Data-driven DRG-DIP-clinical pathway multidimensional fusion analysis and evaluation
10.3760/cma.j.cn111325-20230725-00693
- VernacularTitle:数据驱动的DRG-DIP-临床路径多维融合分析评价
- Author:
Sizhe LONG
1
;
Ruilin ZHANG
;
Yuluan CHEN
;
Yang LIU
;
Zhentian WU
;
Junrong YU
Author Information
1. 中山大学附属第一医院信息数据中心，广州 510080
- Keywords:
Diagnosis-related groups;
Diagnosis-intervention packet;
Clinical pathway;
Multi-dimensional integration;
Management evaluation
- From:
Chinese Journal of Hospital Administration
2024;40(1):64-69
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the correlation between the grouping and weighting of two sets of disease combination systems, namely diagnosis-related groups(DRG) and diagnosis-intervention packet(DIP), and to establish a multidimensional analysis and evaluation mode by applying DRG, DIP, and clinical pathway to guide the standardized diagnosis and treatment and management of disease types.Methods:DRG grouping and DIP simulation full enrollment were applied to patients discharged from a tertiary Grade A general hospital in 2019. The correlation analysis between DRG, DIP, and clinical pathway inclusion(entry), correlation analysis between relative weight of DRG group and DIP standard score, and correlation analysis between clinical pathway entry and cost structure of the two disease groups were conducted by using chi-square test, Pearson correlation analysis, t-test, structural change value, degree of structural change, and incremental contribution rate. Results:Among the 130 395 patients, 41 460 cases entered the clinical pathway, 127 535 cases were enrolled in DRG, and 104 227 cases were enrolled in DIP. There was a correlation between the enrollment of DRG, DIP, and clinical pathway( P<0.05), and there was also a correlation between the relative weight of DRG groups and the enrollment of clinical pathway. The relative weight of the DRG disease group was positively correlated with the DIP standard score( r2=0.761 7, P<0.001). There was a significant difference in hospitalization costs between patients with and without clinical pathway access for some diseases( P<0.05), and different cost categories had different impacts on the total costs. Conclusions:The weight assignment and value orientation of DRG and DIP disease types are consistent, and the multi-dimensional fusion evaluation mode for DRG-DIP-clinical pathway is feasible. The correlation analysis of DRG, DIP, and clinical pathways can serve as the basis for disease classification and cost structure evaluation, which could help to carry out hospital′s refined management and optimize disease structure.
