Medicolegal considerations of radiology report writing in the new paradigm of artificial intelligence

Johnson, Robert; Mackenzie, Don

doi:10.1111/1754-9485.13126

Cited by 3 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Blind obedience bias or ‘learned helplessness’ might result from the use of AI when the radiologist does not sufficiently question the results of the AI product. Error from either overreliance on the AI interpretation or discounting the AI interpretation may result with an accompanying new medicolegal dimension 22 …”

Section: What Types Of Cognitive Bias Are There and What Can We Do To...mentioning

confidence: 99%

“…Error from either overreliance on the AI interpretation or discounting the AI interpretation may result with an accompanying new medicolegal dimension. 22 In the era of rising clinical reliance on imaging, increasingly sophisticated imaging diagnosis, long-term digital image storage, escalating patient expectations and medicolegal risks, radiologists need to be cognisant of diagnostic errors, their causes, impacts and mitigating strategies. The presence and frequency of these errors in the literature should be a welcome reminder for those involved in quality processes or clinical governance and relevant governing bodies involved in radiologist performance review or medical litigation that all diagnostic radiologists make errors and not infrequently.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Error and cognitive bias in diagnostic radiology

2021

View full text Add to dashboard Cite

Errors in diagnostic radiology are not infrequent. Patient harm related to these errors is however less common and may be avoided via various preventative mechanisms within the medical system including, but not limited to, multidisciplinary meetings, second opinions, subspecialty expertise and clinician experience. Failure at a number of points in the system is often required to result in patient harm. Radiologists, and in particular departmental leaders, should proactively address the known underlying root causes of diagnostic errors and cognitive biases, ensure systems are in place to promptly discover and control unmitigated root causes as they arise and ensure an unbiased ‘blameless’ or ‘just’ culture of error investigation and proces sing including the implementation of non‐punitive peer feedback and peer learning. This article provides an overview of errors in diagnostic radiology including the causes and potential ramifications and how we might reduce their frequency and impact.

show abstract

Section: What Types Of Cognitive Bias Are There and What Can We Do To...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%