This paper is in the following e-collection/theme issue:

Ethics, Privacy, and Legal Issues (458) Clinical Informatics (919) Secondary Use of Clinical Data for Research and Surveillance (326)

Published on in Vol 22, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19597, first published .
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

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

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

Authors of this article:

Seungho Jeon1 Author Orcid Image ;   Jeongeun Seo1 Author Orcid Image ;   Sukyoung Kim1 Author Orcid Image ;   Jeongmoon Lee2 Author Orcid Image ;   Jong-Ho Kim3 Author Orcid Image ;   Jang Wook Sohn4 Author Orcid Image ;   Jongsub Moon1 Author Orcid Image ;   Hyung Joon Joo5 Author Orcid Image
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