title: A De-identification method for bilingual clinical texts of various note types.
abstract: De-identification of personal health information is essential in order not to require written patient informed consent. Previous de-identification methods were proposed using natural language processing technology in order to remove the identifiers in clinical narrative text, although these methods only focused on narrative text written in English. In this study, we propose a regular expression-based de-identification method used to address bilingual clinical records written in Korean and English. To develop and validate regular expression rules, we obtained training and validation datasets composed of 6,039 clinical notes of 20 types and 5,000 notes of 33 types, respectively. Fifteen regular expression rules were constructed using the development dataset and those rules achieved 99.87% precision and 96.25% recall for the validation dataset. Our de-identification method successfully removed the identifiers in diverse types of bilingual clinical narrative texts. This method will thus assist physicians to more easily perform retrospective research.
authors.affiliation: Department of Biomedical Informatics, Asan Medical Center, Seoul, Korea. ; Office of Clinical Research Information, Asan Medical Center, Seoul, Korea.
authors.forename: Soo-Yong
authors.identifier: 0000-0002-2410-6120
authors.initials: SY
authors.lastname: Shin
authors.affiliation: Office of Clinical Research Information, Asan Medical Center, Seoul, Korea.
authors.forename: Yu Rang
authors.identifier: 0000-0002-4210-2094
authors.initials: YR
authors.lastname: Park
authors.affiliation: Office of Clinical Research Information, Asan Medical Center, Seoul, Korea.
authors.forename: Yongdon
authors.identifier: 0000-0002-1144-9458
authors.initials: Y
authors.lastname: Shin
authors.affiliation: Office of Clinical Research Information, Asan Medical Center, Seoul, Korea.
authors.forename: Hyo Joung
authors.identifier: 0000-0003-4715-2901
authors.initials: HJ
authors.lastname: Choi
authors.affiliation: Office of Clinical Research Information, Asan Medical Center, Seoul, Korea.
authors.forename: Jihyun
authors.identifier: 0000-0002-1872-8708
authors.initials: J
authors.lastname: Park
authors.affiliation: Office of Clinical Research Information, Asan Medical Center, Seoul, Korea.
authors.forename: Yongman
authors.identifier: 0000-0002-9363-252X
authors.initials: Y
authors.lastname: Lyu
authors.affiliation: Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
authors.forename: Moo-Song
authors.identifier: 0000-0003-1085-9073
authors.initials: MS
authors.lastname: Lee
authors.affiliation: Office of Clinical Research Information, Asan Medical Center, Seoul, Korea. ; Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. ; Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
authors.forename: Chang-Min
authors.identifier: 0000-0002-2881-4669
authors.initials: CM
authors.lastname: Choi
authors.affiliation: Department of Biomedical Informatics, Asan Medical Center, Seoul, Korea. ; Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
authors.forename: Woo-Sung
authors.identifier: 0000-0002-1254-1264
authors.initials: WS
authors.lastname: Kim
authors.affiliation: Department of Biomedical Informatics, Asan Medical Center, Seoul, Korea. ; Office of Clinical Research Information, Asan Medical Center, Seoul, Korea. ; Department of Emergency Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. ; Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA.
authors.forename: Jae Ho
authors.identifier: 0000-0003-2619-1231
authors.initials: JH
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D000068240:Data Anonymization; D057286:Electronic Health Records; D055991:Health Records, Personal; D006801:Humans; D019303:Multilingualism; D009323:Natural Language Processing; D012107:Research Design
keywords: Anonymization; Bilingual Text; Clinical Text; De-identification; Medical Informatics; Patient Privacy; Text Mining