Fatigue in radiology: a fertile area for future research

Cover Page

Cite item

Full Text

Abstract

Fatigue in radiologists may be responsible for a large number of medical errors. This review describes the latest research on fatigue in radiology. This includes measurement methods, and recent evidence on how fatigue affects accuracy in laboratory test conditions and in clinical practice. The extensive opportunities for future research in the area are explored, including testing interventions to reduce fatigue-related error, and further understanding of which fatigue measures correlate with errors. Finally we explore the possibility of answering these questions using large population-based observational studies and pragmatic integrated randomised controlled trials.

This publication is the reprint with Russian translation from original: Taylor-Phillips S, Stinton C. Fatigue in radiology: a fertile area for future research. Br J Radiol. 2019;92:20190043. doi: 10.1259/bjr.20190043.

About the authors

Sian Taylor-Phillips

Warwick Medical School, The University of Warwick

Author for correspondence.
Email: s.taylor-phillips@warwick.ac.uk
ORCID iD: 0000-0002-1841-4346

Ph.D.

United Kingdom, Coventry

Chris Stinton

Warwick Medical School, The University of Warwick

Email: c.stinton@bham.ac.uk
ORCID iD: 0000-0001-9054-1940
United Kingdom, Coventry

References

  1. Hogan H, Healey F, Neale G, et al. Preventable deaths due to problems in care in English acute hospitals: a retrospective case record review study. BMJ Qual Saf. 2012;21(9):737–745. doi: 10.1136/bmjqs-2011-001159
  2. Chief Medical Officer. An organisation with a memory: Report of an expert group on learning from adverse events in the NHS. London: The British Institute of Radiology; 2000.
  3. Lockley SW, Barger LK, Ayas NT, et al. Effects of health care provider work hours and sleep deprivation on safety and performance. Jt Comm J Qual Patient Saf. 2007;33(11 Suppl):7–18. doi: 10.1016/S1553-7250(07)33109-7
  4. Barger LK, Cade BE, Ayas NT, et al. Extended work shifts and the risk of motor vehicle crashes among interns. N Engl J Med. 2005;352:125–134. doi: 10.1056/NEJMoa041401
  5. Hanna TN, Lamoureux C, Krupinski EA, et al. Effect of shift, schedule, and volume on interpretive accuracy: a retrospective analysis of 2.9 million radiologic examinations. Radiology. 2018;287(1):205–212. doi: 10.1148/radiol.2017170555
  6. Clinical Radiology UK workforce census 2014 report. London: The British Institute of Radiology; 2015.
  7. Pigeon WR, Sateia MJ, Ferguson RJ. Distinguishing between excessive daytime sleepiness and fatigue: toward improved detection and treatment. J Psychosom Res. 2003;54(1):61–69. doi: 10.1016/s0022-3999(02)00542-1
  8. Shahid A, Shen J, Shapiro CM. Measurements of sleepiness and fatigue. J Psychosom Res. 2010;69(1):81–89. doi: 10.1016/j.jpsychores.2010.04.001
  9. Xu R, Zhang C, He F, et al. How physical activities affect mental fatigue based on EEG energy, connectivity, and complexity. Front Neurol. 2018;9:915. doi: 10.3389/fneur.2018.00915
  10. Krupinski E, Reiner BI. Real-time occupational stress and fatigue measurement in medical imaging practice. J Digit Imaging. 2012;25(3):319–324. doi: 10.1007/s10278-011-9439-1
  11. Waite S, Kolla S, Jeudy J, et al. Tired in the reading room: the influence of fatigue in radiology. J Am Coll Radiol. 2017;14(2):191–197. doi: 10.1016/j.jacr.2016.10.009
  12. Akerstedt T, Gillberg M. Subjective and objective sleepiness in the active individual. Int J Neurosci. 1990;52(1-2):29–37. doi: 10.3109/00207459008994241
  13. Hoddes E, Zarcone V, Smythe H, et al. Quantification of sleepiness: a new approach. Psychophysiology. 1973;10(4):431–436. doi: 10.1111/j.1469-8986.1973.tb00801.x
  14. Johns MW. A new method for measuring daytime sleepiness: the epworth sleepiness scale. Sleep. 1991;14(6):540–545. doi: 10.1093/sleep/14.6.540
  15. Rosenthal L, Roehrs TA, Roth T. The sleep-wake activity inventory: a self-report measure of daytime sleepiness. Biol Psychiatry. 1993;34(11):810–820. doi: 10.1016/0006-3223(93)90070-T
  16. Buysse DJ, Reynolds CF, Monk TH, et al. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. doi: 10.1016/0165-1781(89)90047-4
  17. Ahsberg E. Dimensions of fatigue in different working populations. Scand J Psychol. 2000;41(3):231–241. doi: 10.1111/1467-9450.00192
  18. Miglioretti DL, Smith-Bindman R, Abraham L, et al. Radiologist characteristics associated with interpretive performance of diagnostic mammography. J Natl Cancer Inst. 2007;99(24):1854–1863. doi: 10.1093/jnci/djm238
  19. Maeda E, Yoshikawa T, Hayashi N, et al. Radiology reading-caused fatigue and measurement of eye strain with critical flicker fusion frequency. Jpn J Radiol. 2011;29(7):483–487. doi: 10.1007/s11604-011-0585-7
  20. Sheppard AL, Wolffsohn JS. Digital eye strain: prevalence, measurement and amelioration. BMJ Open Ophthalmol. 2018;3(1):e000146. doi: 10.1136/bmjophth-2018-000146
