[1]周鹏飞,杨孝光,路 强,等.恶性肿瘤术后化疗住院患者DRG分组研究 ——基于E-CHAID算法[J].卫生经济研究,2023,40(6):35-39,43.
　ZHOU Pengfei,YANG Xiaoguang,LU Qiang,et al.Study on DRG Grouping of Postoperative Chemotherapy Inpatients with Malignant Tumor ——Based on E-CHAID Algorithm[J].Journal Press of Health Economics Research,2023,40(6):35-39,43.
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恶性肿瘤术后化疗住院患者DRG分组研究
——基于E-CHAID算法
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卫生经济研究[ISSN:1004-7778/CN:33-1056/F]

卷:
40
期数:
2023年6期
页码:
35-39,43
栏目:
疾病经济负担
出版日期:
2023-06-05

文章信息/Info

Title:
Study on DRG Grouping of Postoperative Chemotherapy Inpatients with Malignant Tumor
——Based on E-CHAID Algorithm
作者:
周鹏飞1; 2; 杨孝光2; 路 强2; 王 帅2; 裴家兴1; 2; 郭 望2; 3; 张瀚博2; 李运明1; 2; 3
1.西南医科大学公共卫生学院，四川 泸州 646000
2.西部战区总医院，四川 成都 610083
3.西南交通大学数学学院，四川 成都 611756
Author(s):
ZHOU Pengfei;  YANG Xiaoguang;  LU Qiang;  WANG Shuai;  PEI Jiaxing;  GUO Wang;  ZHANG Hanbo;  LI Yunming
School of Public Health, Southwest Medical University, Luzhou Sichuan 646000, China
关键词:
恶性肿瘤; 化疗; 疾病诊断相关分组; 决策树
Keywords:
malignant tumor;  chemotherapy;  disease diagnosis related grouping;  decision tree
分类号:
R195；F840.684
文献标志码:
A
摘要:
目的：分析恶性肿瘤术后化疗患者住院费用的影响因素，设计DRG分组方案并制定支付标准，为DRG支付方式改革提供参考。方法：以四川省成都市某三甲综合医院2021年7月至2022年6月出院的恶性肿瘤术后化疗患者为研究对象，采用非参数检验及多元线性回归筛选出住院费用的主要影响因素，利用E-CHAID算法构建DRG分组方案，利用变异系数及非参数检验评价分组合理性，制定各DRG分组参考费用。结果：住院天数、是否有手术操作及是否有合并症或并发症被纳入决策树模型，最终生成9个DRG分组；各DRG分组的组内同质性高，组间异质性强，分组效果良好。结论：基于E-CHAID算法的恶性肿瘤术后化疗住院患者DRG分组方案科学合理，能够为医疗机构规范诊疗行为、控制资源消耗提供依据。
Abstract:
Objective To analyze the influencing factors of hospitalization expenses of patients with malignant tumor undergoing postoperative chemotherapy, establish the DRG grouping scheme for inpatients with this disease, and formulate the payment standard of hospitalization expenses, so as to provide reference for the reform of DRG payment mode. Methods The patients discharged from a tertiary general hospital in Chengdu, Sichuan Province from July 2021 to June 2022, who were mainly diagnosed with malignant tumors undergoing postoperative chemotherapy, were taken as the research object. The main influencing factors of hospitalization expenses were screened by using nonparametric tests and multiple linear regression. The E-CHAID algorithm was used to construct a DRG grouping scheme, and the coefficient of variation and nonparametric tests were used to evaluate the rationality of grouping and formulate reference costs for each DRG grouping. Results The length of hospital stay, presence of surgical procedures, and presence of comorbidities or complications were included in the decision tree model, resulting in the generation of 9 DRG groups. The intra group homogeneity and inter group heterogeneity of each DRG group are high, and the grouping effect is good. Conclusion The DRG grouping scheme based on E-CHAID algorithm for the inpatients with malignant tumor undergoing postoperative chemotherapy is scientific and reasonable, which can provide a basis for medical institutions to regulate medical behavior and control unreasonable resource consumption, and also provide some reference for promoting the reform of DRG payment mode.

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更新日期/Last Update: 2023-06-05