Recommendations for improving national clinical datasets for health equity research

Rebecca G. Block, Jon Puro, Erika Cottrell, Mitchell R. Lunn, M. J. Dunne, Ana R. Quiñones, Bowen Chung, William Pinnock, Georgia M. Reid, John Heintzman

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1802-1807
Number of pages6
JournalJournal of the American Medical Informatics Association
Issue number11
StatePublished - Nov 1 2020


  • clinical research
  • data science
  • data warehousing
  • electronic health records
  • health equity
  • healthcare disparities

ASJC Scopus subject areas

  • Health Informatics


Dive into the research topics of 'Recommendations for improving national clinical datasets for health equity research'. Together they form a unique fingerprint.

Cite this