A quantitative and qualitative assessment of differential privacy's ability to support collaborative research using a real-world data analysis
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View abstract on PubMed
Summary
This summary is machine-generated.Differential privacy (DP) can protect patient data in collaborative research. Aggregating data with DP mitigated accuracy loss, showing promise for analyzing cancer diagnoses during the COVID-19 pandemic.
Area Of Science
- Health Informatics
- Medical Data Privacy
- Epidemiology
Background
- Sharing clinical data for collaborative research while preserving privacy is challenging.
- Differential privacy (DP) offers a method to protect sensitive information by adding noise to data.
- The utility of DP in analyzing real-world health data, such as cancer diagnoses, requires further assessment.
Purpose Of The Study
- To evaluate the utility of differentially private data for analyzing associations between COVID-19 and new cancer diagnoses (NCCs).
- To assess how different aggregation levels (1-week vs. 4-week) impact data utility in DP analyses.
- To explore potential enhancements for DP platforms in healthcare research.
Main Methods
- Extracted adult cancer diagnosis data (2019-2021) from a multi-hospital system.
- Queried original and differentially private (DP) datasets aggregated at 1-week and 4-week intervals.
- Performed regression analyses to examine associations between COVID-19 rates and changes in NCCs.
Main Results
- New cancer diagnoses (NCCs) decreased in 2020 and rebounded in 2021, a pattern reflected in the 4-week DP dataset but not the 1-week.
- DP analyses yielded wider confidence intervals compared to original data, with 4-week aggregation showing narrower intervals than 1-week.
- Significant associations found in original data were not detected in DP datasets, indicating a trade-off between privacy and analytic accuracy.
Conclusions
- Differential privacy reduces analytic accuracy but aggregation can mitigate this tradeoff.
- DP platforms can be enhanced to better support privacy-preserving, collaborative healthcare research.
- Further development of DP tools is crucial for enabling robust, cross-institutional medical studies.
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