Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.

Journal: Journal of the American College of Radiology : JACR
Published Date: Jun 21, 2019

Abstract

OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary embolism to referring physicians is essential for patient safety. The definitive communication is the radiology free-text report. Quality assurance initiatives require that institutions audit these communications, a time-intensive manual task. We propose using a rule-based natural language processing system to improve the process for auditing critical findings communications.

Authors

  • Marta E Heilbrun
    Department of Radiology and imaging Sciences, Emory University School of Medicine, Atlanta, Georgia. Electronic address: marta.heilbrun@emory.edu.
  • Brian E Chapman
    University of Utah, Department of Radiology, 729 Arapeen Drive, Salt Lake City, UT 84108, United States. Electronic address: brian.chapman@utah.edu.
  • Evan Narasimhan
    Department of Diagnostic Radiology, Oregon Health and Science University, Portland, Oregon.
  • Neel Patel
    Department of Diagnostic Radiology, Oregon Health and Science University, Portland, Oregon.
  • Danielle Mowery
    Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Salt Lake City, 84108 UT United States.

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