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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 1 of 1 Research Studies DisplayedBrown W, Balyan R, Karter AJ
Challenges and solutions to employing natural language processing and machine learning to measure patients' health literacy and physician writing complexity: the ECLIPPSE study.
In the National Library of Medicine-funded ECLIPPSE Project (Employing Computational Linguistics to Improve Patient-Provider Secure Emails exchange), the researchers attempted to create novel, valid, and scalable measures of both patients' health literacy (HL) and physicians' linguistic complexity by employing natural language processing techniques and machine learning. They identified 23 challenges and associated approaches that emerged from three overarching process domains. They suggested that investigators undertaking similar research in HL or using computational linguistic methods to assess patient-clinician exchange may find their solutions helpful when designing and executing health communications research.
Citation: Brown W, Balyan R, Karter AJ .
Challenges and solutions to employing natural language processing and machine learning to measure patients' health literacy and physician writing complexity: the ECLIPPSE study.
AHRQ-funded; HS026383..
Keywords: Health Literacy, Electronic Health Records (EHRs), Health Information Technology (HIT), Communication, Clinician-Patient Communication