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投稿时间：2024-09-23 网络发布日期：2025-05-20
投稿时间：2024-09-23 网络发布日期：2025-05-20
中文摘要: 目的 分析基于控制论反馈模型研发的人工智能系统应用于医保支付的优化作用。方法 针对超声诊疗类别的不明确问题，本团队利用控制论反馈模型研发了用于超声诊疗医保支付的人工智能系统，并对比该系统应用前后的差异。通过医院信息管理系统（HIS）、影像存储传输系统（PACS）以及医保支付数据平台，对医保基金支付异常数据进行全面收集。收集时间为 2020年 1月至 2023年 12月。采用定量分析方法，对原始医保异常数据及控制论反馈系统改进后的医保异常数据进行分析。结果 共收集到原始医保异常数据 46 617条记录。其中，超量收费共记录 7 736例（386 800）元；扩大范围收费共 4 877例（68 016元）；重复收费共 28 976例（1 028 586元）；分解收费共 1 321例（92 470元）；超标准收费共 3 651例（255 525元）；串换类共 56例（560元）。控制论反馈系统改进后的医保异常数据共 492条，其中超量收费 135条，扩大范围收费 4条，重复收费 281条，分解收费 60条，超标准收费 12条，未发生串换类。与原始医保异常数据比较，控制论反馈系统改进后的医保异常数据显著减少，医保支付金额显著降低。结论 基于控制论反馈模型的超声诊疗人工智能系统能显著减少了不必要的检查，降低医保基金支付，提高患者满意度，同时减少按疾病诊断相关分组误判率，提升医护人员工作效率。
Abstract:Objective To analyzes the optimization function of artificial intelligence system based on control theory feedback model applied to medical insurance payment. Methods Aiming at the unclear category of ultrasonic diagnosis and treatment, an artificial intelligence system for ultrasonic diagnosis and treatment medical insurance payment was developed through using control theory feedback model by our team, and the differences before and after application of this system was compared. A comprehensive collection of abnormal data on medical insurance fund payments was conducted using the hospital information system (HIS) , picture archiving and communication system (PACS) , and the medical insurance payment data platform, covering the period from January 2020 to December 2023. Quantitative analysis methods were employed to analyze both the original abnormal medical insurance data and theimproved data following the implementation of the control theory feedback system. Results A total of 46 617 records of original abnormal medical insurance data were collected. Among these, excessive charges accounted for 7 736 cases, totaling 386 800 yuan; expanded scope charges for 4 877 cases, totaling 68 016 yuan; duplicate charges for 28 976 cases, totaling 1 028 586 yuan; decomposed charges for 1 321 cases, totaling 92 470 yuan; over-standard charges for 3 651 cases, totaling 255 525 yuan; and category switching for 56 cases, totaling 560 yuan. After the improvement with the control theory feedback system, there were 492 records of abnormal medical insurance data, including 135 cases of excessive charges, 4 cases of expanded scope charges, 281 cases of duplicate charges, 60 cases of decomposed charges, and 12 cases of over.standard charges, with no occurrences of category switching. Compared with the original abnormal medical insurance data, the abnormal data after the improvement significantly decreased, along with a significant reduction in medical insurance payment amounts. Conclusion The artificial intelligence system for ultrasound diagnostic and treatment based on the control theory feedback model can significantly reduce unnecessary examinations, lower medical insurance fund payments, enhance patients’satisfaction, decrease the misjudgment rate of diagnosis related groups (DRG) , and improve the work efficiency of medical staff.
keywords: Ultrasound diagnostic and treatment Medical insurance payment mechanism Artificial intelligencesystem Control theory feedback model Medical quality management
文章编号： 中图分类号：R319 TR18 文献标志码：A
基金项目:南京市医疗保险研究会2024年度课题（NJYB2024ZWH013）
附件
引用文本：
崔晓梅,黄声稀,张庆红,等.基于控制论反馈模型的人工智能系统在超声诊疗医保支付中的应用[J].中国临床研究,2025,38(5):706-709,714.
崔晓梅,黄声稀,张庆红,等.基于控制论反馈模型的人工智能系统在超声诊疗医保支付中的应用[J].中国临床研究,2025,38(5):706-709,714.