ENIntractable & Rare Diseases Research | Evaluating the Implementation Effectiveness of China's Rare Disease Policies Based on the PMC Index Model
Date: March 03, 2026
Classification: Frontiers
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This study employs the PMC index model and text mining methods to systematically evaluate national and local rare disease policy documents in China from 2016 to 2025, revealing structural characteristics and consistency levels of the policy system, providing empirical evidence for optimizing rare disease governance.
Literature Overview
The article 'How to evaluate rare disease policy effectiveness based on policy modeling consistency (PMC) index model: A quantitative assessment of policy implementation in China,' published in the journal Intractable & Rare Diseases Research, reviews and summarizes the systematic evaluation of national and local rare disease policy texts in China between 2016 and 2025. Based on the Policy Modeling Consistency (PMC) index model and combined with text mining techniques, the study analyzes high-frequency keywords and semantic networks from 32 policy documents, constructing a quantitative evaluation system comprising nine primary variables and 32 secondary variables. It visualizes and categorizes the structural integrity, implementation effectiveness, and regional disparities of policies. Results show that the average PMC index for national-level policies is 5.31 and 4.94 for local-level policies, both falling within the 'Excellent–Acceptable' range, indicating that China's rare disease policy system has established a solid institutional foundation. However, shortcomings remain in incentive mechanisms, patient support, and social integration. The study further recommends strengthening coordination between national and local legislation, establishing a national information platform and special funds, and promoting a full-chain policy system. This work provides a quantitative tool and empirical support for policy optimization and offers international audiences insight into China's rare disease governance trajectory.Background Knowledge
Rare diseases are a group of disorders with extremely low prevalence, affecting small patient populations but often chronic, severe, or life-threatening. Over 10,000 rare diseases have been identified globally, impacting more than 300 million people. Due to small patient numbers and high R&D costs, rare disease treatments (orphan drugs) frequently face market failure, leading to difficulties in diagnosis, treatment, and high medication costs. Countries have established differentiated policy frameworks: the U.S. provides tax incentives, research funding, and market exclusivity through the Orphan Drug Act; the EU has established cross-border collaboration mechanisms for unified approval and保障 systems; Japan and South Korea enhance accessibility through disease catalog recognition, research funding, and health insurance coverage. Since releasing the first Rare Disease Catalog (121 diseases) in 2018, China has gradually built a policy system centered on catalogs, drugs, diagnosis, and保障, expanding to 207 diseases with the second edition released in 2023. However, existing research primarily focuses on policy content, international comparisons, or regional case studies, lacking systematic and standardized quantitative evaluation tools. The Policy Modeling Consistency (PMC) index model, based on the Omnia Mobilis theoretical framework, enables multi-dimensional quantitative analysis of policy texts, measuring structural integrity and implementation potential. While applied in health policy evaluation, this method is used here for the first time in the field of rare diseases. This study fills that gap by constructing a PMC evaluation system tailored to the Chinese context, revealing strengths and weaknesses in policy design and providing scientific evidence for improving institutional保障 and promoting equitable access.
Research Methods and Experiments
The study systematically analyzes 19 national-level and 13 local-level rare disease-related policy documents issued between January 1, 2016, and June 1, 2025, using a combination of the PMC index model and text mining. Policy texts were collected from official websites of the State Council, ministries, local governments, and authoritative platforms such as the Peking University Law Database. Inclusion criteria include: issued by national or provincial government bodies; document type being planning, opinions, or notifications; and direct relevance to rare diseases. Non-official documents such as announcements, replies, or speeches were excluded. Text analysis was conducted using ROSTCM 6.0 software to extract high-frequency words and semantic networks, identifying policy focus and thematic evolution. The PMC evaluation system includes nine primary variables (e.g., issuing agency, policy nature, drug保障, results orientation, incentives, patient support, technological innovation, policy function, social support) and 32 secondary variables, established through expert consultation and literature comparison. Each secondary variable is scored 0 or 1 based on presence, and a weighted calculation yields the PMC index, categorized into four levels: 'Perfect' (7–9), 'Excellent' (5–6.99), 'Acceptable' (3–4.99), and 'Poor' (0–2.99). Radar and surface charts are used for visualization to compare national and local policy performance across dimensions.Key Conclusions and Findings
Research Significance and Outlook
This study marks the first application of the PMC index model to evaluate rare disease policies in China, offering a quantifiable analytical framework that overcomes the limitations of traditional qualitative research, enhancing the scientific rigor and comparability of policy evaluation. High-frequency word and semantic network analyses reveal that policy attention is concentrated on diagnosis and treatment systems, drug development, and clinical practice, while issues such as economic burden and social保障receive insufficient attention, guiding future policy adjustments. The findings emphasize that although China has established an initial policy framework, further strengthening is needed in incentive mechanisms and social support, particularly in areas such as orphan drug R&D incentives, long-term patient care, and anti-discrimination protections.
Future policies should promote specialized legislation such as a Rare Disease Act, incorporating patient rights, R&D incentives, special funds, and inter-agency collaboration into a legal framework to enhance policy stability and enforceability. A unified national rare disease collaboration network should be established to promote sharing of clinical resources, research platforms, and data, reducing regional disparities. Local policy pilots should be encouraged to accumulate experience and feed lessons back to the national level, forming a virtuous cycle of 'legislation–implementation–evaluation–revision.' Additionally, public awareness and social participation should be strengthened to increase pharmaceutical investment and build a multi-stakeholder governance ecosystem for rare diseases.
Conclusion
Basing on the PMC index model and text mining techniques, this study systematically evaluates national and local rare disease policy documents in China from 2016 to 2025, revealing the overall structural characteristics and implementation consistency of the policy system. Results show average PMC indices of 5.31 at the national level and 4.94 at the local level, both within the 'Excellent–Acceptable' range, indicating that China's rare disease policies have established a solid institutional foundation and strong strategic planning capabilities. Policies perform well in top-level design, supervision, execution, and goal setting, but remain weak in R&D incentives, patient support, and social integration. National policies focus on institutional building, while local policies emphasize healthcare assistance and保障innovation, though significant regional disparities exist—policies in economically developed regions are more systematic, while those in underdeveloped areas face limited保障capacity. The study recommends advancing national legislation, establishing a rare disease information platform and special fund, strengthening central-local coordination, and building a full-chain policy system covering R&D, approval, insurance, and patient support. This research provides a quantitative tool and empirical basis for optimizing rare disease governance and offers valuable insights for the international community to understand the evolution of China's policies. Future efforts should enhance dynamic evaluation and public engagement to promote a fairer, more sustainable rare disease保障mechanism.
