We created a software tool that accurately removes all patient identifying information from various kinds of clinical data documents, including laboratory and narrative reports.
We created the Medical De-identification System (MeDS), a software tool that de-identifies clinical documents, and performed 2 evaluations. Our first evaluation used 2,400 Health Level Seven (HL7) messages from 10 different HL7 message producers. After modifying the software based on the results of this first evaluation, we performed a second evaluation using 7,190 pathology report HL7 messages. We compared the results of MeDS de-identification process to a gold standard of human review to find identifying strings. For both evaluations, we calculated the number of successful scrubs, missed identifiers, and over-scrubs committed by MeDS and evaluated the readability and interpretability of the scrubbed messages.