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TANG Cheng, FENG Zhanchun, LI Gang, ZHAO Rui. AI-empowered active health management for chronic disease patients: a case studyJ. Chinese Journal of Public Health, 2026, 42(5): 545-550. DOI: 10.11847/zgggws1146317
Citation: TANG Cheng, FENG Zhanchun, LI Gang, ZHAO Rui. AI-empowered active health management for chronic disease patients: a case studyJ. Chinese Journal of Public Health, 2026, 42(5): 545-550. DOI: 10.11847/zgggws1146317

AI-empowered active health management for chronic disease patients: a case study

  • Objective To analyze typical cases of AI-empowered proactive health management for chronic disease patients, providing mature references for advancing the application of AI in healthcare institutions and chronic disease patient management.
    Methods From October 20 to November 1, 2024, we searched platforms including the China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP, Chinese Medical Journal Full-text Database, Health News, and the official websites of the National Health Commission and the Chinese Center for Disease Control and Prevention for the typical cases of AI-empowered proactive health management for chronic disease patients. Using the text analysis method based on key dimensions of proactive health concepts, we established a thematic framework through hierarchical coding to distill the practical outcomes of these cases.
    Results A total of 43 AI-empowered proactive health management cases for chronic disease patients were included as primary textual sources for framework construction. Three thematic frameworks—individual health responsibility, interpersonal relationship support, and disease management—were constructed. Individual health responsibility involved health monitoring, health assessment, and health education. Interpersonal relationship support included social support and psychological support. Disease management encompassed medication management, diet management, and personalized intervention. Through further screening, 10 representative cases were finalized, and an integrated pathway for AI-empowered proactive health management was distilled. That is, by integrating big data with human-machine interaction, a bidirectional proactive health management cycle was established between healthcare institutions and chronic disease patients, encompassing health monitoring, assessment/diagnosis, intervention reminders, and medication management.
    Conclusions AI enables integrated health management by bidirectionally empowering both healthcare institutions and chronic disease patients. This approach not only enhances patient engagement but also alleviates the workload of primary care providers.
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