Protecting patient privacy in tabular synthetic health data: a regulatory perspective.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 41315669.
- Also identified by DOI 10.1038/s41746-025-02112-0 and PMC identifier 12663144.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Synthetic tabular data generation (SDG) is increasingly important in healthcare research and innovation while preserving patients' privacy. However, ethical concerns remain, primarily over residual privacy vulnerability and insufficient oversight. This review analyzes the only published SDG regulatory guidelines to date, from United Kingdom, Singapore, and South Korea. All emphasize privacy, acknowledging synthetic data is not inherently free from disclosure risks. Thresholds for sufficiently low risk are yet to be determined.