常见病和疑难病的疾病诊断相关分组权重划分研究  

Study on the Relative Weight Divisions of Diagnosis-related Groups for both Common and Complex Diseases

作　　者：陈吟 郝一炜 刘晓宇 姚润徽 李昂 侯亚冰 董爱然[6] 郭默宁 Chen Yin;Hao Yiwei;Liu Xiaoyu(Beijing Municipal Health Big Data and Policy Research Center,Beijing 101117)

机构地区：[1]北京市卫生健康大数据与政策研究中心(北京市医院管理研究所),101117 [2]首都医科大学附属北京地坛医院 [3]首都经济贸易大学统计学院 [4]清华大学未央书院 [5]首都医科大学燕京医学院 [6]首都医科大学宣武医院

出　　处：《中国卫生统计》2025年第1期12-17,共6页Chinese Journal of Health Statistics

基　　金：首都卫生发展科研专项(首发2021-1G-3051,首发2024-2-3052)。

摘　　要：目的探索基于疾病诊断相关分组权重的疑难和常见疾病范围划分,为绩效评价和分级诊疗推进效果评估提供数据支撑。方法采用CN-DRG分组方案对2022年3188340份病案首页数据分为738组并以病组为单位进行k中心点聚类。模拟4个聚类模型并通过指标对模型解释力度确定最优模型后,划分常见病和疑难病的RW截点。结果经过模型测算确定纳入最优聚类模型的指标为平均住院日、进入重症监护室比例、呼吸机使用比例和例均费用四个指标。内科治疗常见病和疑难病的RW截点为0.97;外科治疗常见病和疑难病的RW截点为2.13。结论本研究首次通过资源消耗、疾病治疗界定了疑难病和常见病的疾病诊断相关分组权重范围。研究结果为医院功能定位落实、临床专科能力评估等提供高诊治难度疾病测算工具。Objective To examine the classification of difficult and common diseases based on the weight of diagnosis related groups and to provide data support for performance evaluation and effect evaluation of the hierarchy medical system.Methods The CN-DRG grouping scheme was utilized to categorize the data from 3188340 medical records into 738 groups in 2022.The disease group performed k-medoids clustering.our clustering models were simulated,and the optimal model was determined by evaluating the explanatory power of each model using specific indicators.Subsequently,the relative weight ranges of DRG for common and difficult diseases were established.Results The optimal clustering model was identified using four indicators:the average length of stay,the proportion of patients admitted to intensive care units,the proportion of patients using ventilators,and the average cost per patient.The relative weight for common and difficult diseases was 0.97 for medical treatment,while for surgical treatment,it was 2.13.Conclusion This study is the first to define the weight ranges of diagnosis-related groups for common and difficult diseases by analyzing resource consumption and treatment outcomes.The findings provide a valuable measurement tool for hospital functional positioning and the evaluation of clinical specialty capabilities.

关 键 词：相对权重 诊治难度 疾病诊断相关分组 K中心点聚类 

分 类 号：R195.1[医药卫生—卫生统计学]