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Improved Turnaround Times | Median time to first decision: 12 days

LetterLETTER

A Public Health Perspective on Radiologists’ Interpretation Volumes

Jeffrey P. Guenette, Geoffrey S. Young, Rajiv Gupta, Javier M. Romero and Raymond Y. Huang
American Journal of Neuroradiology June 2024, 45 (6) E10-E11; DOI: https://doi.org/10.3174/ajnr.A8240
Jeffrey P. Guenette
aDivision of NeuroradiologyBrigham and Women’s HospitalBoston, Massachusetts
bCenter for Evidence-Based ImagingBrigham and Women’s HospitalBoston, Massachusetts
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Geoffrey S. Young
cDivision of NeuroradiologyBrigham and Women’s HospitalBoston, Massachusetts
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Rajiv Gupta
cDivision of NeuroradiologyBrigham and Women’s HospitalBoston, Massachusetts
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Javier M. Romero
cDivision of NeuroradiologyBrigham and Women’s HospitalBoston, Massachusetts
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Raymond Y. Huang
fDivision of NeuroradiologyBrigham and Women’s HospitalBoston, Massachusetts
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In the recent AJNR study by Ivanovic et al,1 interpretation volume is associated with diagnostic error at the time of interpretation, presumably in the form of a missed diagnosis or misdiagnosis. The actual error rates may be even higher since RADPEER likely biases reviewers to save time and protect colleagues by minimizing discrepancy. While we support the goal to limit volumes, we note that suddenly limiting ourselves to 32 or 40 neuroradiology examinations per shift would rapidly lead to large queues of unread examinations and would inevitably delay many diagnoses. A delay in diagnosis is also a diagnostic error as defined by the National Academies. In England, delays in reporting have contributed to one-third of examined radiology systems failures.2

Also, we cannot estimate how volume limits would reduce error without knowing the degree to which the study model explains error. In our experience, regression models in radiology quality studies often explain only 10%–15% of the studied effect. We, thus, advocate for including the R2 value to help elucidate the potential impact of interventions on the studied outcome.

Furthermore, as illustrated by the cited airline and anesthesiology experiences, risk mitigation entails addressing many factors that contribute both directly and indirectly to error. For example, examination types are associated with radiologists’ recommendation rates,3 due to diagnostic uncertainty, and there is likely a similar association with error. The Ivanovic et a1l study did not address whether the small fraction of studied shifts with <26 examinations included a high proportion of high-certainty/low-error examination types. Additional unstudied factors that potentially contribute to or confound the error association are noninterpretative responsibilities,4 case complexity, and shift time of day.

Radiologists largely agree that higher interpretation volumes are psychologically unacceptable and unsustainable. Nevertheless, imaging volumes continue increasing, and our work is most valuable to patients and referring providers when performed promptly. Increasing the number of radiologists is virtually impossible in the short term given the 10-year American training pipeline and the barriers to hiring foreign-trained radiologists.5 Meanwhile, strategies to limit radiologists’ workloads and mitigate error should include the following: clinical trial–validated technologies, including artificial intelligence tools, to reduce ancillary and repetitive tasks and interruptions; reduction of clinically unnecessary imaging; examination scheduling triage based on urgency; and evidence-based guidelines that rank and reward quality and safety to counterbalance the incentive for workflows that maximize revenues and profits.

Footnotes

  • Disclosure forms provided by the authors are available with the full text and PDF of this article at www.ajnr.org.

References

  1. 1.↵
    1. Ivanovic V,
    2. Broadhead K,
    3. Chang YM, et al
    . Shift volume directly impacts neuroradiology error rate at a large academic medical center: the case for volume limits. AJNR Am J Neuroradiol 2024;45:374–78 doi:10.3174/ajnr.A8119 pmid:38238099
    Abstract/FREE Full Text
  2. 2.↵
    Parliamentary and Health Service Ombudsman. Unlocking Solutions in Imaging: working together to learn from failings in the NHS. July 2021. https://www.ombudsman.org.uk/publications/unlocking-solutions-imaging-working-together-learn-failings-nhs. Accessed January 23, 2024
  3. 3.↵
    1. Guenette JP,
    2. Lynch E,
    3. Abbasi N, et al
    . Actionability of recommendations for additional imaging in head and neck radiology. J Am Coll Radiol 2024 Jan 12. [Epub ahead of print] doi:10.1016/j.jacr.2024.01.005 pmid:38220042
    CrossRefPubMed
  4. 4.↵
    1. Glover M,
    2. Almeida RR,
    3. Schaefer PW, et al
    . Quantifying the impact of noninterpretive tasks on radiology report turn-around times. J Am Coll Radiol 2017;14:1498–503 doi:10.1016/j.jacr.2017.07.023 pmid:28916177
    CrossRefPubMed
  5. 5.↵
    1. Khoshpouri P,
    2. Khalili N,
    3. Khalili N, et al
    . Visa opportunities for international medical graduates applying for U.S. academic radiology department faculty positions: A national survey. AJR Am J Roentgenol 2024;222:e2330008 doi:10.2214/AJR.23.30008 pmid:37910038
    CrossRefPubMed
  • © 2024 by American Journal of Neuroradiology
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American Journal of Neuroradiology: 45 (6)
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Jeffrey P. Guenette, Geoffrey S. Young, Rajiv Gupta, Javier M. Romero, Raymond Y. Huang
A Public Health Perspective on Radiologists’ Interpretation Volumes
American Journal of Neuroradiology Jun 2024, 45 (6) E10-E11; DOI: 10.3174/ajnr.A8240

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A Public Health Perspective on Radiologists’ Interpretation Volumes
Jeffrey P. Guenette, Geoffrey S. Young, Rajiv Gupta, Javier M. Romero, Raymond Y. Huang
American Journal of Neuroradiology Jun 2024, 45 (6) E10-E11; DOI: 10.3174/ajnr.A8240
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