A De-identification Method for Bilingual Clinical Texts of Various Note Types
Journal of Korean Medical Science
;
: 7-15, 2015.
Artigo
em Inglês
| WPRIM
| ID: wpr-166138
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.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Projetos de Pesquisa
/
Algoritmos
/
Processamento de Linguagem Natural
/
Multilinguismo
/
Registros de Saúde Pessoal
/
Registros Eletrônicos de Saúde
/
Anonimização de Dados
Tipo de estudo:
Estudo diagnóstico
/
Estudo prognóstico
Limite:
Humanos
Idioma:
Inglês
Revista:
Journal of Korean Medical Science
Ano de publicação:
2015
Tipo de documento:
Artigo
Similares
MEDLINE
...
LILACS
LIS