基于数据挖掘技术的差异性医疗设备维修后管理及对照性研究  

Post-Maintenance Management and Comparative Study of Differential Medical Equipment Based on Data Mining Technology

作　　者：孙润祥 金涛[1] Sun Runxiang;Jin Tao(Department of Clinical Medical Engineering,The First People's Hospital of Lianyungang,Lianyungang Jiangsu)

机构地区：[1]连云港市第一人民医院临床医学工程部,江苏连云港222000

出　　处：《医疗装备》2022年第5期8-12,16,共6页Medical Equipment

摘　　要：目的通过数据挖掘技术对既往医疗设备临床使用、管理及维修故障数据进行分析,提出一种基于数据挖掘技术中常用的关联规则在差异性医疗设备维修后的管理方法。方法选取2017年1月至2019年12月连云港市第一人民医院在用的《医疗器械分类目录》可查的254台医疗设备(包含放射类设备、呼吸麻醉类设备、血液透析类设备、超声类设备、生化检验类设备及手术设备)为研究对象,随机将其分为观察组和对照组,各127台,对照组采用传统专家论证方法进行维修后管理,观察组采用基于数据挖掘技术的关联规则分析方法进行维修后管理,比较两组的管理效果。结果各类医疗设备主要故障源的差异性较大,差异有统计学意义(P<0.01);在设备启用6年后,与对照组比较,观察组设备故障率和维修费用显著降低,差异有统计学意义(P<0.05);观察组放射类设备、呼吸麻醉类设备、血液透析类设备、超声类设备、手术设备的故障率均低于对照组,差异有统计学意义(P<0.05)。结论数据挖掘技术可将医疗设备故障诱因与设备故障进行关联,对设备可能存在的故障起到较好的预警作用,使责任工程师按需对目标设备进行预防性维护和质量控制,具有一定的研究意义。Objective Through analyzing the past data of clinical use,management and failure maintenance of medical equipment by data mining technology,a post-maintenance management method of medical equipment based on the commonly used association rules in data mining technology was proposed.Methods 254 sets of radiation equipment,respiratory anesthesia equipment,hemodialysis equipment,ultrasonic equipment,biochemical testing equipment and surgical equipment used in The First People’s Hospital of Lianyungang from January 2017 to December 2019 and listed in the Classification Catalogue of Medical Equipment were selected as the research objects.They were randomly divided into an observation group and a control group,with 127 sets in each.The control group was managed by traditional expert argumentation method after maintenance.The observation group was managed by association rules analysis method based on data mining technology after maintenance.The management effects of the two groups were compared.Results The main fault sources of all kinds of medical equipment were significantly different,with statistically significant differences(P<0.01).After used for 6 years,the equipment failure rate and maintenance cost of the observation group were significantly reduced,and the differences were statistically significant compared with the control group(P<0.05).The failure rates of radiation equipment,respiratory anesthesia equipment,hemodialysis equipment,ultrasonic equipment,and surgical equipment in the observation group were all lower than those in the control group,and the differences were statistically significant(P<0.05).Conclusion Data mining technology can correlate medical equipment fault causes with equipment fault,so it has a certain early warning effect on the possible faults of the equipment and can make responsible engineers carry out preventive maintenance and quality control for objective equipment according to demands,indicating a certain research significance.

关 键 词：数据挖掘技术 关联规则 对照性研究 专家论证法 故障源 

分 类 号：R197.39[医药卫生—卫生事业管理]