| Title: | An empirical assessment of differential privacy in real-world observational data: a case-control study of asthma exacerbation in UK Biobank linked with electronic health records |
| Journal: | Journal of the American Medical Informatics Association |
| Published: | 18 Jun 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40577098/ |
| DOI: | https://doi.org/10.1093/jamia/ocaf090 |
| URL: | https://academic.oup.com/jamia/advance-article-pdf/doi/10.1093/jamia/ocaf090/63520343/ocaf090.pdf |
Publication 16289
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Abstract
OBJECTIVES: Electronic health records (EHRs) provide substantial resources for observational studies, yet present significant challenges in safeguarding patient privacy while maintaining research quality. Differential privacy (DP) offers a quantifiable privacy guarantee; however, its impact on observational studies remains underexplored. We empirically evaluated the effects of DP across varying values of its privacy parameter, epsilon, on case-control analysis outcomes using EHR data. This study aims to inform DP parameter selection and examines the influence of study characteristics on differentially private observational studies.</p>
MATERIALS AND METHODS: We assessed the effects of DP on a case-control study of 1-year asthma exacerbations, including 22 165 participants with a history of asthma from UK Biobank linked to EHR data. Odds ratios (ORs) for sociodemographic factors and comorbidities were analyzed using adjusted and propensity score-matched models across epsilon values.</p>
RESULTS: DP influenced the magnitude, direction, and statistical significance of ORs, occasionally resembling patterns of misclassification, residual confounding, and false-positive bias. Rare and imbalanced covariates showed greater OR variability, especially in matched studies. Epsilons smaller than ln(2) led to noticeable OR fluctuations.</p>
DISCUSSION: The impact of DP on ORs and selection of an optimal epsilon depends on sample size, covariate prevalence, confounders, case-to-control ratios in propensity score matching, mitigation of random seed p-hacking, and trust models.</p>
CONCLUSION: The effects of DP on ORs are highly context-dependent. In this study, epsilon values below ln(2) led to unstable ORs across random seeds. Averaging results or using predetermined seeds may help reduce variability and mitigate p-hacking.</p>
16 Keywords
- Adult
- Aged
- Asthma
- Biological Specimen Banks
- Case-Control Studies
- Confidentiality
- Electronic Health Records
- Female
- Humans
- Male
- Middle Aged
- Observational Studies as Topic
- Odds Ratio
- Propensity Score
- UK Biobank
- United Kingdom
3 Authors
- Mehrdad A Mizani
- Aziz Sheikh
- Amitava Banerjee
1 Application
| Application ID | Title |
|---|---|
| 49708 | Analysing the effects of privacy protection methods on data utility and data research generalisability in observational studies: A case study in asthma |
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