有源医疗设备维护维修中风险识别及预警体系研究  

Research of risk identification and early warning system in maintenance and repair of active medical devices

作　　者：郭军[1] 霍英恺 任建峰 高景明 Guo Jun;Huo Yingkai;Ren Jianfeng;Gao Jingming(Department of Equipment Maintenance,Second Hospital of Shanxi Medical University,Taiyuan 030001,China;Department of Medical Equipment Maintenance and Management,Shanxi Pharmaceutical Vocational College,Taiyuan 030031,China;Equipment Management and Maintenance Center,Shanxi Norman Bethune Hospital,Taiyuan 030001,China)

机构地区：[1]山西医科大学第二医院设备维修部,太原030001 [2]山西药科职业学院医疗器械维护与管理系,太原030031 [3]山西白求恩医院设备管理维护中心,太原030001

出　　处：《中国医学装备》2024年第12期161-166,共6页China Medical Equipment

摘　　要：目的:构建风险识别及预警模型,探讨其在有源医疗设备维护维修风险控制管理中的价值。方法:从基础数据、核心数据和辅助数据3方面建立有源医疗设备维护维修风险识别及预警知识库,结合设备运行状况设计风险评价指标体系,采用变异系数进行权重赋值和可拓云算法模型进行风险等级评定,形成分级预警触发路径和人员、制度、过程的三维预警干预方案。选取2022年至2023年山西医科大学第二医院临床在用的287台有源医疗设备,将2022年1月至12月期间使用的261台设备采用常规管理方法进行管理,2023年1月至12月期间使用的270台(含常规管理方法中在用的244台)有源医疗设备采用有源医疗设备维护维修风险识别及预警模型进行管理(简称风险识别模型管理)。从安全等级评定和风险隐患统计对比两种管理方法设备维护维修管理效果,并对参与设备管理的人员业务能力进行考核评价。结果:采用风险识别模型管理的有源医疗设备维护维修风险率为7.8%(21/270),低于常规管理方法,差异有统计学意义(χ^(2)=8.773,P<0.05);采用风险识别模型管理方法进行的2839次维护维修活动中,大型医疗设备、心电监护设备、生命支持急救设备和医学检验设备安全风险隐患分别发生75、19、82和11次,隐患率为2.6%、0.7%、2.9%和0.4%,均低于常规管理方法,差异有统计学意义(χ^(2)=27.989、24.580、46.654、12.604,P<0.05);参与风险识别模型管理的92名设备管理人员在维护管理(88名)、质量监测(91名)、故障处理(85名)和风险应对(90名)方面的考核合格率分别为95.7%、98.9%、92.4%和97.8%,均高于常规管理方法,差异有统计学意义(χ^(2)=4.901、4.016、6.368、5.176,P<0.05)。结论:基于变异系数赋权和可拓云算法模型的风险识别及预警模型,能够降低有源医疗设备维护维修风险水平,控制安全隐患发生概率,提高维护维修管理保障�Objective:To construct a risk identification and early warning management model,and to explore its value in the risk control and management of active medical devices maintenance and repair.Methods:The risk identification and early warning knowledge base of active medical equipment maintenance and repair was constructed from three aspects:basic data,core data and auxiliary data.The risk evaluation index system was designed in combination with the equipment operating status,and the weight was assigned by coefficient of variation and the extension cloud algorithm was used to evaluate the risk level,so as to form a hierarchical early warning trigger path and a threedimensional early warning intervention scheme of personnel,system and process.A total of 287 active medical devices in clinical use in the Second Hospital of Shanxi Medical University from 2022 to 2023 were selected,and 261 devices used in the period from January to December 2022 were managed by conventional management methods,270 active medical devices(including 244 in use under conventional management method)used from January to December 2023 were managed by active medical equipment maintenance and repair risk identification and early warning model(referred to as risk identification model management).The equipment maintenance and repair management effects of the two management methods were compared from the aspects of safety level assessment and risk hazard statistics,and business capability of personnel involved in equipment management were assessed and evaluated.Results:The risk rate of active medical equipment managed by risk identification model was 7.8%(21/270),which was lower than that of conventional management method,and the difference was statistically significant(χ^(2)=8.773,P<0.05).Among the 2839 maintenance and repair activities carried out by the risk identification model management method,safety risk hazards of large medical equipment,ECG monitoring equipment,life support emergency equipment and medical testing equipment occurred 75,19,82

关 键 词：维护维修 风险识别 预警干预 变异系数 可拓云 有源医疗器械 

分 类 号：R197.39[医药卫生—卫生事业管理]