精神科DRG优化分组方案研究*

目的：探索精神科按疾病诊断相关分组 （DRG） 优化分组方案,为提升DRG工具在精神科医保付费的针对性、 有效性提供支持。方法：依托京津冀精神卫生大数据平台,选取从2018—2019年北京安定医院符合DRG入组条件的住院患者数据进行回顾性研究。基于决策树模型构建优化分组方案,使用方差分析和秩和检验进行MDCT-DRG （DRG主要诊断大类精神科类别下的DRG组） 组内、组间差异性比较,用总体方差减少系数 （RIV） 评估分组效能。结果：优化后精神科DRG组内一致性和组间异质性均有提高,分组效能较好。结论：精神科DRG分组方案可以采用决策树模型进行优化。在国家医保制度改革中,还应进一步研究精神科患者住院及对医疗资源消耗的特点和规律,制定适用于精神科的医保支付方式,更加有效发挥DRG在医保费用监测和绩效评价中的作用。

Assessment and Recommendation on Psychiatric DRGs Optimisation Grouping Scheme

Objective: To explore the optimal grouping scheme of psychiatric Diagnosis Related Groups (DRG), and to provide sup- port for improving the targeting and effectiveness of DRG tools in psychiatric medical insurance payments. Methods: Based on the Beijing-Tianjin-Hebei Mental health big data platform, data of inpatients eligible for DRG inclusion in Beijing Anding Hospital from 2018 to 2019 were selected for retrospective study. An optimal grouping scheme was constructed based on the decision tree model. Variance analysis and rank sum test were used to compare the differences within and between MDCT-DRG groups, and reduction in- variance (RIV) was used to evaluate the grouping efficiency. Results: After the optimization, the intra-group consistency and in- ter-group heterogeneity of psychiatric DRG were improved, and the grouping efficacy was better. Conclusion: The DRG grouping scheme in Psychiatric Department can be optimized by decision tree model. In the national medical insurance reform, the characteris- tics of hospitalization and consumption of medical resources by psychiatric patients should be further studied, to formulate a more suit- able payment method for psychiatric departments, so as to play a more effectively role of DRG in medical insurance and performance evaluation.