Quantitative evaluation of traditional Chinese medicine registration management  policy texts based on the PMC index model

Abstract

Abstract:

To systematically and quantitatively evaluate China’s national-level traditional Chinese medicine (TCM) registration management policies, providing evidence for policy optimization. Eight core policy documents from 2008 to 2025 were selected. Text mining was conducted using ROSTCM 6.0 software to construct the Policy Management Capability (PMC) index model, which includes 9 primary and 31 secondary indicators. The PMC index for each policy was calculated, and a three-dimensional surface plot was generated for visualization. The overall average PMC score was 6.19, with the quality distribution exhibiting a “bottle-shaped” pattern. The “Drug Registration Management Measures” (2020) achieved the highest score of 7.50 (Excellent), while some technical guidance documents scored below 5.4 (Unsatisfactory). The policies generally performed well in terms of operability and content coverage but were deficient in policy evaluation, hierarchical structuring, and innovation incentives. The TCM registration management policies demonstrate a robust framework with imbalanced details. Dynamic evaluation and incentives for innovation need enhancement. Recommendations include systematic optimization of the system through improvements in post-market evaluation, enhanced incentive tools, and stronger policy coordination.

Key words:

"> traditional Chinese medicine registration management, PMC index model, policy evaluation, text mining, policy , quantification

Pan Chen, Shuling Wang.

Quantitative evaluation of traditional Chinese medicine registration management policy texts based on the PMC index model

[J]. Asian Journal of Traditional Medicines, 2026, 21(2): 100-113.

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Asian Journal
Of Traditional Medicines