Automatic Clinical Text De-Identification: Is It Worth It, and Could It Work for Me?

and Objective The increased use and adoption of Electronic Health Records, and parallel growth in patient data available for secondary use by clinicians, researchers, and operational purposes, all cause patient confidentiality protection to become an increasingly more important requirement and expectation. The laws protecting patient confidentiality typically require the informed consent of the patient to use data for research purposes, a requirement that can be waived if the data are deidentified. Several methods to automatically remove identifying information from clinical text have been tested experimentally over the last 10 years, guided by the HIPAA “Safe Harbor” methodology. This panel will focus on the issues related with the automatic de-identification of clinical text. It will include an overview of the domain, a demonstration of good examples of such applications in English and in Swedish with their main authors sharing development and adaptation experiences, and a discussion of the HIPAA “Safe Harbor” deidentification quality and the risk for re-identification of deidentified data. The difficulties and issues related to this task will be debated, as well as the main methods used and the performance and adaptability of these methods.