The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Understanding and Confronting Our Mistakes: The Epidemiology of Error in Radiology and Strategies for Error Reduction
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.
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Cites
Mental contamination and mental correction: Unwanted influences on judgments and evaluations.
Wilson, T. D., & Brekke, N. (1994) · Psychological Bulletin · doi:10.1037/0033-2909.116.1.117 · Cited by 1,157 · cited 3×
“The idea of cognitive debiasing has existed for decades and was well described by Wilson and Brekke (25) in 1994 as a form of “mental correction.”
BackgroundInfluentialThe Checklist Manifesto: How to Get Things Right
Gawande, A. (2011) · Journal of Nursing Regulation · doi:10.1016/s2155-8256(15)30310-0 · Cited by 1,151
Overconfidence as a Cause of Diagnostic Error in Medicine
Berner, E. S., & Graber, M. L. (2008) · The American Journal of Medicine · doi:10.1016/j.amjmed.2008.01.001 · Cited by 1,034
Clinical cognition and diagnostic error: applications of a dual process model of reasoning
Croskerry, P. (2009) · Advances in Health Sciences Education · doi:10.1007/s10459-009-9182-2 · Cited by 494
Cognitive interventions to reduce diagnostic error: a narrative review
Graber, M. L., Kissam, S., Payne, V. L., Meyer, A. N. D., Sorensen, A., Lenfestey, N., Tant, E., Henriksen, K., LaBresh, K., & Singh, H. (2012) · BMJ Quality & Safety · doi:10.1136/bmjqs-2011-000149 · Cited by 449
Cognitive debiasing 2: impediments to and strategies for change
Croskerry, P., Singhal, G., & Mamede, S. (2013) · BMJ Quality & Safety · doi:10.1136/bmjqs-2012-001713 · Cited by 419
Current perspectives in medical image perception
Krupinski, E. A. (2010) · Attention, Perception & Psychophysics · doi:10.3758/app.72.5.1205 · Cited by 343
Miss Rate of Lung Cancer on the Chest Radiograph in Clinical Practice
Quekel, L. G. B. A., Kessels, A. G. H., Goei, R., & van Engelshoven, J. M. A. (1999) · Chest · doi:10.1378/chest.115.3.720 · Cited by 311
Computer aided detection (CAD): an overview
Castellino, R. A. (2005) · Cancer Imaging · doi:10.1102/1470-7330.2005.0018 · Cited by 284
Error in radiology: classification and lessons in 182 cases presented at a problem case conference.
Renfrew, D. L., Franken, E. A., Berbaum, K. S., Weigelt, F. H., & Abu-Yousef, M. M. (1992) · Radiology · doi:10.1148/radiology.183.1.1549661 · Cited by 267
Cited by
Lebovitz, S., Levina, N., & Lifshitz-Assaf, H. (2021) · MIS Quarterly · doi:10.25300/misq/2021/16564 · Cited by 49
Radiology report generation with a learned knowledge base and multi-modal alignment
Yang, S., Wu, X., Ge, S., Zheng, Z., Zhou, S. K., & Xiao, L. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102798 · Cited by 199
Rauschecker, A. M., Rudie, J. D., Xie, L., Wang, J., Duong, M. T., Botzolakis, E. J., Kovalovich, A. M., Egan, J., Cook, T. C., Bryan, R. N., et al. (2020) · Radiology · doi:10.1148/radiol.2020190283 · Cited by 148
Best practices in modified barium swallow studies
Martin-Harris, B., Canon, C. L., Bonilha, H. S., Murray, J., Davidson, K., & Lefton-Greif, M. A. (2020) · American Journal of Speech-Language Pathology · doi:10.1044/2020_ajslp-19-00189 · Cited by 129
Perceptual and interpretive error in diagnostic radiology—causes and potential solutions
Degnan, A. J., Ghobadi, E. H., Hardy, P., Krupinski, E., Scali, E. P., Stratchko, L., Ulano, A., Walker, E., Wasnik, A. P., & Auffermann, W. F. (2019) · Academic Radiology · doi:10.1016/j.acra.2018.11.006 · Cited by 121
Self-citation
Metadata
- Authors
- Bruno, M. A., Walker, E. A., & Abujudeh, H. H.
- Venue
- RadioGraphics
- Published
- 2015-10
- Volume
- 35
- Issue
- 6
- Pages
- 1668-1676
- ISSN
- 0271-5333 (ISSN-L)
- 1527-1323
- OpenAlex
- W2168199261
- Cited by
- 573
- References
- 28
- FWCI
- 14.29
- Type
- journal article
- Language
- en
- Open access
- closed
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