基于预测性模型的磁共振成像设备智能预防性维护方法构建及使用效果分析  

Analysis of intelligently preventive maintenance method and application effect of magnetic resonance imaging equipment based on a predictive model

作　　者：周鹏 刘琼[2] 邢文飞 张朝智 Zhou Peng;Liu Qiong;Xing Wenfei;Zhang Chaozhi(Department of Medical Engineering,Hainan Hospital of Chinese PLA General Hospital,Sanya 572013,China;Medical Support Center,Hainan Hospital of Chinese PLA General Hospital,Sanya 572013,China)

机构地区：[1]中国人民解放军总医院海南医院医学工程科,三亚572013 [2]中国人民解放军海南总医院医疗保障中心,三亚572013

出　　处：《中国医学装备》2024年第12期167-172,共6页China Medical Equipment

基　　金：海南省重大科技计划项目(ZDKJ2019012)。

摘　　要：目的:探讨基于预测性模型的磁共振成像设备智能预防性维护方法在医疗设备智能预防性维护中的效果。方法:设计磁共振成像设备智能预防性维护自回归积分移动平均(ARIMA)预测性模型,用于磁共振成像设备性能检测,从预防维护、故障维修和质量检测3个维度做好设备智能预防性维护。选取2022年至2023年解放军总医院海南医院在用的20台磁共振成像设备,将2022年1月至12月的设备维护采用常规维护方法,2023年1月至12月的设备维护采用基于预测性模型的磁共振成像设备智能预防性维护方法(预测性模型方法),对比两种维护方法的设备预防性维护质量评分、设备运行管理规范度和设备操作人员对设备服务质量的满意度评分。结果:采用预测性模型维护方法的设备维护有效率、维修及时性、质检合格率和维修规范度平均评分分别为(90.36±6.33)、(89.14±4.36)、(88.62±3.36)和(91.58±3.47)分,均高于常规维护方法,差异有统计学意义(t=10.876、11.360、12.283、12.226,P<0.05);采用预测性模型维护方法的设备平均开机率、运转率和配置率分别为(91.58±4.12)%、(90.69±5.14)%和(89.25±6.01)%,均高于常规维护方法,而故障发生频次为(1.02±0.25)次/年,低于常规维护方法,差异均有统计学意义(t=5.298、6.557、10.572、27.867,P<0.05);10名设备操作人员对采用预测性模型方法的设备预防维护、预防维修、故障维修、事后维护和质量勘测满意度平均评分分别为(90.54±2.36)、(91.59±3.14)、(92.54±4.69)、(91.89±3.25)和(92.54±2.45)分,均高于常规维护方法,差异有统计学意义(t=12.807、12.290、8.764、12.146、15.612,P<0.05)。结论:基于预测性模型的磁共振成像设备智能预防性维护方法能够提高设备维护质量和运行质量,相关操作人员对设备服务满意度较高,能够有效提高设备管理效果,确保设备稳定高效应用。Objective:To explore the effects of intelligently preventive maintenance of magnetic resonance imaging(MRI)equipment based on a predictive model in the intelligently preventive maintenance of medical equipment.Methods:An autoregressive integrated moving average(ARIMA)predictive model of intelligently preventive maintenance of MRI equipment was designed to perform detection for performance of MRI equipment,so as to do well for the intelligently preventive maintenance from three dimensions:preventive maintenance,fault repair and quality detection.A total of 20 MRI equipment in Hainan Hospital of Chinese PLA General Hospital from 2022 to 2023 were selected,and conventional maintenance method was adopted for equipment maintenance from January to December 2022,and intelligently preventive maintenance method(predictive model method)based on predictive model was adopted for MRI equipment based on predictive model for equipment maintenance from January to December 2023.The quality scores of preventive maintenance,the standardization level of operation and management of equipment and the satisfaction scores of operators for service quality of equipment were compared between the two maintenance methods.Results:The maintenance efficiency score,maintenance timeliness score,qualification rate of quality inspection and average score of maintenance regularity of the equipment of using maintenance method of predictive model were respectively(90.36±6.33)points,(89.14±4.36)points,(88.62±3.36)points and(91.58±3.47)points,all of which were significantly higher than those of conventional maintenance method,and the differences were statistically significant(t=10.876,11.360,12.283,12.226,P<0.05).The average operation rate,operational rate and allocation rate of equipment of using the maintenance method of predictive model were(91.58±4.12)%,(90.69±5.14)%,and(89.25±6.01)%,respectively,which were significantly higher than those of conventional maintenance method,while the fault frequency of the former was(1.02±0.25)times/year,whic

关 键 词：预测性模型 磁共振成像 预防性维护 效果分析 

分 类 号：R445.2[医药卫生—影像医学与核医学]