Study on the Relative Weight Divisions of Diagnosis-related Groups for both Common and Complex Diseases
10.11783/j.issn.1002-3674.2025.01.003
- VernacularTitle:常见病和疑难病的疾病诊断相关分组权重划分研究
- Author:
Yin CHEN
1
;
Yiwei HAO
;
Xiaoyu LIU
Author Information
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)
- Publication Type:Journal Article
- Keywords:
Relative weight;
Treatment difficulty;
Diagnosis-related groups;
K-medoids
- From:
Chinese Journal of Health Statistics
2025;42(1):12-17
- CountryChina
- Language:Chinese
-
Abstract:
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.
