Assessing Legal and Ethical Considerations for Processing Digital Medical Data in China: Framework, Issues, and Policy Recommendations

The processing of digital medical data (DMD) raises significant legal and ethical challenges. The rapid development of artificial Intelligence (AI) has tremendously influenced the processing of DMD. However, AI may also give rise to concerns about patient privacy breaches and data security risks. China emphasizes the legal and ethical considerations for processing DMD. In this article, we focus upon the parameters of DMD in the context of China’s legal framework and identify related applications of DMD. We explore the legal issues involving processing DMD in China: (1) individual control right/informed consent, (2) institutional obligations, (3) security impact assessment, and (4) secondary use compliance. We also find ethical issues involving processing DMD in China, involving (1) group bias and other data flaws and (2) privacy risks. Building on the above analysis, we propose legal and ethical “toolboxes” for regulating processing DMD in China. In the legal toolbox, there are four tools, including (1) optimizing individual permit and authorization, (2) creating three types of obligations, (3) promoting responsible and explainable security impact assessment, and (4) identifying public interest standards. In the ethical toolbox, there are two tools, including (1) paying particular attention to handling specific groups’ DMD and (2) enhancing accountability of handling DMD.

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Publication Details

Journal
Biotechnology Law Report
Published
2026-03-16
DOI
https://doi.org/10.1177/0730031x261430528
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Assessing Legal and Ethical Considerations for Processing Digital Medical Data in China: Framework, Issues, and Policy Recommendations

Q. L. Li, Xinxi Cao, James G. Stevenson, Jie Wang
Biotechnology Law Report
Artificial Intelligence in Healthcare and Education
article

Assessing Legal and Ethical Considerations for Processing Digital Medical Data in China: Framework, Issues, and Policy Recommendations

Q. L. Li, Xinxi Cao, James G. Stevenson, Jie Wang
article en

Abstract

The processing of digital medical data (DMD) raises significant legal and ethical challenges. The rapid development of artificial Intelligence (AI) has tremendously influenced the processing of DMD. However, AI may also give rise to concerns about patient privacy breaches and data security risks. China emphasizes the legal and ethical considerations for processing DMD. In this article, we focus upon the parameters of DMD in the context of China’s legal framework and identify related applications of DMD. We explore the legal issues involving processing DMD in China: (1) individual control right/informed consent, (2) institutional obligations, (3) security impact assessment, and (4) secondary use compliance. We also find ethical issues involving processing DMD in China, involving (1) group bias and other data flaws and (2) privacy risks. Building on the above analysis, we propose legal and ethical “toolboxes” for regulating processing DMD in China. In the legal toolbox, there are four tools, including (1) optimizing individual permit and authorization, (2) creating three types of obligations, (3) promoting responsible and explainable security impact assessment, and (4) identifying public interest standards. In the ethical toolbox, there are two tools, including (1) paying particular attention to handling specific groups’ DMD and (2) enhancing accountability of handling DMD.

Biotechnology Law Report
Stevenson University (US), Nanjing Normal University (CN), East China University of Political Science and Law (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 21%
Artificial Intelligence in Healthcare and Education
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Assessing Legal and Ethical Considerations for Processing Digital Medical Data in China: Framework, Issues, and Policy Recommendations — Q. L. Li, Xinxi Cao, et al. · Biotechnology Law Report (2026) | TGRS Research Map | TGRS