Trends of Chronic Disease Management Research (1992–2022): A Scientometric Review

Abstract

Abstract Background: ​Chronic disease management (CDM) is a scientific management model that aims to improve the health level of patients, delay the deterioration of diseases and reduce the medical costs. Its research has grown rapidly in the past 30 years, covering multiple aspects such as graded management, risk management, management models and intervention subjects of chronic diseases. Although several scholars have conducted literature reviews and analyses on these aspects, there are still some key issues that have not been fully answered, such as the publication subjects, pioneering and landmark literature, mainstream and future research topics of CDM research. Therefore, it is necessary to conduct a systematic review. Methods: ​This paper selected 6 core databases of WoS (SCI-Expanded, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI) as the data source. The time span was set from January 1, 1992 to August 2, 2022, and the search mode was: TS = (“chronic disease management*” OR “chronic illness management*” OR “chronic condition management*”), with the retrieval date being August 2, 2022. Then the document type was refined by selecting “Article” and “Review” and the document language by selecting “English”. Finally, the 2986 studies were comprehensively evaluated and incorporated into Cite Space for review and analysis. Results: ​The results show that authors and institutions in United States are the main contributors to CDM research and that interdisciplinary collaboration is gradually growing. Using document co-citation analysis, research hotspots in the field were investigated. Furthermore, the research frontiers and trendy topics in CDM from 1922 to 2022 were found by using burst detection, and research gaps were identified. Conclusions: ​The findings provide valuable insights for both researchers and practitioners involved in CDM. But there are also some limitations, including (1) data sources can be enriched (2) search terms can be more flexible (3) scientometric sources selection can be more diverse, etc.