Clinical and research organizations increasingly want to share patient data, and robust de-identification is crucial to meet legal obligations and or ethical reasons. This book, written by two leading experts in de-identification, explains how to adhere to regulations in a defensible way to protect sensitive patient data. Numerous case studies are included from settings that range from typical clinical treatment to disease registries. The metrics used to determine that reidentification is unlikely, and special cases such as continuously released data, will be covered. The authors finish with a discussion of the effects of de-identification on data quality and analysis.
