医院微信公众平台服务发展现状及建设对策研究
2019-07-26
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doi:10.3969/j.issn. 1672-5166.2019.03.010

 

医院微信公众平台服务发展现状及建设对策研究

雷健波②△


目的 了解医院微信公众平台建设和使用情况,以及公众对医院微信公众平台的需求。方法 以排行榜中前100强医院为研究对象,利用对比分析法,对医院微信公众平台的功能开展比较研究;采用现场问卷调查和网络问卷调查两种方式,分析公众的需求和满足现状。结果 95%的被调查医院开通了微信公众号,从划分的6大功能模块来看,每个模块中所占比例最高的功能分别是医院介绍(占79.1%)、查报告单(占63.7%)、预约挂号(占75.8%)、问卷调查(占14.3%)、医院导航(占41.8%)、健康知识(占36.3%)。结论 医院微信公众平台虽然开通率较高,但使用人群比例并不高,平台服务功能设置大同小异,仅少部分医院提供一些特色功能,尚不能满足用户的需求。医院开通微信公众平台是大势所趋,需加强在线服务功能,提供个性化医疗服务。

关键词 社交媒体 微信公众平台 医疗服务 预约挂号

 

Research on the Construction and Application Status of Hospital WeChat Public Platform for Health

Services

LI Jin, LEI Jianbo

School of Medical Information and Engineering, Southwest Medical University, Luzhou 646000, Sichuan,China

 

Abstract Objective To understand the construction and use of hospital WeChat public platform,as well as the public demands for the hospital WeChat public platform. Method Taking the top 100 hospitals as the research object; comparative analysis method was used to conduct a study on the functions of the hospital WeChat public platform; on-site questionnaire survey and online questionnaire survey were used to analyze the demand and current satisfaction of public. Results 95% of the surveyed hospitals opened the WeChat public account. The functions with the highest proportion are hospital introduction (79.1%), appointment registration (75.8%), report query (63.7), hospital navigation (41.8%), health knowledge (36.3%) and questionnaire investigation (14.3%). Conclusions Although the opening rate of the hospital WeChat public platform is high, the proportion of the users is not y high. The service functions of WeChat public platforms are much the same, and only a few hospitals had some characteristic functions, which cannot meet the needs of the users. It’s a trend for hospitals to apply the WeChat public platform. The hospitals need to strengthen the construction of the online service functions and provide personalized medical services.

Keywords social media; WeChat public platform; medical service; appointment registration

 

基金项目: 国家自然科学基金面上项目基于深度学习和迁移学习的非结构化临床文本挖掘的方法探索(项目编号:81771937

西南医科大学医学信息与工程学院,四川省泸州市,646000

北京大学医学信息学中心,北京市,100191

作者简介:李瑾(1984—),女,硕士,讲师;研究方向:生物信息学,智能计算与复杂网络;E-maileddyblue@swmu.edu.cn

通信作者: 雷健波(1970—),男,博士;研究方向:可穿戴设备,医学信息学;E-mailjianbolei@qq.com

通信作者