Recommendation-Based De-identification: A Practical Systems Approach towards De-identification of Unstructured Text in Healthcare

摘要

In healthcare, de-identification is fast becoming a service that is indispensable when medical data needs to be used for research and secondary use purposes. Currently, this process is done either manually, by human agent, or by an automated software algorithm. Both approaches have shortcomings. Here, we introduce a framework for enhancing the outcome of the current modes of executing a de-identification service. This paper presents the steps taken in conceiving and building a privacy framework and tool that improves the service of de-identification. Further, we test the usefulness and applicability of this system through a study with HIPAA-trained experts.