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

BackgroundDe-identifying personal information is critical when using personal health data for secondary research. The Observational Medical Outcomes Partnership Common Data Model (CDM), defined by the nonprofit organization Observational Health Data Sciences and Informatics,...

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Bibliographic Details
Main Authors: Jeon, Seungho, Seo, Jeongeun, Kim, Sukyoung, Lee, Jeongmoon, Kim, Jong-Ho, Sohn, Jang Wook, Moon, Jongsub, Joo, Hyung Joon
Format: Article
Language:English
Published: JMIR Publications 2020-11-01
Series:Journal of Medical Internet Research
Online Access:http://www.jmir.org/2020/11/e19597/

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http://www.jmir.org/2020/11/e19597/

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