Impact of two DRG performance management approaches on the operations of neurology and neuro-surgery departments
10.3969/j.issn.1671-332X.2025.02.027
- VernacularTitle:两种DRG绩效管理模式对神经内科和神经外科运营的影响研究
- Author:
Yongji MENG
1
;
Quan WEN
1
;
Minlan ZHANG
1
;
Linling QIN
1
;
Qin LYU
1
Author Information
1. 来宾市人民医院 广西来宾 546100
- Publication Type:Journal Article
- Keywords:
DRG;
Hospital management;
Interrupted Time Series;
Heatmap clustering analysis
- From:
Modern Hospital
2025;25(2):266-269
- CountryChina
- Language:Chinese
-
Abstract:
Objective To examine the impact of two DRG performance management approaches on the operations of neu-rology and neurosurgery departments.Methods DRG discharge case data were collected from a tertiary hospital in Laibin City between January 2022 and April 2024.The Interrupted Time Series(ITS)was used to analyze the impact of the two types of DRG performance management on financial performance,service capacity and efficiency,patient burden,and profitability of the neurology and neurosurgery departments.Heatmap clustering analysis was employed to compare the changes in disease surplus rates before and after the two management models,and non-parametric tests were conducted to analyze the impact of departmental transfers on hospitalization costs.Results The change in the ITS(Interrupted Time Series)slope coefficient for operational effi-ciency was significant in the neurology department but not in neurosurgery.The change rates of disease surplus in the two depart-ments were classified into five categories,with similar trends observed in diseases with closely related weights.Furthermore,hos-pitalization costs for certain diseases significantly increased following the transfer of patients from one department to the other(P＜0.05).Conclusion Significant differences exist in the impact of different DRG(Diagnosis-Related Group)performance management approaches in the same department,and the same DRG performance management approach has varying effects on dif-ferent departments.Departmental transfer is a key factor influencing hospitalization costs.
