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.

Seungho Jeon JeongEun Seo Sukyoung Kim Jeong Moon Lee Jong-Ho Kim Jang Wook Sohn Jongsub Moon Hyung Joon Joo

Published 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.

Keyphrases

big data
healthcare
electronic health record
health information
artificial intelligence
machine learning
bioinformatics analysis
mental health
emergency department
data analysis
metabolic syndrome
insulin resistance