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基于安全智能预警系统的血液内科层流室设备管理研究

Research on equipment management of laminar flow room in hematology department based on safety intelligent warning system
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摘要 目的:构建安全智能预警系统,探讨其在血液内科层流室医疗设备管理中的应用效果。方法:采用浏览器与服务器(B/S)模式构建安全智能预警系统,系统由客户机层、应用服务器层和数据库服务器层3层架构以及数据采集、数据传输、数据处理和数据应用4个核心模块组成。选取2021年11月至2023年10月空军军医大学唐都医院血液内科层流室在用的45台常用设备,将2021年11月至2022年10月设备使用期间实施常规管理,2022年11月至2023年10月设备使用期间应用安全智能预警系统管理(简称智能管理),对比两种管理方法设备安全风险评估指数、随机抽检的设备安全风险隐患率和600次检查(每种方法300次)的设备使用平均正确率。结果:采用智能管理方法的45台设备安全风险评估为差、一般、良好和好的平均风险指数分别为0.02±0.01、0.06±0.02、0.18±0.04和0.39±0.07,评估为差、一般和良好的平均风险指数均低于常规管理方法,评估为好的安全风险指数高于常规管理方法,差异有统计学意义(t=19.092、12.457、6.751、15.809,P<0.05);采用智能管理方法随机抽检45台设备的137例事项中机械损伤、交叉感染和电击伤害分别发生4、5和1例,发生率分别为2.92%、3.65%、0.73%,低于常规管理方法,差异有统计学意义(x2=9.336、16.286、17.328,P<0.05);采用智能管理方法的45台设备摆放正确、设备连接顺序正确、设备参数设置正确和设备整理规范使用平均正确率(%)分别为(99.52±3.51)%、(98.63±4.05)%、(99.74±4.18)%和(97.37±5.36)%,均高于常规管理方法,差异有统计学意义(Z=12.231、9.075、13.584、8.933,P<0.05)。结论:采用安全智能预警系统对血液内科层流室设备进行管理,能够有效预防设备安全风险隐患,提高设备使用正确率。 Objective:To construct a safety intelligent early warning system,and to explore its application effect in the management of medical equipment in laminar flow room of hematology department.Methods:The safety intelligent early warning system was constructed by using the browser and server(B/S)mode.The system was consisted of three layers:client layer,application server layer and database server layer,as well as four core modules:data acquisition,data transmission,data processing and data application.A total of 45 equipment in clinical use in the laminar flow room of the Department of Hematology,Tangdu Hospital,Air Force Medical University from November 2021 to October 2023 were selected.Routine management was implemented during the use period of the equipment from November 2021 to October 2022,and the safety intelligent early warning system management(hereinafter referred to as the intelligent management)was applied during the equipment use period from November 2022 to October 2023.The equipment safety risk evaluation index,the potential safety risk rate of the equipment sampled randomly and the average accuracy rate of the equipment use in 600 checks(300 times for each method)under the two management methods were compared.Results:The safety risk assessments of 45 equipment adopted the intelligent management method were poor,fair,good,and excellent with risk indices of 0.02±0.01,0.06±0.02,0.18±0.04 and 0.39±0.07,respectively,the poor,fair,and good risk indices were lower than those of routine management method,and the safety risk index assessed as excellent was higher than that of routine management method,the difference was statistically significant(t=19.092,12.457,6.751,15.809,P<0.05).Among the 137 cases of 45 equipment randomly sampled using intelligent management method,4,5 and 1 cases of mechanical injury,cross-infection and electric shock injury occurred,with the incidence rates of 2.92%,3.65%and 0.73%,respectively,which were lower than those of routine management methods,the difference was statistically significant(x2=9.336,16.286,17.328,P<0.05).The average accuracy rates(%)of the 45 equipment adopted the intelligent management method in terms of correct placement,correct connection sequence,correct parameter setting and organization and standard use of the equipment were 99.52±3.51,98.63±4.05,99.74±4.18 and 97.37±5.36,respectively,which were higher than those of the routine management method,the difference was statistically significant(Z=12.231,9.075,13.584,8.933,P<0.05).Conclusion:The application of safety intelligent warning system for the equipment management of laminar flow room in the department of hematology can effectively prevent potential safety risks of the equipment and improve the accuracy of equipment use.
作者 刘丹 凤丽娜 李帆 张爱华 Liu Dan;Feng Lina;Li Fan;Zhang Aihua(Department of Hematology,Tangdu Hospital,Air Force Medical University,Xi'an 713700,China)
出处 《中国医学装备》 2024年第11期132-136,共5页 China Medical Equipment
关键词 安全智能预警系统 血液内科层流室 医疗设备 安全风险 Safety intelligent early warning system Laminar flow room of hematology department Medical equipment Safety risk
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