随着医疗保障体系不断优化与完善,医疗机构在医保基金监管中的作用日益凸显。为有效遏制不当基金支出,各医疗机构积极运用管理优势和先进技术开展医保费用事前审核工作,但传统的人工审核方式难以匹配医保管理部门的监管要求,新兴的嵌入式智能审核在大型三甲医院高并发场景下存在系统延迟、影响核心业务运行的局限性。针对这些痛点,本研究探寻医保智能审核新模式,自主开发独立分布式医保智能审核辅助工具。该工具采用非嵌入式设计,充分考量大型三甲医院的实际承载能力,在避免影响医院信息系统（HIS）可用性和可持续性的同时,显著提升了审核流程的自动化与智能化水平,从而实现了审核效率和准确性的双重优化。本研究详细阐述了独立分布式医保智能审核辅助模式,系统分析辅助工具的技术方案与实现路径,并结合关键数据对其实际运行情况进行全面评估,总结出一套可推广的实践经验,以期更好地服务于医保基金监管工作。

In the context of continuous optimization and improvement of healthcare system, medical institutions play an increasingly prominent role in medical insurance fund supervision. To effectively curb inappropriate fund expenditures, medical institutions actively utilize management advantages and advanced technologies to conduct pre-auditing of medical insurance expenses. However, traditional manual auditing methods is difficult to meet the regulatory requirements of medical insurance management departments, while emerging embedded intelligent auditing systems face limitations such as system delays and impact on core business operations in high-concurrency scenarios at large tertiary hospitals. Addressing these problems, this study explores new models for intelligent medical insurance auditing, independently developing a distributed auxiliary tool for intelligent medical insurance auditing. This tool employs a non-embedded design that fully considers the actual capacity of large tertiary medical institutions, significantly enhancing the automation and intelligence of the auditing process while avoiding impacts on hospital information systems' availability and sustainability, thereby achieving optimization of auditing efficiency and accuracy. This research elaborates on the independent distributed medical insurance intelligent audit auxiliary model, systematically analyzes the technical solutions and implementation paths of the auxiliary tool, and comprehensively evaluates its actual operation combined with key data. It summarizes a set of replicable practical experience to better serve medical insurance fund supervision work.