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作 者:刘星雨 韦皓琪 孙浩然 刘晓勇 刘星宸 章洁琼 杨才君[1]
机构地区:[1]西安交通大学药学院,西安710061 [2]西安交通大学宗濂书院,西安710061 [3]宜兴市生命健康产业创新服务中心,无锡214000
出 处:《中国医疗保险》2025年第3期51-59,共9页China Health Insurance
摘 要:目的:探讨我国DRG支付背景下各地基础病组名单的设定特点与规律,为优化基础病组政策提供科学参考。方法:通过检索全国2022—2024年发布的政策文件,收集20个城市的基础病组名单及相关信息。采用描述性统计分析各地病组数量、疾病类别、权重范围,并计算Jaccard相似系数分析城市间相似性。结果:各地基础病组数量差异显著(3~117个)。基础病组以内科诊断为主(85%),权重值多集中于0.2~0.8,60%不伴并发症或合并症。主要诊断类别(MDC)最多分布在消化系统疾病及功能障碍(MDCG)。城市间相似性差异较大,雅安、保山等地相似度高,安阳、铜仁、银川等地因病组数量极端、细分组不同或地方特色相似度较低。结论:建议优化基础病组遴选原则,兼顾地方疾病谱与医疗资源差异,动态监测其适配性;加强跨区域协作,强化数据支持,共同促进分级诊疗与医保支付效率优化。Objective:The paper explores the characteristics and rules of the list of basic disease groups in China under the background of DRG payment,in order to provide a scientific reference for optimizing the policy of basic disease groups.Methods:The list of basic disease groups and related information in 20 cities was collected by searching the policy documents released from 2022 to 2024 in China.Descriptive statistics were used to analyze the number of disease groups,disease categories and weight ranges in different regions,and the Jaccard similarity coefficient was calculated to analyze the similarity between cities.Results:There were significant differences in the number of basic disease groups,varying from 3 to 117.In the basic disease groups,85%were mainly diagnosed by internal medicine,the weight values were mostly from 0.2 to 0.8,and 60%had no complications or comorbidities.The main diagnostic category(MDC)is most commonly distributed in digestive disorders and dysfunction(MDCG).There were large differences in similarity among cities,with Ya'an and Baoshan City having a high degree of similarity,while Anyang,Tongren,Yinchuan having a low degree of similarity due to the extreme number of disease groups,different sub-groups or local characteristics.Conclusion:It is recommended to optimize the selection principle of disease groups,take the differences in local disease spectrum and medical resources into account,and dynamically monitor their suitability.Also,cross regional collaboration data support should be strengthened,jointly promoting the optimization of hierarchical diagnosis and treatment and medical insurance payment efficiency.
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