The quality evaluation of Chinas digital health policy based on PMC index model

Corresponding author: Liuzhiyong, zhiyongliu@hust.edu.cn

DOI: 10.12201/bmr.202411.00008

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  Abstract: Objective:To quantitatively evaluate Chinas digital health policies since the new healthcare reform, identify shortcomings in existing policies, and provide recommendations for future policy formulation and optimization. Methods:Employing ROSTCM6 software, we conducted text mining analysis on 130 national-level digital health policies. Based on the findings, we constructed a PMC Index Model evaluation system comprising 9 primary variables and 42 secondary variables. From these policies, 20 representative texts were selected for in-depth quantitative analysis. Results:The average PMC score of the 20 policies analyzed was 5.47, indicating overall excellence. One policy achieved the perfect standard, 12 were rated as excellent, and 7 fell within the acceptable range. Notably, no policies were classified as inadequate. Conclusion:While Chinas digital health policies demonstrate considerable success, there are opportunities for improvement. It is crucial to fortify the temporal effectiveness of policies and implement systems for continuously monitoring the dynamic shifts within the policy environment. Furthermore, clarifying the roles of various policy actors and establishing a diversified collaborative governance mechanism are essential to ensuring effective policy implementation. To facilitate the profound integration of digital technologies in the healthcare sector, the incorporation of economic incentives is vital. Additionally, maintaining a balance in policy formulations is paramount to promoting the sustainable growth of the digital health industry.

  Key words: Digital health; Policy evaluation; Text mining; PMC index model

  Submit time: 7 November 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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