DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text

被引：35

作者：

Menger, Vincent ^{[1
]}

Scheepers, Floor ^{[2
]}

van Wijk, Lisette Maria ^{[1
]}

Spruit, Marco ^{[1
]}

机构：

[1] Univ Utrecht, Dept Informat & Comp Sci, POB 80089, NL-3508 TB Utrecht, Netherlands

[2] Univ Med Ctr Utrecht, Dept Psychiat, POB 85500, NL-3508 GA Utrecht, Netherlands

来源：

TELEMATICS AND INFORMATICS | 2018年 / 35卷 / 04期

关键词：

De-identification; Dutch medical text; Pattern matching; Protected Health Information; Patient privacy; HEALTH INFORMATION; RECORDS; IMPACT;

D O I：

10.1016/j.tele.2017.08.002

中图分类号：

G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];

学科分类号：

1205 ; 120501 ;

摘要：

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 F-1-score of 0.862. For person names, a recall of 0.964 was achieved, while no names of patients were missed.

引用

页码：727 / 736

页数：10

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