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Recommendations for improving national clinical datasets for health equity research
Author(s) -
Rebecca Block,
Jon Puro,
Erika Cottrell,
Mitchell R. Lunn,
Maryjane Dunne,
Ana Quiñones,
Bowen Chung,
William Pinnock,
Georgia M Reid,
John Heintzman
Publication year - 2020
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocaa144
Subject(s) - health equity , equity (law) , usability , health care , medline , health data , medicine , medical education , data science , political science , computer science , human–computer interaction , law
Health and healthcare disparities continue despite clinical, research, and policy efforts. Large clinical datasets may not contain data relevant to healthcare disparities and leveraging these for research may be crucial to improve health equity. The Health Disparities Collaborative Research Group was commissioned by the Patient-Centered Outcomes Research Institute to examine the data science needs for quality and complete data and provide recommendations for improving data science around health disparities. The group convened content experts, researchers, clinicians, and patients to produce these recommendations and suggestions for implementation. Our desire was to produce recommendations to improve the usability of healthcare datasets for health equity research. The recommendations are summarized in 3 primary domains: patient voice, accurate variables, and data linkage. The implementation of these recommendations in national datasets has the potential to accelerate health disparities research and promote efforts to reduce health inequities.

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