De-identification is the process of automatic removal of all Private Health Information (PHI) from medical records. The main focus in this active and important research area is on semi-structured records. This narrow focus has allowed the development of standard criteria that formally determines the boundaries of privacy and can be used for evaluations. However, medical records include, as well as semi-structured data from filling in forms, etc., free text in which identifiers are more difficult to detect. In this article we address the problem of de-identification within unstructured medical records. We show how through the following methods we are able to recognize, in some cases, identifiers that currently go undetected: (1) Parsing free-form medical text into typed logical relationships including assumptions for candidate identifiers. (2) A novel use of the state-of-the-art engines for processing English queries to the web. We present as well a formal definition of our approach within a rigorous logical system that supports the implementation of our ideas.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org