Research on the Risk Factors of DRG-Based Medical Insurance Fund Management for the Nervous System Disease Group and the Construction of a Predictive Model

Chen Zhishui; Zhang Tao; Li Rui; Yue Xiaolin

Abstract：Objective:To investigate the risk factors of medical insurance fund management for the neurological disease group under the background of Diagnosis Related Groups(DRG)reform,and to construct a warning model to provide references for optimizing the management of medical institutions.Methods:A total of 5 615 medical records from Beijing Tiantan Hospital Affiliated to Capital Medical University in 2024 were selected to simulate and compare the differences in medical insurance fund compensation under the Version 1.1 of China Health-care Security Diagnosis-Related Groups(CHS-DRG),hereinafter referred to as DRG 1.1,and the Version 2.0 of Diagnosis-Related Groups(DRG),hereinafter referred to as DRG 2.0.LASSO regression was used to screen variables,and logistic regression analysis was employed to identify the risk factors of fund management and construct Nomogram prediction model.Results:With the implementation of DRG 2.0,the proportion of cases with fund management risks increased from 23.47％to 25.16％,and the overall surplus rate decreased from 14.97％to 12.57％.Logistic regression showed that age,type of medical insurance,mode of admission,and the CCI comorbidity index were significant influencing factors in fund risk management(P＜0.05),while the use of centrally procured medical consumables had a protective effect.The constructed model had an AUC of 0.827,indicating a certain level of predictive performance.Analysis of high-risk management combinations showed that cases with employee medical insurance,emergency admission,no use of centrally procured medical consumables,and non-surgical treatment were the focus of fund payment management.Conclusions:The adjustment of DRG 2.0 has reduced the deviation of overruns and surpluses among cases.Medical institutions need to strengthen their own management,optimize practical processes,and focus on the refinement of medical insurance fund management.