Academic medical centers need to make sensitive data from electronic health records, payor claims, genomic pipelines, and other sources available for analytical and educational purposes while ensuring privacy and security. Although many studies have described warehouses for collecting biomedical data, few studies have described secure computing environments for analysis of sensitive data. This case report describes the Weill Cornell Medicine Data Core with respect to user access, data controls, hardware, software, audit, and financial considerations. In the 2.5 years since launch, the Data Core has supported more than 200 faculty, staff, and students across nearly 60 research and education projects. Other institutions may benefit from adopting elements of the approach, including tools available on Github, for balancing access with privacy and security.
Learning Objective 1: Understand process and technology required for faculty, staff, and students to access a secure computing environment for analysis of sensitive data
Peter Oxley, Weill Cornell Medicine
John Ruffing, Weill Cornell Medicine
Thomas Campion (Presenter)
Weill Cornell Medicine
Terrie Wheeler, Weill Cornell Medicine
Curtis Cole, Weill Cornell Medicine