数智化技术推进罕见病医疗保障机制:概念与应用  

Using Digital Intelligence in Promoting Mechanism for Medical Care Insurance for Rare Diseases:Concepts and Applications

作　　者：杨昕昱 张誉铮 王胜锋[1,2,4] 郭武栋 YANG Xinyu;ZHANG Yuzheng;WANG Shengfeng;GUO Wudong(Department of Epidemiology and Biostatistics,School of Public Health,Peking University,Beijing 100191,China;Key Laboratory of Epidemiology of Major Diseases(Peking University),Ministry of Education,Peking University,Beijing 100191,China;Department of Medical and Health Technology Assessment and Innovation Development,China National Health Development Research Center,Beijing 100044,China;Institute for Artificial Intelligence,Peking University,Beijing 100871,China)

机构地区：[1]北京大学公共卫生学院流行病与卫生统计学系,北京100191 [2]北京大学重大疾病流行病学教育部重点实验室(北京大学),北京100191 [3]国家卫生健康委卫生发展研究中心医药卫生技术评估与创新发展部,北京100044 [4]北京大学人工智能研究院,北京100871

出　　处：《罕见病研究》2025年第1期30-38,共9页Journal of Rare Diseases

基　　金：国家自然科学基金(72342015)。

摘　　要：本研究旨在系统总结和评估数智技术在罕见病医疗保险领域中的应用现状与前景,并构建数智化赋能的罕见病医疗保障机制概念框架。通过检索PubMed、Embase、Web of Science、中国知网、万方数据知识服务平台、维普中文科技期刊数据库等,以“罕见病、医疗保险、人工智能、预测模型、机器学习、大数据、算法”及对应的英文检索词收集相关文献,并制订纳入排除标准。研究发现,中国罕见病医疗保障机制在药品准入和基金承载力等方面面临显著挑战,而数智化技术在筹资、准入、支付和监管环节展现出广泛的应用潜力。具体而言,动态仿真模型和大数据分析能够精准预测医保基金需求;机器学习算法优化了药物安全性和经济性的动态评估;个性化支付模型可有效识别高额费用人群,缓解基金支出压力;智能监控技术则实现了医保基金异常行为的精准检测。这些技术为完善罕见病医疗保障机制提供了系统化、科学化的解决方案。尽管仍需进一步实践验证,数智化技术在提升医保体系的灵活性、高效性和可持续性方面展现出显著潜力,有望更好地满足罕见病患者的需求。Our study aims at systematically summarizing and evaluating the applications of digital intelli-gence technologies in the field of rare disease medical care insurance now and in the future and at constructing a conceptual framework for the digital powered mechanism for the medical care insurance for rare diseases.By using Chinese keywords of"rare disease""medical insurance""artificial intelligence""prediction model""machine learning""big data""algorithm"and their English equivalents,we searched the databases of PubMed,Embase,Web of Science,CNKI,Wanfang,and VIP,collected relevant literature,and decided the criteria of inclusion and exclusion.The finding of our study shows that medical care insurance mechanism of rare disease in China faces significant challenges in drug accessbility and the funding sustainability.Meanwhile,our study shows that the digital intelligence technologies have broad potential in applications-in financing,accessbility,payment,and supervision.Specifically,dynamic simulation models and big data analysis can make precise prediction of the demand for funding of medical care insurance.The machine learning algorithms improve the dynamic evaluation of drug safety and cost-effectiveness.The personalized payment models enhance the efficiency in identifying the cohort with high expenditure so as to alleviate fund expenditure pressures.The intelligent monitoring technologies can accurately detect the abnormal behaviors in funds of medical care insurance.These technologies provide systematic and scientific solutions for improving the medical care mechanism for rare diseases.Even though further investigation is needed,the digital intelligence technologies have shown remarkable potential in enhancing the flexibility,efficiency,and sustainability of the medical care insurance system and a promising future in meeting the needs of patients with rare diseases.

关 键 词：罕见病 医疗保障 数智化 机制设计 

分 类 号：R197.1[医药卫生—卫生事业管理] TP39[医药卫生—公共卫生与预防医学]