Underserved populations with missing race ethnicity data differ significantly from those with structured race/ethnicity documentation.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 31329882

Abstract

OBJECTIVE: We aimed to address deficiencies in structured electronic health record (EHR) data for race and ethnicity by identifying black and Hispanic patients from unstructured clinical notes and assessing differences between patients with or without structured race/ethnicity data.

Authors

  • Evan T Sholle
    Information Technologies and Services Department, Weill Cornell Medicine, New York, NY.
  • Laura C Pinheiro
    Department of Medicine, Weill Cornell Medicine, New York, New York, USA.
  • Prakash Adekkanattu
    Information Technologies and Services.
  • Marcos A Davila
    Information Technologies & Services Department, Weill Cornell Medicine, New York, New York, USA.
  • Stephen B Johnson
    Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY.
  • Jyotishman Pathak
    Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • Sanjai Sinha
    Department of Medicine, Weill Cornell Medicine, New York, New York, USA.
  • Cassidie Li
    Department of Medicine, Weill Cornell Medicine, New York, New York, USA.
  • Stasi A Lubansky
    Department of Medicine, Weill Cornell Medicine, New York, New York, USA.
  • Monika M Safford
    Department of Medicine, Weill Cornell Medicine, New York, New York, USA.
  • Thomas R Campion
    Information Technologies and Services Department, Weill Cornell Medicine, New York, NY.

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