,可以同时实现增加患者安全性和降低医疗成本的两个目标。