复杂不确定环境下医疗故障模式及影响分析方法研究

Medical or clinical risk is exist throughout the entire healthcare process, from diagnosis to treatment to rehabilitation. Healthcare risk managemen has become one of the important issues increasingly concerned by modern hospital and managers. Failure mode and effects analysis (FMEA), as a prospective reliability analysis technique, shows some important weaknesses concerning the rationality of the approach when used in real situations, especially in healthcare risk management. First, the risk priority number (RPN) considers only three factors mainly in terms of safety; other important factors such as economic aspects are ignored. Second, there can be significant dependence and feedbacks between the different risk factors, but the conventional RPN method cannot capture these complex interrelationships. Third, the tradntional FMEA has not considered indirect relations between components and thus is deficient for systems with many subsystems or components. Fourth, the different types of assessment information provided by FMEA team are very difficult to incorporate into the FMEA by the conventional RPN method. These drawbacks make the use of the traditonal FMEA model for healthcare risk assessment far from perfect. To slove the problems mentioned above, in this project, we will first develop a healthcare risk factor conceptual framework which well fit the healthcare context in China through a systematic review of literature and a questionnaire survey to healthcare experts; then propose a systematic healthcare FMEA model based on multi-criteria decision making (MCDM) methods and uncertainty theories, which can be used to analyze the overall risk of healthcare failure modes under complex and uncertain environment. The purpose of this project is to minimize medical risks and optimize the configuration of health resources by identifying and eliminating potential healthcare failures from systems, equipments or processes in hospitals and provide more accurate and effective information for the medical risk management decision making.

医疗风险无处不在，而如何降低医疗风险提高医疗质量已成为当今医院管理所面临的一项重要而紧迫的研究课题。故障模式及影响分析(FMEA)，作为一种前瞻性的可靠性分析技术，在实际应用尤其在医疗风险评价中存在许多不足，主要表现在没有考虑医疗风险因子的特殊性、医疗风险因子的相互关系、医疗故障模式关系的复杂性和医疗故障模式评价的不确定性。本课题将根据FMEA技术应用到医疗风险分析这一特定情境，首先通过系统文献回顾和问卷调研的方法，建立适合医疗风险评价的风险因子层次框架模型；然后运用多准则决策技术和不确定理论，提出相应的医疗风险因子依赖性关系分析方法、研究医疗故障模式影响关系分析算法及系统风险排序模型、探讨医疗故障模式评价信息获取策略；最后，基于上述研究成果开发出医疗故障模式及影响分析原型系统，并选取医疗服务中高风险的过程、设备或系统进行实证检验，以期为医疗机构和医保部门风险管理和科学决策提供依据和参考。

如何降低医疗风险、提高医疗服务质量是当今医院管理者所面临的一项重要而紧迫的研究课题。本项目针对传统FMEA方法的不足与医疗风险的特点，开展了以下研究：(1) 通过研究医疗风险因子的多维性和层次性，建立了一种适合医疗风险评价的风险因子层次框架模型；(2) 通过研究医疗故障模式的复杂性和系统性，提出了一种医疗故障模式相互影响及风险分析方法；(3) 通过研究医疗评价信息的多样性和不确定性，提出了一种更加可靠、有效的故障评价信息获取策略；(4) 最后建立了医疗故障模式及影响分析框架模型及原型系统，并通过医院实际案例进行了实证检验，提出了相应的医疗风险管理建议与措施。本项目完成了预设的主要研究内容，取得了超过预期的研究成果。在IIE Transactions、IEEE Transactions等国际知名学术期刊上累计发表SCI/SSCI论文34篇，在国内重要期刊上发表论文8篇，出版英文专著1部。本项目的成果获得了国内外同行与业界的关注与积极评价，其中9篇论文入选ESI高被引论文，1篇论文获得2016年度 Emerald Literati Network 最佳论文奖。项目执行期间，培养硕士研究生 3名，主办4次学术会议，邀请10余名国内外学者来校合作交流，项目组成员出国合作交流3人次。此外，通过本项目的研究积累，项目负责人2017年破格晋升为教授、2015年入选首批上海高校青年东方学者、2017年入选上海市青年拔尖人才。