Handwork vs machine: a comparison of rheumatoid arthritis patient populations as identified from EHR free-text by diagnosis extraction through machine-learning or traditional criteria-based chart review
Published in Arthritis Res Ther, 2021
Electronic health records (EHRs) offer a wealth of observational data. Machine-learning (ML) methods are efficient at data extraction, capable of processing the information-rich free-text physician notes in EHRs. The clinical diagnosis contained therein represents physician expert opinion and is more consistently recorded than classification criteria components.OBJECTIVES: To investigate the overlap and differences between rheumatoid arthritis patients as identified either from EHR free-text through the extraction of the rheumatologist diagnosis using machine-learning (ML) or through manual chart-review applying the 1987 and 2010 RA classification criteria.
Recommended citation: Maarseveen TD, Maurits MP, Niemantsverdriet E, van der Helm-van Mil AHM, Huizinga TWJ, Knevel R. (2021) "Handwork vs machine: a comparison of rheumatoid arthritis patient populations as identified from EHR free-text by diagnosis extraction through machine-learning or traditional criteria-based chart review" Arthritis Res Ther. 2021 Jun 22;23(1):174. doi: 10.1186/s13075-021-02553-4.
Recommended citation: Maarseveen TD, Maurits MP, Niemantsverdriet E, van der Helm-van Mil AHM, Huizinga TWJ, Knevel R. (2021) "Handwork vs machine: a comparison of rheumatoid arthritis patient populations as identified from EHR free-text by diagnosis extraction through machine-learning or traditional criteria-based chart review" Arthritis Res Ther. 2021 Jun 22;23(1):174. doi: 10.1186/s13075-021-02553-4.
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