The disease spectrum of Chinese residents is undergoing fundamental changes. Chronic diseases have become the most important public health problem.

To reveal the evolution logic of hot topics in the field of chronic disease management, the research hotspots and evolution paths of chronic disease management were visually analyzed. A prediction model based on trend degree is generated to reveal the future development direction of hot topics in the field of chronic disease management.

The literature search time was as of April 30, 2023. The type was limited to academic journals, and non-research literatures such as academic papers, meeting minutes, news reports, and expert consensus were excluded. Relevant literatures are retrieved in China National Knowledge Infrastructure (CNKI), VIP Chinese Science and Technology Journal Full-text Database, and Wanfang Data Knowledge Service Platform. In order to ensure the quality of the included literature, the journal types were limited to Peking University Core, China Science Citation Database (CSCD) and Chinese Social Sciences Citation Index (CSSCI). Based on text mining technology and bibliometric methods, this paper used VOSviewer software to draw a co-word timeline network map, and deeply analyzes the structural relationship and evolution characteristics of research hotspots in chronic disease management. Based on cluster analysis and strategic coordinate analysis, the research status and development trend of its clustering theme were revealed. The topic trend degree index was constructed by weighting and superimposing the characteristic indexes including topic novelty and intensity indexes. The three exponential smoothing way was used to predict and analyze the time series of topic trend degree.

At the initial stage, the research focus in the field of chronic disease management was policy-oriented and fragmented, and gradually developed towards a diversified trend, forming a multi-center network structure with core nodes, such as "diabetes" "hypertension" "community" "management mode" "hierarchical diagnosis and treatment" "medical consortium" "Internet medicine", and "sports medicine integration".

The related literature in the field of chronic disease management showed an exponential growth trend. It has become a key research topic in academia. Multiple chronic disease management, chronic disease management of specific groups, psychological status of patients with chronic diseases, intelligent medical care, chronic disease management of traditional Chinese medicine, and big health management are emerging hot topics in the field of chronic disease management at this stage. Grassroots chronic disease management is a marginal research content, and the research results are not yet mature. In the future, we should focus on the research on the health management model of chronic disease comorbidity, continue to explore the deep integration mechanism of big data, cloud computing, Internet of things and wearable devices with chronic disease management, innovate the new model of chronic disease management based on the integration of medical treatment and prevention, and create a new health management plan for the whole population and the whole life cycle.

我国居民疾病谱系正发生根本性改变，慢性病已成为影响人群健康最重要的公共卫生问题。

对我国慢性病管理研究热点及其演变路径进行可视化分析，生成基于趋势度的预测模型，揭示慢性病管理领域热点议题的演变逻辑及其未来发展方向。

文献检索时间截至2023-04-30，限定类型为学术期刊，排除学术论文以及会议纪要、新闻报道、专家共识等非研究型文献，在中国知网、维普中文科技期刊全文数据库、万方数据知识服务平台检索相关文献，为保证纳入文献质量，期刊类型限定为北大核心、中国科学引文数据库（CSCD）和中文社会科学引文索引（CSSCI）。基于文本挖掘技术和文献计量学方法，运用VOSviewer软件绘制共词时间线网络图谱，深入剖析慢性病管理研究热点间的结构关系及其演变特征；基于聚类分析和战略坐标分析揭示其聚类主题的研究现状与发展趋势；将主题新颖性、强度等特征指标赋权叠加构建主题趋势度指标，并运用三次指数平滑对主题趋势度时间序列进行预测分析。

慢性病管理领域的研究焦点初期以政策为导向，呈碎片化特征，逐步朝着多元化趋势发展，形成"糖尿病""高血压""社区""管理模式""分级诊疗""医联体""互联网医疗""体医融合"等核心节点相互连接的多中心网络结构。

慢性病管理领域相关文献呈指数型增长态势，已成为学术界重点研究议题。多重慢性病管理、特定群体慢性病管理、慢性病患者心理状况、智慧医疗、中医慢性病管理、大健康管理是现阶段慢性病管理领域的新兴热点议题，基层慢性病管理属于边缘型研究内容，研究成果尚不成熟。未来应着重关注慢性病共病的健康管理模式研究，继续挖掘大数据、云计算、物联网及可穿戴设备与慢性病管理的深度融合机制，创新医防融合慢性病管理新模式，打造全人群与全生命周期的健康管理新方案。