Protected Health Information Recognition of Unstructured Code-Mixed Electronic Health Records in Taiwan

Author:

Lee You-Qian1,Wang Bo-Hong1,Su Chu-Hsien2,Chen Pei-Tsz3,Lin Wu-Qing1,Wu Chi-Shin2,Dai Hong-Jie145

Affiliation:

1. Intelligent System Lab, College of Electrical Engineering and Computer Science, Department of Electrical Engineering, National Kaohsiung University Science and Technology, Kaohsiung, Taiwan R.O.C.

2. Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan R.O.C.

3. Department of Chemical Engineering, Feng Chia University, Taichung, Taiwan R.O.C.

4. National Institute of Cancer Research, National Health Research Institutes, Tainan, Taiwan R.O.C.

5. School of Post-Baccalaureate Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan R.O.C.

Abstract

Electronic health records (EHRs) at medical institutions provide valuable sources for research in both clinical and biomedical domains. However, before such records can be used for research purposes, protected health information (PHI) mentioned in the unstructured text must be removed. In Taiwan’s EHR systems the unstructured EHR texts are usually represented in the mixing of English and Chinese languages, which brings challenges for de-identification. This paper presented the first study, to the best of our knowledge, of the construction of a code-mixed EHR de-identification corpus and the evaluation of different mature entity recognition methods applied for the code-mixed PHI recognition task.

Publisher

IOS Press

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