Strategies for De-identification and Anonymization of Electronic Health Record Data for Use in Multicenter Research Studies

Current de-identification strategies have their limitations, and statistical learning-based systems have distinct advantages over other approaches for the de-identification of free text. True anonymization is challenging, and further work is needed in the areas of de-identification of datasets and protection of genetic information.