Objective: The paper attempts to improve the quality of the medical insurance settlement list and consolidate the DIP payment foundation. Methods: The paper analyzes the current status of the medical insurance settlement list quality in the sample areas from the three dimensions of completeness, standardization and rationality, explores the construction of a closed-loop quality control management model, and compares and analyzes the implementation effect of the model before and after the intervention. Results: In 2023, there were 87500 lists (accounting for 8.12%) that failed the quality control, of which completeness, standardization, and rationality issues accounted for 3.51%, 11.18%, and 8.85%, respectively. A closed-loop quality control management model for medical insurance settlement lists was built from the establishment of quality control rule database, pre-quality control data verification, real-time feedback of problems, and timely revision of medical institutions. After the implementation of this model, the proportion of the number of unqualified lists from January to June 2024 dropped to 2.67%. Conclusionsand Suggestions: At present, the quality of the medical insurance settlement list needs to be improved, and the problems of standardization and rationality are more prominent. Through the construction of a closed-loop quality control management model and multi-department cooperation, the connotation and quality of the medical insurance settlement list can be improved. Also, we should strengthen the construction of information systems, continuously optimize quality control rules, improve data governance capabilities, and empower the efficient operation of medical insurance funds.