{"title":"A Decision Tree Model-based Study on the Grouping of Hospitalization Expenses of Type 2 Diabetes Patients in a Traditional Chinese Medicine Hospital","authors":"Xue Zhang, Jianke Ren, Xin Wang, Lijun Liang","doi":"10.62051/7d9h3y73","DOIUrl":null,"url":null,"abstract":"Objective To discover the case-mix approach for TCM treatment of dominant disease type 2 diabetes patients and to analyze the hospitalization expense standards for different combinations of patients to provide theoretical references for better participation of TCM hospitals in the DRG payment method as well as reasonable regulation of hospitalization expenses for TCM type 2 diabetes patients in the future. Methods Case data were collected from 1,171 patients discharged with a principal diagnosis of type 2 diabetes from September 2021 to April 2023 from a tertiary care Chinese medicine hospital in Tianjin. Univariate and multivariate stepwise regression analyses determined categorical node variables. The decision tree model was used to perform case combinations and to analyze the expense standards and weights of different groups of disease types. Results The number of days of hospitalization, conditions in admission, and whether complicated cardiovascular and cerebrovascular diseases are the main factors affecting the hospitalization expense of type 2 diabetes patients in Chinese medicine hospitals, and the decision tree model was used to group the patients to form nine groups of patient case combinations. The standard of hospitalization expense for each combination was set reasonably. Conclusion The grouping results are more satisfactory, and the grouping scheme and hospitalization expense standards can provide a scientific basis for DRG grouping, adopting differentiated expense management, and improving the medical resource efficiency in TCM hospitals.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions on Computer Science and Intelligent Systems Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.62051/7d9h3y73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective To discover the case-mix approach for TCM treatment of dominant disease type 2 diabetes patients and to analyze the hospitalization expense standards for different combinations of patients to provide theoretical references for better participation of TCM hospitals in the DRG payment method as well as reasonable regulation of hospitalization expenses for TCM type 2 diabetes patients in the future. Methods Case data were collected from 1,171 patients discharged with a principal diagnosis of type 2 diabetes from September 2021 to April 2023 from a tertiary care Chinese medicine hospital in Tianjin. Univariate and multivariate stepwise regression analyses determined categorical node variables. The decision tree model was used to perform case combinations and to analyze the expense standards and weights of different groups of disease types. Results The number of days of hospitalization, conditions in admission, and whether complicated cardiovascular and cerebrovascular diseases are the main factors affecting the hospitalization expense of type 2 diabetes patients in Chinese medicine hospitals, and the decision tree model was used to group the patients to form nine groups of patient case combinations. The standard of hospitalization expense for each combination was set reasonably. Conclusion The grouping results are more satisfactory, and the grouping scheme and hospitalization expense standards can provide a scientific basis for DRG grouping, adopting differentiated expense management, and improving the medical resource efficiency in TCM hospitals.