人工神经网络感知机模型判别医疗设备维修期内影响医疗服务满意要素的可行性  

The feasibility of artificial neural network perceptron model in discriminating the elements of influencing the satisfaction of medical service during the maintenance period of medical equipment

作　　者：李盈盈[1] 葛毅[1] 高莺 赵婧[1] 马玲 LI Ying-ying;GE Yi;GAO Ying(Department of Instrument and Equipment,Shanghai Changzheng Hospital,Shanghai 200003,China.)

机构地区：[1]上海长征医院仪器设备科,上海200003

出　　处：《中国医学装备》2020年第7期127-132,共6页China Medical Equipment

摘　　要：目的:探讨人工神经网络感知机模型判别医疗设备故障停机对医疗服务的影响。方法:参考世界卫生组织(WHO)对卫生系统绩效进行测评的反应性水平评估标准,以及人工神经网络的感知机模型和学习规划等资料,对人工神经网络感知机模型进行分析和研究,并对其进行模型构建和判别。通过正交实验设计,验证感知机模型判别医疗设备故障停机对医疗服务影响程度的分析,并通过社会类别、医疗类别和求医类3组训练输出值判别交通因子(Tr)、候诊因子(Td)和健康因子(H)是否给予关注。结果:患者在医疗设备停机时所受的影响程度可归结为最大关注和可以忽略;社会类别、医疗类别和求医类别3组训练输出值医疗服务满意度(y)均>学习期望值(d);设备停机时患者对交通因子(Tr)的影响可忽略,候诊因子(Td)不属最大关注,而患者对健康因子(H)的影响表示最大关注。结论:人工神经网络感知机模型判别结果可用于研究医疗设备维护期内影响医疗服务的满意度要素,验证感知机模型判别医疗设备故障停机对医疗服务影响程度的可行性,为大数据下智能化评价医疗服务满意度提供借鉴。Objective:To explore the effect of artificial neural network perceptron model in identifying downtime of medical equipment on medical service.Methods:Referring to the World Health Organization(who)response level evaluation standard for health system performance evaluation to implement measures,as well as the perceptron model and learning plan of artificial neural network,this paper analyzed and studied the perceptron model of artificial neural network,and built and distinguished this model.Through the orthogonal experimental design,the analysis of the influence degree that the perceptron model discriminated disorderly close-down of medical equipment was verified.And the training output values of three groups included social category,medical category and seeking medical category were used to discriminate whether the traffic factor(T_r),waiting factor(T_d)and health factor(H)should be concerned.Results:The influenced degrees of patients in downtime of medical equipment were attributed to the greatest concern and negligible.The satisfaction degrees of medical service(y)of social category,medical category and seeking medical category were larger than desired value of learning.When the equipment was stopped,the influence of patients on T_r could be ignored,and T_d was not belong to the most attention,while the influence of patients on H expressed the most attention.Conclusion:The discriminated results of artificial neural network perceptron model can be used to research the elements of satisfaction that affect medical service during the maintenance period of medical equipment,and verify the feasibility that perceptron model discriminated the influenced degree of medical equipment downtime on medical service,and provide reference for intelligent evaluating satisfaction of medical service under big data.

关 键 词：人工神经网络 感知机模型 医疗设备故障 医疗服务满意度 正交实验设计 

分 类 号：R197.39[医药卫生—卫生事业管理]