  21. Thomson DR, Besner D, Smilek D. A critical examination of the evidence for sensitivity loss in modern vigilance tasks. Psychol Rev. 2016;123(1):70–83. doi: 10.1037/rev0000021
  22. Mackworth N. Researches on the measurement of human performance. London, UK: The British Institute of Radiology; 1950.
  23. See JE, Howe SR, Warm JS, et al. Meta-analysis of the sensitivity decrement in vigilance. Psychological Bulletin. 1995;117(2):230–249. doi: 10.1037/0033-2909.117.2.230
  24. Gur D, Rockette HE, Armfield DR, et al. Prevalence effect in a laboratory environment. Radiology. 2003;228(1):10–14. doi: 10.1148/radiol.2281020709
  25. Evans KK, Birdwell RL, Wolfe JM. If you don’t find it often, you often don’t find it: why some cancers are missed in breast cancer screening. PLoS One. 2013;8(5):e64366. doi: 10.1371/journal.pone.0064366
  26. Kompaniez-Dunigan E, Abbey CK, Boone JM, Webster MA. Visual adaptation and the amplitude spectra of radiological images. Cogn Res Princ Implic. 2018;3(1):3. doi: 10.1186/s41235-018-0089-4
  27. Blatter K, Cajochen C. Circadian rhythms in cognitive performance: methodological constraints, protocols, theoretical underpinnings. Physiol Behav. 2007;90(2-3):196–208. doi: 10.1016/j.physbeh.2006.09.009
  28. Monk TH. The post-lunch dip in performance. Clin Sports Med. 2005;24(2):e15–23xi-xii. doi: 10.1016/j.csm.2004.12.002
  29. Krupinski EA, Berbaum KS, Caldwell RT, et al. Long radiology workdays reduce detection and accommodation accuracy. J Am Coll Radiol. 2010;7(9):698–704. doi: 10.1016/j.jacr.2010.03.004
  30. Krupinski EA, Berbaum KS, Caldwell RT, et al. Do long radiology workdays affect nodule detection in dynamic CT interpretation? J Am Coll Radiol. 2012;9(3):191–198. doi: 10.1016/j.jacr.2011.11.013
  31. Al-s’adi M, McEntee M, Ryan E. Time of day does not affect radiologists’ accuracy in breast lesion detection. Proc SPIE Med Imag. 2011;7966:1–7. doi: 10.1117/12.877972
  32. Cowley HC, Gale AG. Time of day effects on mammographic film reading performance. 1997. doi: 10.1117/12.271295
  33. Stec N, Arje D, Moody AR, et al. A systematic review of fatigue in radiology: is it a problem? AJR Am J Roentgenol. 2018;210(4):799–806. doi: 10.2214/AJR.17.18613
  34. Krupinski EA, Schartz KM, Van Tassell MS, et al. Effect of fatigue on reading computed tomography examination of the multiply injured patient. J Med Imaging. 2017;4(3):1. doi: 10.1117/1.JMI.4.3.035504
  35. Hanna TN, Zygmont ME, Peterson R, et al. The effects of fatigue from overnight shifts on radiology search patterns and diagnostic performance. J Am Coll Radiol. 2018;15(12):1709–1716. doi: 10.1016/j.jacr.2017.12.019
  36. Gur D, Bandos AI, Cohen CS, et al. The “laboratory” effect: comparing radiologists’ performance and variability during prospective clinical and laboratory mammography interpretations. Radiology. 2008;249(1):47–53. doi: 10.1148/radiol.2491072025
  37. Miglioretti DL, Ichikawa L, Smith RA, et al. Correlation between screening mammography interpretive performance on a test set and performance in clinical practice. Acad Radiol. 2017;24(10):1256–1264. doi: 10.1016/j.acra.2017.03.016
  38. Taylor-Phillips S, Wallis MG, Jenkinson D, et al. Effect of using the same vs different order for second readings of screening mammograms on rates of breast cancer detection: a randomized clinical trial. JAMA. 2016;315(18):1956–1965. doi: 10.1001/jama.2016.5257
  39. Stinton C, Jenkinson D, Adekanmbi V, et al. Does time of day influence cancer detection and recall rates in mammography? SPIE Medical Imaging. 2017. Vol. 10136. doi: 10.1117/12.2254280.
  40. Wolfe JM, Van Wert MJ. Varying target prevalence reveals two dissociable decision criteria in visual search. Curr Biol. 2010;20(2):121–124. doi: 10.1016/j.cub.2009.11.066
  41. Burnside ES, Park JM, Fine JP, Sisney GA. The use of batch reading to improve the performance of screening mammography. AJR Am J Roentgenol. 2005;185(3):790–796. doi: 10.2214/ajr.185.3.01850790
  42. Fenton JJ, Abraham L, Taplin SH, et al. Effectiveness of computer-aided detection in community mammography practice. J Natl Cancer Inst. 2011; 103(15):1152–1161. doi: 10.1093/jnci/djr206
  43. Fenton JJ, Taplin SH, Carney PA, et al. Influence of computer-aided detection on performance of screening mammography. N Engl J Med. 2007;356(14):1399–1409. doi: 10.1056/NEJMoa066099
  44. ISRCTN Register and Evaluating the age extension of the NHS breast screening Programme – trial registration. 2010.
  45. Freemantle N, Ray D, McNulty D, et al. Increased mortality associated with weekend hospital admission: a case for expanded seven day services? BMJ. 2015;351:h4596. doi: 10.1136/bmj.h4596
  46. Rimmer A. The BMJ paper and seven day services. BMJ. 2016;352:i1193. doi: 10.1136/bmj.i1193.

Supplementary files

Supplementary Files
Action
1. JATS XML
2. British Journal of Radiology original article
View 

Copyright (c) 2019 Taylor-Phillips S., Stinton C.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies