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Improving clinician interpretation of emergency skeletal radiographs
  1. David Metcalfe1,2,
  2. Sarim Ather3,
  3. Alex Novak2
  1. 1 Oxford Trauma and Emergency Care (OxTEC), University of Oxford, Oxford, UK
  2. 2 Emergency Medicine Research Oxford (EMROx), John Radcliffe Hospital, Oxford, UK
  3. 3 Department of Radiology, John Radcliffe Hospital, Oxford, UK
  1. Correspondence to Prof. David Metcalfe; david.metcalfe{at}ndorms.ox.ac.uk

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In this issue of the EMJ, Dann et al 1 report an online prospective study in which clinicians were asked to identify injuries in a series of 10 paediatric elbow radiographs.1 The participants were mostly doctors working within emergency medicine and 73% had over 6 years’ experience. However, on average, clinicians interpreted just over half of the radiographs correctly and only 3% of participants achieved a perfect score.

This level of underperformance is surprising, but there are reasons to suspect that the study could have underestimated the ability of clinicians to identify injuries in the ED. First, paediatric elbow radiographs are notoriously difficult to interpret due to a range of normal findings mimicking fractures that evolve until adulthood.2 It is likely that many clinicians seek a second opinion when reviewing paediatric elbow radiographs in clinical practice and abnormalities may also be highlighted in advance by radiographers. Second, clinicians typically have an opportunity to examine patients for themselves and may not be accustomed to interpreting radiographs in isolation. Finally, the participants were a self-selected group that might have disproportionately included those who …

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Footnotes

  • Handling editor Ellen J Weber

  • X @TraumaDataDoc, @AlexTNovak

  • Contributors DM drafted the commentary which was critically revised by SA and AN. All authors approved the final version. DM is the guarantor.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests DM was a member of the NHS Resolution working group on missed fractures. SA is the founder and CEO of RAIQC Ltd, which administers the Report and Image Quality Control (RAIQC) clinical simulation platform that mimics real-world practice to improve clinician interpretation of imaging modalities. DM, SA and AN are investigators in the NIHR-funded study FRACT-AI, which is evaluating the effectiveness of using AI to augment clinician interpretation of skeletal radiographs.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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