目的: 分析英国、加拿大、美国在医保准入中应用真实世界数据（RWD）的实践经验,结合我国政策现状,提出RWD驱动医保准入中药品综合价值评价体系构建路径,为我国医保准入政策完善提供参考。方法: 选取英国国家卫生与临床优化研究所（NICE）在2025年5月前通过高度专业化技术评估纳入英国国家医疗服务体系（NHS）的26种罕见病药品为样本,分析NICE、加拿大药品与健康技术署（CADTH）、美国临床与经济评论研究所（ICER）的医保准入评审报告,并结合具体的应用案例,从企业（P1）和评估机构（P2）两个视角探讨RWD在解决效果（D1）、成本（D2）、人群和市场份额（D3）三个维度不确定性中的具体用途、数据来源及评估机构考量。结果: NICE、CADTH、ICER分别有96%、62%、19%的罕见病药品在医保准入中使用RWD,主要用于评价药品经济性、有效性、安全性、可及性四个维度,具体表现在使用RWD解决效果不确定性（D1）、解决成本不确定性（D2）、解决人群和市场份额不确定性（D3）三大类,具体用途主要包括提供疾病管理费用、患者结局及目标人群数据等。RWD在解决成本（D2）和效果（D1）不确定性方面应用最广。所有类型的RWD均在评估中被企业（P1）和评估机构（P2）使用,但部分数据因适用性或证据等级较低,被评估机构提出异议。结论: RWD在医保准入环节的应用已经被评估机构采纳,但是评估机构对不同用途及不同类型RWD的认可度存在差异。总体而言,RWD在医保准入环节具有重要价值,但仍需通过明确应用场景、完善数据源分级与具体用途相匹配,同时建立规范化指南,以提升其应用的科学性与规范性。
Abstract
Objective: The paper attempts to analyze the practical experience of the United Kingdom, Canada, and the United States in applying real-world data (RWD) to health insurance access (reimbursement) decision-making, and, in light of China's current policy context, propose a construction pathway for an RWD-driven comprehensive value assessment system for pharmaceuticals to inform the improvement of China's reimbursement policy. Methods: Twenty-six orphan drugs that had been included in the UK National Health Service (NHS) through the Highly Specialised Technologies (HST) evaluations conducted by the National Institute for Health and Care Excellence (NICE) before May 2025 were selected as the study samples. The reimbursement assessment reports issued by NICE, the Canadian Agency for Drugs and Technologies in Health (CADTH), and the US Institute for Clinical and Economic Review (ICER) were analyzed. Combining specific application cases, the study examined the use of RWD from two perspectives—companies (P1) and assessment agencies (P2)—to explore the specific purposes, data sources, and assessment agencies' considerations of RWD in addressing uncertainties related to effectiveness (D1), cost (D2), population and market share (D3). Results: RWD was used in the reimbursement assessments of 96%, 62%, and 19% of the drugs evaluated by NICE, CADTH, and ICER, respectively. Its primary applications were in evaluating four dimensions of pharmaceutical value: economic efficiency, effectiveness, safety, and accessibility. Specifically, RWD was employed to address three main categories of uncertainty: effectiveness uncertainty (D1), cost uncertainty (D2), and population and market share uncertainty (D3) . The main purposes included providing data on disease management costs, patient outcomes, and target populations. RWD was most widely applied in addressing cost (D2) and effectiveness (D1) uncertainties. All types of RWD were used by both companies (P1) and assessment agencies (P2), though some datasets were challenged by assessment agencies due to concerns about their applicability or low evidence level. Conclusion: The application of RWD in reimbursement decision-making has been increasingly adopted by assessment agencies. However, differences remain in the degree of acceptance across different purposes and RWD types. Overall, RWD plays a crucial role in the reimbursement process, yet its application still requires clarification of specific use scenarios, alignment of data-source grading with appropriate purposes, and the establishment of standardized guidelines to enhance scientific rigor and standardization of its application.
关键词
真实世界数据 /
真实世界证据 /
医保准入 /
药品综合价值评价
Key words
real-world data /
real-world evidence /
medical insurance admission /
comprehensive value assessment of drugs
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