| 引用本文：赵梦园, 林坤河, 熊英贝, 姚轶凡, 陈知禾, 张雨孟, 项莉.DIP支付方式下医疗机构医保支付率及影响因素分析[J].中国卫生政策研究,2024,17(6):40-46 |
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| DIP支付方式下医疗机构医保支付率及影响因素分析 |
| 投稿时间：2024-04-17 修订日期：2024-06-06 PDF全文浏览 HTML全文浏览 |
| 赵梦园1, 林坤河1, 熊英贝1, 姚轶凡1, 陈知禾1, 张雨孟1, 项莉1,2 |
1. 华中科技大学同济医学院医药卫生管理学院 湖北武汉 430030;
2. 国家医疗保障研究院华科基地 湖北武汉 430030 |
| 摘要:目的：分析DIP支付方式下医疗机构的医保支付率现状及其影响因素，以完善DIP支付政策，促进医疗机构优化内部运营及合理补偿。方法：基于2022年A市196家医疗机构DIP结算数据，运用多重线性回归分析医保支付率影响因素，并对不同等级医疗机构进行异质性分析。结果： A市医疗机构2022年医保支付率为103.32%，CMI标准化次均住院费用越低、偏差病例占比越低、三级医疗机构、四级手术占比越低、居民与职工医保病例比值越低的医疗机构医保支付率越高(P＜0.05)。异质性分析发现，偏差病例占比、基层病种病例占比、居民与职工医保病例比值、低标入院率对不同等级医疗机构影响不同。结论：医保部门应完善基层病种政策，动态调整病种目录和支付标准，优化筹资水平与机构系数，提高违规处罚力度，确保基金有效利用。医疗机构需加强政策理解，注重内部精细化管理，通过转变绩效考核促进规范合理诊疗，发挥自身医疗服务优势合理提升医保支付率。 |
| 关键词:医保支付率 医保 DIP 异质性分析 |
| 基金项目:国家自然科学基金项目(72174068；71874058) |
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| Analysis of medical reimbursement rate and influencing factors under the DIP payment method |
| ZHAO Meng-yuan1, LIN Kun-he1, XIONG Ying-bei1, YAO Yi-fan1, CHEN Zhi-he1, ZHANG Yu-meng1, XIANG Li1,2 |
1. School of Medical and Health Management, Tongji Medical College of Huazhong University of Science and Technology, Wuhan Hubei 430030, China;
2. HUST Base of National Institute of Healthcare Security, Wuhan Hubei 430030, China |
| Abstract:Objective: Analyze the medical reimbursement rate and influencing factors under the DIP payment method to refine the DIP payment policy, promote the optimization of internal operations in medical institutions, and ensure reasonable compensation. Methods: Based on the 2022 DIP fund settlement data from 196 medical institutions in City A, the study used multiple linear regression to analyze the factors affecting medical reimbursement rate and conducted a heterogeneity analysis for medical institutions of different levels. Results: The medical reimbursement rate for medical institutions in City A in 2022 was 103.32%. Medical institutions with lower CMI standardized inpatient costs, lower rates of deviation cases, tertiary care institutions, lower proportion of level-four surgeries, and lower ratios of resident to employee medical insurance cases have higher medical reimbursement rate (P<0.05).Heterogeneity analysis reveals that therates of deviation cases, the proportion of primary care diseases, the ratio of resident to employee medical insurance cases, and the low-standard admission rate have different impacts on medical institutions of different levels. Conclusion: Medical insurance departments should improve policies for primary care diseases, dynamically adjust disease catalogs and payment standards, optimize funding levels and institutional coefficients, and increase penalties for violations to ensure effective use of funds. Medical institutions need to strengthen their understanding of policies, focus on refined internal management, promote standardized and rational diagnosis and treatment through performance assessment transformation, and leverage their own advantages in medical services to reasonably increase the medical reimbursement rate. |
| Key words:Medical reimbursement rate Medical insurance DIP Heterogeneity analysis |
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