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

BACKGROUND: De-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, has been gaining atten...

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Detalles Bibliográficos
Autores principales: Jeon, Seungho, Seo, Jeongeun, Kim, Sukyoung, Lee, Jeongmoon, Kim, Jong-Ho, Sohn, Jang Wook, Moon, Jongsub, Joo, Hyung Joon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728527/
https://www.ncbi.nlm.nih.gov/pubmed/33177037
http://dx.doi.org/10.2196/19597

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728527/
https://www.ncbi.nlm.nih.gov/pubmed/33177037
http://dx.doi.org/10.2196/19597

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