The traditional chronic disease management system is confronted with challenges such as the growing pressure on medical insurance fund expenditures, inefficient allocation of medical resources, and inadequate regulatory methods. Taking the practice of Tai'an City, Shandong Province as a case study, this research discusses a full-chain management system for medical insurance funds of outpatient chronic and special diseases based on big data and artificial intelligence (AI) technologies. In terms of architecture, this model constructs a functional framework of "1 platform plus 4 subsystems", with the AI-based risk management analysis platform as the core, integrating four functional modules: eligibility admission and withdrawal, standardized diagnosis and treatment pathways, intelligent medical insurance supervision, and health management. At the institutional level, the model is supported by a governance framework featuring government-society resource collaboration, an efficient and unified pharmaceutical supply chain management, and an incentive-compatible medical insurance payment method. Statistics and empirical analysis based on the actual operation data of the system show that this system has significantly alleviated the expenditure pressure on medical insurance funds and improved the health status of patients.
Key words
outpatient chronic and special disease /
medical insurance fund /
digital intelligence empowerment /
health management
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