Health technology assessment and medical insurance access for rare disease drugs in China: A policy review with quantitative insights from publicly available data

中国罕见病药物的卫生技术评估和医保覆盖:基于公开数据的定量分析政策回顾

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Abstract

To ascertain the status and propose optimization strategies for rare disease drugs (RDDs) value assessment in the scenario of the National Reimbursement Drug List (NRDL) dynamic adjustment in China, we conducted a narrative policy review that synthesized published literature and policy documents, supplemented by a secondary descriptive statistical analysis of publicly available 2022-2024 year NRDL negotiation data to contextualize recent reimbursement practices for rare disease drugs in China. This study found that value assessment of RDDs largely aligned with the traditional framework, encompassing five key dimensions: safety, efficacy, economic evaluation, innovation, and equity. Considering disease severity and the competitive landscape, innovative RDDs tend to receive higher clinical value ratings, higher willingness-to-pay thresholds, and broader policy support across the healthcare system. Between 2022 and 2024, a total of 60 RDDs applied for NRDL inclusion, with 43% successfully reimbursed. Most applicants were either original research drugs already approved overseas or modified new drugs launched domestically and abroad. Notably, 42% of the drugs had achieved global first launches before 2015, thereby accumulating extensive clinical evidence, and 58% submitted randomized controlled trial (RCT) data. The proportion of drugs supported by RCT evidence in the reimbursed group was significantly higher than the figure in the non-reimbursed group, whereas the proportion of drugs with pediatric indications were relatively lower in the reimbursed group. No significant differences were observed in other value assessment dimensions between successful and unsuccessful applicants. It is recommended that China develop detailed health technology assessment (HTA) guidelines and real-world evidence (RWE) guidance tailored for RDDs, facilitating the generation of high-quality evidence and decreasing decision-making risks associated with the value assessment of innovative RDDs.

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