Research on the Influencing Factors of Hospitalization Expense of Patients with Uterine Leiomyoma in Beijing Based on Grey Correlation Analysis and Random Forest Model
Objective:To investigate the internal structure and determinants of hospitalization expenses for uterine leiomyoma patients in DRG pilot and non-DRG pilot hospitals in Beijing,to fumish insights for the forthcoming phase of public hospital reform.Methods:The statistical data of 5 DRG pilot hospitals and 124 non-DRG pilot hospitals in Beijing from 2015 to 2021 were collected to analyze the correlation degree between each detail expense and the average hospitalization expense by using grey correlation analysis,and the influencing factors of the average hospitalization expense of hospitalized patients by using random forest model.Results:The results of the grey correlation analysis revealed that the highest correlations affecting hospitalization expense in the DRG pilot hospital group and the non-DRG pilot hospital group were the average expense in each surgical treatment and the average drug costs for each patient,respectively,and the lowest was the average expense of inspection and test in each patient.The results of random forest model showed that the top two influencing factors of DRG pilot hospital group were consumption ratio and the average length of hospitalization,while the average length of hospitalization,surgical treatment expense ratio and consumption ratio are more important than other influential factors of non-DRG pilot hospital group.Conclusion:DRG payment is conducive to optimizing the hospitalization expense structure of uterine leiomyoma hospitalized patients.The average length of hospitalization,consumption ratio,and surgical treatment expense ratio are important factors affecting the hospitalization expense of uterine leiomyoma hospitalized patients.Public hospitals should continue to optimize the expense structure in the future,pay equal attention to"reducing expenditure"and"open source",implement DRG payment and its supporting measures to enhance the efficiency of medical services,reinforce the comprehensive management of consumables,and empower hospitals and medical personnel.
Diagnosis Related Grouphospitalization expensegrey correlation analysisrandom forest model
NETL
NSTL
万方数据
