Estimating the re-identification risk of clinical data sets

2012102 citationsJournal Articlegold Open Access

Authors

Fida K. Dankar · Children's Hospital of Eastern Ontario

Khaled El Emam · Children's Hospital of Eastern Ontario

Angelica Neisa · Children's Hospital of Eastern Ontario

Tyson Roffey · Children's Hospital of Eastern Ontario

Abstract

This study identified an accurate decision rule that can be used by health privacy researchers and disclosure control professionals to estimate uniqueness in clinical data sets. The decision rule provides a reliable way to measure re-identification risk.

Topics & Keywords

Privacy-Preserving Technologies in Data Ethics in Clinical Research Patient Dignity and Privacy

UN Sustainable Development Goals

Peace, Justice and strong institutions

Publication Details

Published in: BMC Medical Informatics and Decision Making

Volume 12, Issue 1, pp. 66-66

DOI: 10.1186/1472-6947-12-66

Field-Weighted Citation Impact: 6.28