基于BP神经网络的医疗卫生服务质量满意度研究  

Evaluation of satisfaction with medical and health services using BP neural network

作　　者：果爽 程伟 刘鑫鑫 刘洪雷[1] 邓彤[1] GUO Shuang;CHENG Wei;LIU Xinxin;LIU Honglei;DENG Tong(Beijing Jishuitan Hospital,Beijing 100035,China)

机构地区：[1]北京积水潭医院,北京100035

出　　处：《中国医学物理学杂志》2023年第6期788-792,共5页Chinese Journal of Medical Physics

基　　金：北京市科委科技新星交叉合作项目(20220484166)。

摘　　要：目的:应用BP神经网络及其他机器学习算法对医疗卫生服务质量满意度进行综合评价,分析患者对医疗卫生服务质量的满意度及其影响因素,为提升医疗机构卫生服务质量提供参考。方法:在北京市所辖33家医疗卫生服务机构中按照一定比例对年满16周岁的患者进行满意度问卷调查,探究患者对医疗卫生服务的医疗安全性、患者体验、医疗服务跟进效果以及医疗服务及时性的满意状况。结果:在患者满意度的预测中,BP神经网络在准确率、召回率和调和平均数3个指标均优于传统的机器学习算法;在患者满意度的决策中,满意度重要性系数依次为医疗服务及时性(1.0214)、患者体验(0.9239)、医疗安全性(0.8981)、医疗服务跟进效果(0.1798)。结论:医疗服务及时性、患者体验以及医疗安全性是医疗卫生服务质量满意度的重要影响因素,医疗卫生服务机构应进一步加强以上3个方面的培训建设。Objective To comprehensively evaluate the patient satisfaction with medical and health services using BP neural network and other machine learning algorithms,and analyze the factors affecting patient satisfaction,thereby providing reference for improving the quality of health services in medical institutions.Methods A questionnaire survey was conducted on patients over the age of 16 admitted to 33 medical and health service institutions in Beijing to explore patient satisfaction with nursing safety,patient experience,nursing follow-up and nursing-timeliness.Results In the prediction of patient satisfaction,the accuracy,recall rate and harmonic average of BP neural network were all higher than those of the traditional machine learning algorithms.The importance coefficient of satisfaction in the decision on patient satisfaction was as follow:nursing-timeliness(1.0214),patient experience(0.9239),nursing safety(0.8981)and nursing follow-up(0.1798).Conclusion Nursing-timeliness,patient experience and nursing safety are the important factors affecting the satisfaction with medical and health services.Medical and health service institutions should further strengthen the training in the above 3 aspects.

关 键 词：医疗卫生服务 满意度 BP神经网络 比较研究 

分 类 号：R195[医药卫生—卫生统计学]