摘要
目的:探讨多维数据离群点检测算法在医疗设备管理能力评估中的应用价值。方法:依据医疗设备管理评估模式的不同,将2015年7月至2017年6月的医疗设备管理能力评估数据纳入对照组,采用传统的管理事项评估模式;将2017年7月至2019年6月的评估数据纳入观察组,采用多维的管理能力评估模式,从专业知识、专业技能及职业素养3个层面建立医疗设备管理能力模型,通过x2量的多元离群点检测算法对管理能力评估的结果用于指导科室绩效分配、学习培训和设备管理方案进行修订。对比分析两组医疗设备评估数据中管理能力和管理效果。结果:观察组的专业知识考核成绩和临床满意度高于对照组,工作差错率低于对照组,两组比较差异有统计学意义(t=2.526,t=2.820,t=2.596;P<0.05);观察组的设备开机率和故障自修率高于对照组,管理费用增幅低于对照组,两组比较差异有统计学意义(t=2.335,t=2.211,t=2.107;P<0.05)。结论:多维数据离群点检测算法在医疗设备管理能力评估中具有重要的应用价值,可有效提升医学工程技术人员的管理能力和管理水平。
Objective:To discuss the application value of multivariate outlier detection method in the assessment of management ability for medical equipment.Methods:According to the differences of management assessment mode of medical equipment,the assessment data of management ability of medical equipment from July 2015 to June 2017 were divided into control group which adopted traditional assessment mode for management items,and that from July 2017 to June 2019 were divided into observation group which adopted multi-dimensional assessment mode for management ability.The model of management ability for medical equipment was established from three aspects included professional knowledge,professional skills and professional accomplishment.The results from the assessment of management ability by multi-dimensional outlier detection method with x2 statistic were used to guide the performance distribution of department,the learning and training,and the revising of the management plan of equipment.And then the management ability and management effect of assessment data of medical equipment of two groups were further compared and analyzed.Results:The examination achievement of professional knowledge and clinical satisfaction of observation group were significantly higher than those of control group,and the error rate of work of observation group was significantly lower than that of control group(t=2.526,t=2.820,t=2.596,P<0.05).And the operating rate of equipment and the self-repair rate of failure of observation group were significantly higher than those of control group,and the increase range of management cost of observation group was significantly lower than that of control group(t=2.335,t=2.211,t=2.107,P<0.05).Conclusions:The multi-dimensional data outlier detection method has important application value in the assessment of management ability for medical equipment,and it can effectively improve the management ability and management level of technicians of medical engineering.
作者
王子洪
郭宇峰
郭熙
韩锦川
WANG Zi-hong;GUO Yu-feng;GUO Xi(Medical Engineering Department,The First Hospital Affiliated to Army Medical University,Chongqing 400038,China;不详)
出处
《中国医学装备》
2020年第5期35-38,共4页
China Medical Equipment
基金
重庆市技术创新与应用示范(社会民生类)一般项目(cstc2018jscx-msybX0070)“公立医院医疗设备全生命周期管理系统的研究”。
关键词
医疗设备管理
专业知识
专业技能
职业素养
离群点
管理能力
The management of medical equipment
Professional knowledge
Professional skill
Professional accomplishment
Outlier
Management ability
