Development of a Portable Tool to Identify Patients With Atrial Fibrillation Using Clinical Notes From the Electronic Medical Record.

Journal: Circulation. Cardiovascular quality and outcomes
PMID:

Abstract

BACKGROUND: The electronic medical record contains a wealth of information buried in free text. We created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone.

Authors

  • Rashmee U Shah
    Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City.
  • R Kannan Mutharasan
    Division of Cardiology, Department of Medicine (R.K.M., F.S.A., H.C.G.), Northwestern University Feinberg School of Medicine, Chicago, IL.
  • Faraz S Ahmad
    Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
  • Anna G Rosenblatt
    Division of Cardiology (A.G.R.), The University of Texas Southwestern Medical Center, Dallas.
  • Hawkins C Gay
    Division of Cardiology, Department of Medicine (R.K.M., F.S.A., H.C.G.), Northwestern University Feinberg School of Medicine, Chicago, IL.
  • Benjamin A Steinberg
    School of Medicine, University of Utah, SLC, UT, USA.
  • Mark Yandell
    Eccles Institute of Human Genetics (M.Y.), University of Utah, Salt Lake City.
  • Martin Tristani-Firouzi
    Division of Pediatric Cardiology (M.T.-F.), University of Utah School of Medicine, Salt Lake City.
  • Jake Klewer
    Department of Internal Medicine (J.K.), University of Utah School of Medicine, Salt Lake City.
  • Rebeka Mukherjee
    Division of Cardiovascular Medicine, Department of Internal Medicine (R.U.S., B.A.S., R.M.), University of Utah School of Medicine, Salt Lake City.
  • Donald M Lloyd-Jones
    Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.