基于大数据与人工智能的医院医保智能监控系统设计与应用

Design and Application of Hospital Medical Insurance Intelligent Monitoring System Based on Big Data and Artificial Intelligence

摘要: 针对医保基金使用中重复收费、分解收费、超标准收费、不合理用药等违规行为，以及按疾病诊断相关分组(DRG)支付模式下费用核算与分组管理面临的技术挑战，本文设计并实现了一套基于大数据与人工智能的医院医保智能监控系统。系统通过整合多源异构医疗数据构建违规行为规则库，建立违规风险预测模型。系统与医院HIS、LIS等信息系统对接，在医嘱开具、费用记账等环节实现实时干预。初步试点数据显示，系统上线后月均违规提醒次数呈下降趋势，DRG分组准确率有所提升。初步证据表明，该系统有潜力降低医保违规风险，提升医院精细化管理水平，为DRG支付改革背景下的医院医保管理提供可参考的技术方案。

Abstract: In response to violations such as duplicate billing, itemized billing, exceeding standard billing, and irrational medication use in the utilization of medical insurance funds, as well as the technical challenges faced in cost accounting and grouping management under the Diagnosis-Related Groups (DRG) payment model, this paper designs and implements a hospital medical insurance intelligent monitoring system based on big data and artificial intelligence. The system constructs a rule base for identifying violations by integrating multi-source heterogeneous medical data and establishes a violation risk prediction model. The system interfaces with hospital information systems such as HIS and LIS to enable real-time intervention in doctor’s order issuance and cost accounting. Preliminary pilot data shows that the average monthly number of violation reminders has decreased since the system went online, and the accuracy of DRG grouping has improved. Preliminary evidence suggests that this system has the potential to reduce the risk of medical insurance violations, enhance the level of fine management in hospitals, and provide a technical solution for hospital medical insurance management in the context of DRG payment reform.