Cognitive biases have a complex and significant impact on the perception of examinations within diagnostic radiology, with the clear and present danger of diagnostic errors. The following are some of the more common cognitive biases that can affect day-to-day decision making 1.
Anchoring bias is the tendency for one to focus on salient evidence upon the initial stages of the diagnosis leading to the diagnosis. Anchoring bias can also be heuristic in nature.
Automation bias is the tendency for reporters using computer-aided decision support to over rely on the software for the diagnosis, and ignoring their own opinions 2.
Availability bias is the process in which one is to pass judgment more frequently if this information is readily available in the mind.
Having a predetermined diagnosis in mind, then looking for evidence that supports this predetermined idea. Alliterative errors 3, sometimes referred to as satisfaction of report errors, are caused by the tendency to overvalue previous reports, can be conceptualized as a type of confirmation bias.
Hindsight bias occurs, when the difficulty of making the correct diagnostic decision by prior imaging is retrospectively de-emphasized, after the diagnosis has been proven. It is also informally termed as the the “I knew it all along” or "retrospectoscope" bias 5.
Making a judgment on an aspect of an image that is based on one's own perception of what that represents. Representativeness bias as the description suggest can also be heuristic in nature.
Search satisfaction is the tendency to cease a search early due to early findings satisfying the reader. Satisfaction of search (SOS) errors have been reported to account for 22% of diagnostic errors 4.
Framing bias is in which the reader is influenced by the clinical question. For example, a well-written request form detailing the exact pathology expected, may influence the reader's decision.
A tendency to favor a less severe diagnosis based on empathy for a patient.
Zebra retreat bias
A reader will not make a rare diagnosis, which is otherwise supported by the available evidence due to a lack of confidence.
- 1. Bruno MA, Walker EA, Abujudeh HH. Understanding and Confronting Our Mistakes: The Epidemiology of Error in Radiology and Strategies for Error Reduction. (2015) Radiographics : a review publication of the Radiological Society of North America, Inc. 35 (6): 1668-76. doi:10.1148/rg.2015150023 - Pubmed
- 2. Goddard K, Roudsari A, Wyatt JC. Automation bias: a systematic review of frequency, effect mediators, and mitigators. (2012) Journal of the American Medical Informatics Association : JAMIA. 19 (1): 121-7. doi:10.1136/amiajnl-2011-000089 - Pubmed
- 3. Alliterative Errors. (2012) American Journal of Roentgenology. 174 (4): 925-31. doi:10.2214/ajr.174.4.1740925 - Pubmed
- 4. Young W. Kim, Liem T. Mansfield. Fool Me Twice: Delayed Diagnoses in Radiology With Emphasis on Perpetuated Errors. (2014) American Journal of Roentgenology. 202 (3): 465-70. doi:10.2214/AJR.13.11493 - Pubmed
- 5. Lindsay P. Busby, Jesse L. Courtier, Christine M. Glastonbury. Bias in Radiology: The How and Why of Misses and Misinterpretations. (2017) RadioGraphics. 38 (1): 236-247. doi:10.1148/rg.2018170107 - Pubmed
Related Radiopaedia articles
- clinical trials
- descriptive studies
- Bayes' theorem
- sensitivity and specificity
- positive predictive value (PPV)
- negative predictive value (NPV)
- likelihood ratio (LR)
- normal distribution
- type I error
- type II error
- confidence interval
- ROC curve
- retrospective studies
- prospective studies
- analyzes of variance
- nonparametric statistics
- cognitive bias in image perception