摘要
目的:探究在线医疗用户择医行为的研究热点及演化脉络,为推动在线医疗用户择医行为研究的发展提供理论指导。方法:基于中国知网2016-2023年以“在线择医”“在线问诊”为主题的文献,运用CiteSpace软件,就在线医疗用户择医行为研究进展、共现网络和关键词进行知识图谱分析。结果:在线医疗用户择医行为相关研究总体呈现上升趋势;高校管理学院是在线医疗用户择医行为研究的主要力量,但尚未形成稳定的核心作者群,相关合作研究尚局限在机构内部;高频关键词有“患者选择”“医生推荐”等。结论:需加强跨学科研究,加强学者及机构间合作,还需根据政策变化拓展在线医疗用户择医行为研究前沿;患者应考量海量信息,做出理性决策;医生应提升综合素质,提供高质量服务;在线医疗平台应优化系统设计,提升用户体验。
Objective:To explore the research hotspots and evolutionary trends in online medical users'physician selection behavior,providing theoretical guidance for advancing research in this area.Methods:Based on literature from CNKI(China National Knowledge Infrastructure)from 2016 to 2023 with themes of"online physician selection"and"online consultation,"CiteSpace software was used to conduct knowledge map analysis on the research progress,co-occurrence networks,and keywords related to online medical users'physician selection behavior.Results:The research on online medical users'physician selection behavior shows an overall upward trend;management schools in universities are the main contributors to this research,but a stable core group of authors has not yet formed,and related cooperative research is still limited to within institutions.High-frequency keywords include"patient choice,""doctor recommendation,"etc.Conclusion:It is necessary to strengthen interdisciplinary research,enhance cooperation among scholars and institutions,and expand the frontiers of online medical users'physician selection behavior research according to policy changes.Patients should consider vast information and make rational decisions;doctors should improve their overall competence and provide high-quality services;online medical platforms should optimize system design to enhance user experience.
作者
张利江
刘文璐
任文杰
ZHANG Lijiang;LIU Wenlu;REN Wenjie(School of Health Management,Xinxiang Medical University,Xinxiang,He'nan Province,453000,PRC)
出处
《中国医院》
北大核心
2024年第9期28-31,共4页
Chinese Hospitals
基金
国家社会科学基金一般项目(21BTQ063)
河南省哲学社会科学规划年度项目(2020BZH004)。
关键词
在线医疗
择医行为
CITESPACE
患者选择
可视化分析
online medical care
physician selection behavior
CiteSpace
patient choice
visualization analysis