考虑护理工作量的呼吸内科DRG分组探索研究

Exploratory study of DRG grouping in respiratory medicine considering nursing workload

目的:探究疾病诊断相关分组(DRG)运用于呼吸内科护理管理的可行性,构建考虑护理工作量的DRG分组方案。方法:采用病例回顾方法收集2021年1~12月某医院呼吸内科1094例住院患者电子病历数据,以护理工时作为DRG分组依据,采用单因素分析、多元线性回归探讨护理工时的影响因素,筛选分组变量,采用决策树E-CHAID算法构建考虑护理工时的DRG分组方案。结果:单因素分析和多元线性回归结果显示影响护理工时的因素主要有并发症与合并症程度(CCI)、年龄、入院途径、入院次数、呼吸机使用、抗菌药物使用,其中CCI、年龄、呼吸机使用、入院次数作为分组变量进入决策树模型,形成10个DRG分组。各组间CV值均<1,RIV值为37.7%,差异具有统计学意义(P<0.05),分组方案良好。结论:基于决策树构建的考虑护理工作量的呼吸内科DRG分组方案合理,可为护理人力资源配置和护理绩效考核等临床护理管理提供参考。

Objective:To investigate the feasibility of applying disease diagnosis-related grouping(DRG)to nursing management in respiratory medicine and to construct a DRG scheme that takes the nursing workload into account.Methods:A case-review method was used to collect data from 1094 electronic medical records of inpatients in the respiratory medicine department of a hospital from January to December 2021,and nursing work hours were used as the basis for DRG grouping,univariate analysis,and multiple linear regression were used to explore the factors influencing nursing work hours,to screen the grouping variables,and a decision tree E-CHAID algorithm was used to construct a DRG grouping scheme considering nursing work hours.Results:The results of univariate analysis and multiple linear regression showed that the factors affecting nursing work hours were mainly the degree of complications and comorbidities(CCI),age,route of admission,number of admissions,ventilator use,antimicrobial drug use,which CCI,age,ventilator use and number of admissions were entered into the decision tree model as grouping variables to form 10 DRGs.The CV values among all groups were<1,and the RIV value was 37.7%,with statistically significant differences(P<0.05),and the grouping scheme was good.Conclusion:The DRG scheme of respiratory medicine considering nursing workload constructed based on a decision tree is reasonable and can provide a reference for clinical nursing management such as nursing human resource allocation and nursing performance assessment.