Reducing Errors Resulting From Commonly Missed Chest Radiography Findings.

Journal: Chest
Published Date:

Abstract

Chest radiography (CXR), the most frequently performed imaging examination, is vulnerable to interpretation errors resulting from commonly missed findings. Methods to reduce these errors are presented. A practical approach using a systematic and comprehensive visual search strategy is described. The use of a checklist for quality control in the interpretation of CXR images is proposed to avoid overlooking commonly missed findings of clinical importance. Artificial intelligence is among the emerging and promising methods to enhance detection of CXR abnormalities. Despite their potential adverse consequences, errors offer opportunities for continued education and quality improvements in patient care, if managed within a just, supportive culture.

Authors

  • Warren B Gefter
    Department of Radiology, University of Pennsylvania Perelman School of Medicine.
  • Hiroto Hatabu
    Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.