为了深入研究我国慢性病医防融合领域的发展趋势和演化过程,本文收集了2006~2024年的373篇相关文献,经过数据清洗和预处理后,引入Word2vec的LDA模型进行文献的主题挖掘,确定每个时期的最佳主题数量,并生成主题演化桑基图。计算不同时间段内各主题强度,并通过交互式条形图描述热点主题。结果显示,在第一阶段2006~2020年,大部分研究主要集中在如何整合医疗服务,以及如何将慢性病防控与医防结合;在第二阶段2021~2022年,除了延续既有的主题,部分研究焦点转移到如何更好地管理和融合综合医疗服务,以及如何将公共卫生服务与医疗体系更有效地结合;在第三阶段2023~2024年,研究重点在于如何实现健康服务与医防的深度融合,以及如何在医疗服务中具体落实医防融合的理念,研究更加注重实际操作和具体应用。通过主题演化分析揭示了不同时期内主题之间的关联和演化过程,综合医疗服务、慢性病防控与医防结合等主题在不同阶段都有较强的延续性,而研究重点随着时间的推移逐渐从综合医疗服务向医防融合和健康服务管理方向转移。研究发现,一些主题在不同时期内保持较高的强度,从本研究主题强度图可以看出,在慢性病医防融合领域,社区基层医疗机构在医防融合中具有重要作用,此外2021年及以后的阶段中公共卫生体系建设及医防融合成为研究的共识热点。该研究有助于更全面地理解慢性病医防融合领域的研究动态,为未来的研究方向和政策制定提供有益的参考,同时也为文本分析方法的应用提供了实践示范。未来的研究可以进一步挖掘基层医疗与医防协同机制以及健康服务管理与慢性病防控方面的潜力,更好地帮助社区基层医疗机构服务提供者应对来自人口老龄化社会慢性病高发以及多样化健康需求的挑战,同时也要关注对应的新兴技术如人工智能和大数据分析和对应的数据隐私和伦理挑战,以及政策实施中的风险。In this paper, in order to deeply study the development trend and evolution process in the field of chronic disease medical preventive integration in China, 373 relevant literatures from 2006~2024 were collected, and after data cleaning and pre-processing, the LDA model of Word2vec was introduced in the theme mining of the literature to determine the optimal number of themes in each period and generate the theme evolution Sankey diagram. The intensity of each topic in different time periods is calculated and hot topics are described by interactive bar charts. The results show that in the first period of 2006~2020, most of the studies focused on how to integrate healthcare services and how to combine chronic disease prevention and control with medical prevention;in the second period of 2021~2022, in addition to the continuation of the existing themes, some of the studies shifted their focus to how to better manage and integrate integrated healthcare services and how to combine public health services with the healthcare system more effectively;in the third stage, 2023~2024, the research focused on how to realize the deep integration of health services and medical preventive, and how to implement the concept of med
本文以我国基层医疗机构开展慢性病医防融合为研究对象,运用LDA (Latent Dirichlet Allocation)主题模型和社会网络分析对基层医疗机构慢性病医防融合的聚焦主题和探索路径进行研究,以期为基层医防融合实践提供更具价值的参考和政策建议。运用Python软件和Gephi软件分别绘制关键词云图、共线网络图、主题聚类图,旨在挖掘目前基层社区慢性病医防融合关注的主要内容,归纳出基层医疗与慢性病防控、社区服务与公共卫生、管理与政策支持三个主题名称,提出了加强基层医疗机构的服务能力建设、创新基层医疗机构开展慢性病医防融合的服务模式、完善医防融合政策支持、加强信息化互联互通建设的政策建议,以期为未来基层医疗机构推进慢性病医防融合实践提供参考借鉴。Taking the integration of chronic disease medicine and prevention in China’s primary healthcare institutions as the research object, this paper used the LDA (Latent Dirichlet Allocation) thematic model and social network analysis to study the focusing themes and exploratory paths of chronic disease medicine and prevention integration in primary healthcare institutions, with a view to providing more valuable references and policy suggestions for the practice of primary medicine and prevention integration. It used Python software and Gephi software to draw keyword cloud map, co-linear network map, and theme clustering map respectively, aiming to dig out the main contents of the current focus on chronic disease medicine and prevention integration in primary communities and summarize the names of three themes: primary healthcare and chronic disease prevention and control, community service and public health, and management and policy support, and put forward proposals to strengthen the service capacity building of primary healthcare institutions, innovate the service mode of primary healthcare institutions to carry out the integration of chronic diseases medicine and prevention, improve the policy support for the integration of medicine and prevention, and strengthen the construction of information technology interconnection, with a view to providing a reference for the future practice of promoting the integration of medicine and prevention of chronic diseases in primary healthcare institutions.
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