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机构地区:[1]联勤保障部队第九八九医院,洛阳471000 [2]河南大学,开封475000
出 处:《中国医疗保险》2024年第8期93-98,共6页China Health Insurance
摘 要:目的:基于肺恶性肿瘤内科诊断组探讨不同病例复杂度衡量模型的异同,为进一步优化DRG分组提供参考。方法:以河南洛阳某三甲医院2019—2022年2131例肺恶性肿瘤内科诊断组为研究对象,分别采用MCC/CC表、PCCL模型和ECC模型计算出研究对象的病例复杂度,通过决策树构建分组,并对分组效果进行对比分析。结果:肺恶性肿瘤内科诊断组按MCC/CC表分为3组,CV值分别为0.51、0.57和0.62,RIV值为0.02;按PCCL模型分为5组,CV值分别为0.57、0.57、0.50、0.76和0.70,RIV值为0.14;按ECC模型分为3组,CV值分别为0.61、0.63和0.49,RIV值为0.03。根据非参数检验结果,各基本组的组间住院费用差异有统计学意义。结论:基于分组性能,MCC/CC表和ECC模型优于PCCL模型,不同ADRG下MCC/CC表和ECC模型分组效果有待进一步对比研究。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.
关 键 词:DRG 肺恶性肿瘤内科诊断组 病例复杂度衡量模型 决策树
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