Comparative Study on Case Complexity Measurement Models Based on the Internal Medicine Diagnosis Groups of Pulmonary Malignant Tumors
Objective:The paper explores the similarities and differences of different case complexity measurement models based on internal medicine diagnosis groups of pulmonary malignant tumor to provide a reference for further optimizing DRG grouping.Methods:Taking 2131 cases of pulmonary malignant tumor internal medicine diagnosis groups from a tertiary hospital in Luoyang City of Henan Province from 2019 to 2022 as the research object,the paper adopts the MCC/CC tables,PCCL model and ECC model to calculate the case complexity of the research object,constructs groups through decision trees,and compares and analyzes the effectiveness of the groups.Results:According to the MCC/CC table,the internal medicine diagnosis groups of pulmonary malignant tumor was divided into 3 groups,the CV was 0.51,0.57 and 0.62,and the RIV was 0.02.According to the PCCL model,they were divided into 5 groups,the CV was 0.57,0.57,0.50,0.76 and 0.70,and the RIV was 0.14.According to the ECC model,they were divided into 3 groups,the CV was 0.61,0.63 and 0.49,and the RIV was 0.03.According to the results of non-parametric test,there were significant differences in hospitalization expenses among the basic groups.Conclusion:Based on the grouping performance,the MCC/CC table and ECC model are better than the PCCL model,and the grouping effect of the MCC/CC table and ECC model under different ADRG needs to be further compared and studied.
DRGinternal medicine diagnosis group of pulmonary malignant tumorcase complexity measurement modeldecision tree
NETL
NSTL
万方数据
