目的: 采用中断时间序列分析法,评价医保基金智能监管拒付政策对医院耗材支付性质审核管理错误率的影响,探讨该政策对耗材规范化使用医保基金以及医院耗材管控道德风险损害的影响。方法: 选择温州某三甲医院2023年1月—2024年11月期间吻合器和专用创面覆盖材料的住院费用数据,采用DW检验和BG检验对耗材支付性质错误审批率进行自相关检验,采用ADF检验对数据进行平稳性检验,并以耗材智能监管拒付政策实施时间为中断点,采用分段回归模型分析耗材支付性质错批率变化情况。结果: 耗材智能监管拒付政策实施后,从长期影响来看,吻合器自费错批率以每月0.51个百分点的水平上升,专用创面覆盖材料自费错批率以每月0.28个百分点的水平上升;吻合器医保错批率以每月0.08个百分点的水平下降,专用创面覆盖材料医保错批率以每月3.95个百分点的水平下降。结论: 耗材智能监管拒付政策对医院正确审核耗材支付性质,合规使用医保基金起到一定正向作用,但同时加大了医院的耗材费用审核压力和拒付金额损失自担风险,可能引发医院将本可医保支付的耗材审批为自费,转嫁风险给患者。为优化智能监管拒付政策,医院应推动耗材审核模式由人工主导向智能机审转变。同时强化医务人员培训与院内监测奖惩机制,防范费用转嫁风险,降低政策执行的初期适应成本,并协同医保部门探索构建统一标准化的医保支付规则库、知识库。

Objective: The study used interrupted time series analysis to evaluate the impact of medical insurance fund intelligent supervision with denial-of-payment policy on hospital consumables payment type verification error rates, and to explore the policy's effects on standardized utilization of medical insurance fund for consumables and mitigation of moral hazard in hospital consumables management control. Methods: This study selected inpatient cost data for staplers and specialized wound covering materials from a Class-A tertiary public hospital in Wenzhou City, covering the period from January 2023 to November 2024. We employed the DW test and BG test to examine autocorrelation in the consumables payment type verification error rate, conducted the ADF test to assess data stationarity, and utilized the implementation date of the consumables intelligent supervision and denial-of-payment policy as the interruption point. A segmented regression model was applied to analyze changes in the consumables payment type mis-verification rate. Results: Post-implementation of the consumables intelligent supervision and denial-of-payment policy, long-term analysis showed the self-payment mis-verification rate for staplers increased by 0.51 percentage points per month, while the self-payment mis-verification rate for specialized wound covering materials increased by 0.28 percentage points monthly. Conversely, the medical insurance mis-verification rate for staplers decreased by 0.08 percentage points per month, and the medical insurance mis-verification rate for specialized wound covering materials decreased significantly by 3.95 percentage points monthly. Conclusions: While the consumables intelligent supervision and denial-of-payment policy exerts a positive influence on hospitals' accurate verification of consumable payment types and compliant utilization of medical insurance funds, it simultaneously increases hospitals' burden in consumables cost review and the financial risk of bearing denied payment costs. Furthermore, it may lead hospitals to approve reimbursable medical consumables as self-paid items, thereby shifting the financial risk onto patients. To optimize the intelligent supervision and denial-of-payment policy, hospitals should transition their consumables audit model from a manual paradigm to an intelligent, machine-led one. This requires enhanced training for medical staff and the establishment of robust internal monitoring and incentive mechanisms to mitigate cost-shifting risks and reduce initial adaptation costs. Concurrently, collaboration with healthcare security authorities is essential to explore the development of a unified and standardized knowledge base for medical insurance payment rules.