Identifying Patients with Significant Problems Related to Social Determinants of Health with Natural Language Processing.

Journal: Studies in health technology and informatics
Published Date:

Abstract

Social and behavioral factors influence health but are infrequently recorded in electronic health records (EHRs). Here, we demonstrate that psychosocial vital signs can be extracted from EHR data. We processed structured and unstructured EHR data using expert-driven queries and Natural Language Processing (NLP), validating results through structured annotation. We found that although these vital signs are present in EHRs, with 681 structured entries identified for psychosocial concepts, NLP identified a nearly 90-fold increase in patients.

Authors

  • David Dorr
    Oregon Health & Science University, Portland, OR, USA.
  • Cosmin A Bejan
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.
  • Christie Pizzimenti
    Oregon Health & Science University, Portland, OR, USA.
  • Sumeet Singh
    Oregon Health & Science University, Portland, OR, USA.
  • Matt Storer
    Oregon Health & Science University, Portland, OR, USA.
  • Ana Quinones
    Oregon Health & Science University, Portland, OR, USA.