Digital Health and AI for Chronic Disease Control and Management

A special issue of Healthcare (ISSN 2227-9032).

Deadline for manuscript submissions: 30 June 2026 | Viewed by 738

Special Issue Editor

Special Issue Information

Dear Colleagues,

This Special Issue aims to explore the transformative role of digital health technologies and artificial intelligence (AI) in the control and management of chronic diseases. With the rising prevalence of conditions such as diabetes, cardiovascular diseases, and respiratory disorders, innovative solutions are essential for enhancing patient outcomes and optimizing healthcare delivery. We invite contributions that examine the integration of digital health tools—including mobile health applications, wearable devices, telemedicine, and AI-driven analytics—into chronic disease management strategies.

The objectives of this Special Issue are to highlight cutting-edge research, case studies, and practical applications that demonstrate how digital health and AI can facilitate early detection, personalized treatment plans, and improved patient engagement. We also seek to address the challenges and ethical considerations associated with implementing these technologies in diverse healthcare settings. By bringing together a multidisciplinary perspective, this Special Issue aims to inform healthcare professionals, policymakers, and researchers about the potential of digital health and AI to revolutionize chronic disease management and ultimately improve population health outcomes.

Dr. Weike Zhang
Guest Editor

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Keywords

  • digital health
  • artificial intelligence (AI)
  • chronic disease
  • healthcare delivery
  • health economics

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Published Papers (1 paper)

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Research

20 pages, 683 KB  
Article
The Digital Amplifier in Medical Insurance: How Chinese Provincial Pooling Policy Optimizes Chronic Disease Management
by Ming Zeng, Huan Cheng and Weike Zhang
Healthcare 2025, 13(20), 2643; https://doi.org/10.3390/healthcare13202643 - 21 Oct 2025
Viewed by 401
Abstract
Background: Chronic diseases have proliferated worldwide and become one of the foremost public health challenges. The provincial pooling policy of Chinese Basic Medical Insurance Program (BMIP) (hereinafter the Policy) is conducive to coordinating healthcare resources more broadly and containing medical costs more effectively, [...] Read more.
Background: Chronic diseases have proliferated worldwide and become one of the foremost public health challenges. The provincial pooling policy of Chinese Basic Medical Insurance Program (BMIP) (hereinafter the Policy) is conducive to coordinating healthcare resources more broadly and containing medical costs more effectively, which creates opportunities to improve chronic disease patients’ health outcomes. Against this backdrop, this study aims to identify how the Policy affects chronic disease patients’ health outcomes. Methodology: Utilizing data from the China Family Panel Studies (CFPS) across 31 provinces (except Hong Kong, Macao, and Taiwan) from 2010 to 2022, we constructed a panel of 26,585 observations on chronic disease patients enrolled in the BMIP. We employed a difference-in-differences (DID) design to identify the causal effects of the Policy on self-rated health (SRH) supplemented by a series of robustness checks, including event-study analysis, placebo tests, and propensity score matching DID (PSM-DID). Results: The results show that the Policy enhances Chinese chronic disease patients’ health outcomes across various robustness assessments. However, the effects exhibit heterogeneity in that the Policy can more effectively improve the health outcomes of urban patients, low-income patients, and highly educated patients. The mechanism analysis indicates that the Policy can enhance chronic disease patients’ health outcomes by reducing the out-of-pocket ratio, increasing household income, and stimulating consumer expenditure. Furthermore, digital technology can amplify the effectiveness of the Policy in Chinese chronic disease patients’ health outcomes. Conclusions: These findings provide valuable insights into the potential of provincial pooling and digital technology to optimize Chinese chronic disease management. Full article
(This article belongs to the Special Issue Digital Health and AI for Chronic Disease Control and Management)
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