Recommendations for improving national clinical datasets for health equity research. (3rd September 2020)

• Record Type: Journal Article
• Authors: Block, Rebecca G; Puro, Jon; Cottrell, Erika; Lunn, Mitchell R; Dunne, M J; Quiñones, Ana R; Chung, Bowen; Pinnock, William; Reid, Georgia M; Heintzman, John
• Is Part Of: Journal of the American Medical Informatics Association. Volume 27:Number 11(2020)
• Page Start: 1802
• Page End: 1807
• Publication Date: 2020-09-03
• Subjects: healthcare disparities -- health equity -- data science -- data warehousing -- electronic health records -- clinical research; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocaa144
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: 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.