Implementing Data Governance with Multi-Modal Privacy-Preserving Record Linkages between Restricted and Public Open Enclaves
Data centralization is increasingly non-viable in the changing landscape of data privacy and data governance. New models of data sharing are needed, in particular when privacy-preserving record linkages (PPRL) are being used to connect data within restricted data enclaves and public open enclaves. We share a privacy-preserving data-sharing infrastructure that employs a linkage honest broker implementation of PPRL connecting structured electronic health record data between the National Center for Advancing Translational Science (NCATS) National Clinical Cohort Collaborative (N3C), a restricted data enclave, with the National Cancer Institute (NCI) Cancer Imaging Archive (TCIA), a public open enclave. In particular we will address: Data governance models needed when linking data from restricted vs. public enclaves Specific privacy-preserving consideration when linking to imaging data which contain specific structured data and imaging considerations Privacy-preserving data aggregation when combining multi-modal data from restricted data enclaves with publicly discoverable imaging data
Authors
- Ahmad Baghal (ORCID: https://orcid.org/0000-0003-0389-0021)
- Richard A. Moffitt (ORCID: https://orcid.org/0000-0003-2723-5902)
- Kenneth Gersing (ORCID: https://orcid.org/0000-0003-3897-3409)
- Shaun J. Grannis (ORCID: https://orcid.org/0000-0002-8093-6639)
- Sam Michael (ORCID: https://orcid.org/0000-0002-1070-6563)
- Fred Prior (ORCID: https://orcid.org/0000-0002-6314-5683)
- Jasmin Phua (ORCID: https://orcid.org/0000-0001-6002-044X)
- Joel Saltz (ORCID: https://orcid.org/0000-0002-3451-2165)
- Andrew T. Girvin (ORCID: https://orcid.org/0000-0002-2031-9209)
- Sara Rogovin
- Ben Amor
Institutions
- National Institutes of Health (US)
- Regenstrief Institute (US)
- Emory University (US)
- DATADVANCE (France) (FR)
- Stony Brook University (US)
- University of Arkansas for Medical Sciences (US)
Publication Details
- Journal
- International Journal for Population Data Science
- Published
- 2024-09-10
- DOI
- https://doi.org/10.23889/ijpds.v9i5.2898
- Citations
- 1
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.49