Proposal and Assessment of a De-Identification Strategy to Enhance Anonymity of the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) in a Public Cloud-Computing Environment: Anonymization of Medical Data Using Privacy Models.
Seung Ho JeonJeongEun SeoSukyoung KimJeong Moon LeeJong-Ho KimJang Wook SohnJongsub MoonHyung Joon JooPublished in: Journal of medical Internet research (2020)
Our proposed de-identification strategy effectively enhanced the privacy of the CDM database, thereby encouraging clinical research involving multiple centers.