ZHOU Liying 1,2 , TAO Junliang 1,2 , DENG Xinxin 1,2 , LIANG Cui 1,2 , YANG Kehu 2 , LI Xiuxia 1,2
  • 1. Health Technology Assessment Center, School of Public Health, Lanzhou University, Lanzhou 730000, P. R. China;
  • 2. Evidence-based Social Sciences Interdisciplinary Innovation Laboratory, Lanzhou University, Lanzhou 730000, P. R. China;
YANG Kehu, Email: yangkh-ebm@lzu.edu.cn; LI Xiuxia, Email: lixiuxia@lzu.edu.cn
Medical insurance fund; Supervision; DRG; Evidence-based health decision-making; Systematic review
10.7507/1672-2531.202411083
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Objective  To systematically review the issues and countermeasures in supervising medical insurance funds under the DRG/DIP payment model. Methods  The CNKI, WanFang Data, CBM, VIP, PubMed, Web of Science, and Embase databases were electronically searched to collect studies related to objectives from inception to March 15, 2024. Two reviewers independently screened the literature, extracted data, and assessed the quality of the included studies using the Critical Appraisal Skills Programme (CASP). Excel 2019 was used for data extraction and organization, and a thematic synthesis approach was employed for analysis. Results  Nineteen qualitative studies were included. Nine studies identified key issues in fund supervision under the DRG/DIP model: inadequate regulatory mechanisms, weak regulatory capacity, low informatization, and traditional regulatory concepts. Fourteen studies proposed optimization strategies, including establishing a regulatory system, customizing regulatory indicators, creating a performance evaluation mechanism, developing talent, promoting multi-party regulation, enhancing intelligent supervision systems, and improving stakeholder collaboration and communication. Conclusion  The DRG/DIP payment model faces challenges in medical insurance fund supervision, including weak mechanisms and capacity. Improving regulatory efficiency and ensuring medical service quality requires strengthening the regulatory system, customizing indicator systems, and enhancing talent development.

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