理论研究

“治理—需求—工具—主题”四维框架下我国互联网医疗政策文本量化研究

  • 张云秋 ,
  • 刘帅兵
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  • 吉林大学公共卫生学院 长春 130012
张云秋,教授,博士生导师,确定论文选题与论文修改,E-mail:yunqiu@jlu.edu.cn;刘帅兵,博士研究生,设计论文选题、文献调研与数据分析、论文撰写

收稿日期: 2023-12-06

  修回日期: 2024-02-25

  网络出版日期: 2024-10-08

Quantitative Research on the China’s Internet Medical Policy Texts Under the Four-dimensional Framework of “Governance-Demand-Tools-Theme”

  • Zhang Yunqiu ,
  • Liu Shuaibing
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  • School of Public Health, Jilin University, Changchun 130012

Received date: 2023-12-06

  Revised date: 2024-02-25

  Online published: 2024-10-08

摘要

[目的/意义] 分析我国互联网医疗政策的内容结构,为后续政策体系的完善和优化提供理论依据。[方法/过程] 以我国互联网医疗领域的中央政策文本为研究对象,结合协同治理理论、患者需求层次模型、政策工具理论及KeyBERT模型,构建协同治理—需求层次—政策工具—政策主题四维政策分析框架,分析政策内容结构与演变,识别政策重点与取向。[结果/结论] 互联网医疗政策呈现主体协同中心化、需求满足基础化、政策工具结构失衡化及主题覆盖全面化。未来应推动政策执行主体协同治理结构功能整合、满足政策客体更高层次的需求、优化政策工具内部组成结构、推动政策覆盖主题深化细化。

本文引用格式

张云秋 , 刘帅兵 . “治理—需求—工具—主题”四维框架下我国互联网医疗政策文本量化研究[J]. 图书情报工作, 2024 , 68(18) : 71 -86 . DOI: 10.13266/j.issn.0252-3116.2024.18.008

Abstract

[Objective/Significance] The analysis of China’s internet healthcare policy’s content structure aims to provide a theoretical basis for the improvement and optimization of the follow-up policy system. [Method/Process] This article took China’s central policy text in the field of Internet health care as the research object. By combining collaborative governance theory, patient demand hierarchy model, policy tool theory and KeyBERT model, the four-dimensional policy feature analysis framework of collaborative governance, demand hierarchy, policy tool, - policy theme was constructed. The framework was then employed to analyze the structure and evolution of policy content, and identify the policy focus and orientation. [Result/Conclusion] The internet medical policy presents a centralized coordination structure, a focus on meeting basic demand, an imbalance in its policy tool structure and comprehensive coverage of themes. In the future, it is necessary to promote the functional integration of policy implementation bodies’ collaborative governance structure, meet the higher-level needs of policy objects, optimize the internal composition structure of policy tools, and promote the deepening and elaboration of policy coverage topics.

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