Understanding and confronting our mistakes: The epidemiology of error in radiology and strategies for error reduction

Michael A. Bruno, Eric A. Walker, Hani H. Abujudeh

Research output: Contribution to journalArticlepeer-review

354 Scopus citations

Abstract

Arriving at a medical diagnosis is a highly complex process that is extremely error prone. Missed or delayed diagnoses often lead to patient harm and missed opportunities for treatment. Since medical imaging is a major contributor to the overall diagnostic process, it is also a major potential source of diagnostic error. Although some diagnoses may be missed because of the technical or physical limitations of the imaging modality, including image resolution, intrinsic or extrinsic contrast, and signal-to-noise ratio, most missed radiologic diagnoses are attributable to image interpretation errors by radiologists. Radiologic interpretation cannot be mechanized or automated; it is a human enterprise based on complex psychophysiologic and cognitive processes and is itself subject to a wide variety of error types, including perceptual errors (those in which an important abnormality is simply not seen on the images) and cognitive errors (those in which the abnormality is visually detected but the meaning or importance of the finding is not correctly understood or appreciated). The overall prevalence of radiologists’ errors in practice does not appear to have changed since it was first estimated in the 1960s. The authors review the epidemiology of errors in diagnostic radiology, including a recently proposed taxonomy of radiologists’ errors, as well as research findings, in an attempt to elucidate possible underlying causes of these errors. The authors also propose strategies for error reduction in radiology. On the basis of current understanding, specific suggestions are offered as to how radiologists can improve their performance in practice.

Original languageEnglish (US)
Pages (from-to)1668-1676
Number of pages9
JournalRadiographics
Volume35
Issue number6
DOIs
StatePublished - Oct 2015

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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