DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text
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Publication date
2018-07
Authors
Menger, Vincent
Scheepers, Floor
van Wijk, Lisette Maria
Spruit, Marco R
Editors
Advisors
Supervisors
Document Type
Article
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License
taverne
Abstract
In order to use medical text for research purposes, it is necessary to de-identify the text for legal and privacy reasons. We report on a pattern matching method to automatically de-identify medical text written in Dutch, which requires a low amount of effort to be hand tailored. First, a selection of Protected Health Information (PHI) categories is determined in cooperation with medical staff. Then, we devise a method for de-identifying all information in one of these PHI categories, that relies on lookup tables, decision rules and fuzzy string matching. Our de-identification method DEDUCE is validated on a test corpus of 200 nursing notes and 200 treatment plans obtained from the University Medical Center Utrecht (UMCU) in the Netherlands, achieving a total micro-averaged precision of 0.814, a recall of 0.916 and a F1-score of 0.862. For person names, a recall of 0.964 was achieved, while no names of patients were missed.
Keywords
De-identification, Dutch medical text, Patient privacy, Pattern matching, Protected Health Information, Taverne, Communication, Computer Networks and Communications, Electrical and Electronic Engineering, Law
Citation
Menger, V, Scheepers, F, van Wijk, L M & Spruit, M R 2018, 'DEDUCE : A pattern matching method for automatic de-identification of Dutch medical text', Telematics and Informatics, vol. 35, no. 4, pp. 727-736. https://doi.org/10.1016/j.tele.2017.08.002