随着DRG/DIP医保支付方式改革的持续推进,基金监管中出现了套高病组、费用转移等新问题。本文深入研究上海在DRG/DIP医保智能监管中的创新性实践,系统展示该市从监管指标、规则应用的初步探索到基于病组循证轨迹的智能预警模型的创建。预警模型嵌入真实监管场景中,通过引入临床路径的理念并应用大数据+AI技术进行疑点检出,降低监管人员对医学专业知识的依赖。基于DRG/DIP病组循证轨迹的智能预警模型的应用有效提高了监管工作的科学性、精准性、高效性,建议未来继续扩大DRG/DIP智能监管预警范围,逐步优化病组循证轨迹,持续强化医院主动监管意识。

With the continuous advancement of the DRG/DIP medical insurance payment methods reform, new problems such as upcoded disease groups and cost transfer have emerged in medical insurance fund supervision. This paper deeply studied the innovative practice of Shanghai in DRG/DIP medical insurance intelligent supervision, and systematically demonstrated Shanghai's initial exploration of regulatory indicators and rule application to the construction of an intelligentwarning model based on evidence-based trajectory of disease groups. The warning model was embedded in the real supervision scenarios, the concept of clinical pathways was introduced, and big data plus AI technology was applied to detect suspicious points, the supervision personnel's dependence on medical professionals was reduced. The application of the intelligent warning model based on the evidence-based trajectory of DRG/DIP disease groups has effectively improved the scientificity, accuracy and efficiency of supervision. In the future, it is recommended to expand the scope of DRG/DIP intelligent supervision and warning, gradually optimize the evidence-based trajectory of disease groups, and continuously strengthen the hospitals' awareness of active supervision.