Considerations for Patient Privacy of Large Language Models in Health Care: Scoping Review
We propose comprehensive recommendations across 3 phases-study design, implementation, and reporting-to strengthen patient privacy protection and transparency in PHI-LLM. This study emphasizes the urgent need for the development of stricter regulatory frameworks and the adoption of advanced privacy protection technologies to effectively safeguard PHI. It is anticipated that future applications of LLMs in the health care field will achieve a balance between innovation and robust patient privacy protection, thereby enhancing ethical standards and scientific credibility.
Authors
- Hongcai Shang
- Dongdong Yu (ORCID: https://orcid.org/0000-0003-2759-7647)
- Xiaoying Zhong (ORCID: https://orcid.org/0000-0003-1861-4046)
- Liangzhen You (ORCID: https://orcid.org/0000-0001-7422-1680)
- Chen Zhao (ORCID: https://orcid.org/0000-0002-3911-1125)
- Shi-Jia Wang (ORCID: https://orcid.org/0009-0002-8054-9855)
- Siyi Li (ORCID: https://orcid.org/0009-0001-2649-9933)
- Long Ge (ORCID: https://orcid.org/0000-0002-3555-1107)
Institutions
- Guangzhou University of Chinese Medicine (CN)
- Beijing University of Chinese Medicine (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-11-21
- DOI
- https://doi.org/10.2196/76571
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96