Skip to main content

From Images to Reports

  • Chapter
  • First Online:
Efficient Radiology
  • 475 Accesses

  • The original version of this chapter was revised. The year “1985” in the first line of Section 9.1 is corrected as “1895”. The correction to this chapter can be found at https://doi.org/10.1007/978-3-030-53610-7_11

Abstract

The last steps in the radiology workflow fall to the radiologist. The images must be evaluated with an eye to answering the explicit or implicit questions raised in the order. A report must be created, and essential communications completed. This chapter describes some of the ways to optimize the radiologist’s workflow, from quality assurance to prioritization and service expectations. Issues concerning productivity and timeliness are covered as well as potential trade-offs between productivity and quality.

“All meanings, we know, depend on the key of interpretation.”

George Eliot

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 16.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Change history

  • 19 December 2020

    The original version of Chapter 9 was inadvertently published with an incorrect year on first line of Section 9.1. It is corrected as "1895".

Notes

  1. 1.

    We told you this was an amoral book!

References

  1. Glasser O. W. C. Roentgen and the discovery of the Roentgen rays. Am J Roentgenol Radium Ther. 1995;165:437–50.

    Google Scholar 

  2. Czuczman G, Pomerantz S, Alkasab T, Huang A. Using a web-based image quality assurance reporting system to improve image quality. Am J Roentgenol. 2013;201(2):361–8.

    Article  Google Scholar 

  3. ASRS. Immunity policies. [Online]. https://asrs.arc.nasa.gov/overview/immunity.html.

  4. Gaskin CM, Patrie JT, Hanshew MD, Boatman DM, McWey RP. Impact of a reading priority scoring system on the prioritization of examination interpretations. Am J Roentgenol. 2016;206(5):1031–9.

    Article  Google Scholar 

  5. Halford GS, Baker R, McCredden JE, Bain JD. How many variables can humans process? Psychol Sci. 2005;16(1):70–6.

    Article  Google Scholar 

  6. Iyengar SS, Lepper MR. When choice is demotivating: can one desire too much of a good thing? J Pers Soc Psychol. 2000;79(6):995–1006.

    Article  CAS  Google Scholar 

  7. Harvey H, Alkasab T, Stingley P, Shore M, Abedi-Tari F, Abujudeh H, Meyersohn M, Zhao J, Pandharipande P, Rosenthal D. Curbing inappropriate usage of STAT imaging at a large academic medical center. J Patient Saf. 2019;15(1):24–9.

    Article  Google Scholar 

  8. Rubenstein J, Meyer D, Evans J. Executive control of cognitive processes in task switching. J Exp Psychol. 2001;27(4):763–97.

    Google Scholar 

  9. Benitez BFF, Cardoso R, Torres F, Faccin C, Dora J. Systematic layout planning of a radiology reporting area to optimize radiologists’ performance. J Digit Imaging. 2018;31:193–200.

    Article  Google Scholar 

  10. Lee MH, Schemmel AJ, Pooler BD, Hanley T, Kennedy T, Field A, Wiegmann D, Yu J. Radiology workflow dynamics: how workflow patterns impact radiologist perceptions of workplace satisfaction. Acad Radiol. 2017;24(4):483–7.

    Article  Google Scholar 

  11. Wong T, Kaza J, Rasiej M. Effect of analytics-driven worklists on musculoskeletal MRI interpretation times in an academic setting. AJR Am J Roentgenol. 2019;212(5):1091–5.

    Article  Google Scholar 

  12. Khan SH, Hedges WP. What is the relation between number of sessions worked and productivity of radiologists—a pilot study? J Digit Imaging. 2016;29:165–74.

    Article  Google Scholar 

  13. Brady AP. Measuring Consultant Radiologist workload: method and results from a national survey. Insights Imaging. 2011;2(3):247–60.

    Article  Google Scholar 

  14. National Archives and Records Administration. Medicare programs: fee schedules for radiologists’ services. Fed Regist. 1989;54:8994–9023.

    Google Scholar 

  15. Lu Y, Zhao S, Chu PW, Arenson RL. An update survey of academic radiologists’ clinical productivity. J Am Coll Radiol. 2008;5(7):817–26.

    Article  Google Scholar 

  16. Monaghan DA, Kassak KM, Ghomrawi HM. Determinants of radiologists’ productivity in private group practices in California. J Am Coll Radiol. 2006;3(2):108–14.

    Article  CAS  Google Scholar 

  17. Dora JTF, Gerchman M, Fogliatto F. Development of a local relative value unit to measure radiologists’ computed tomography reporting workload. J Med Imaging Radiat Oncol. 2016;60:714–9.

    Article  Google Scholar 

  18. Walsh C, Aquino J, Seely J, Kielar A, Rakhra K, Dennie C, et al. The Ottawa Hospital RADiologist Activity Reporting (RADAR) productivity metric: effects on radiologist productivity. Can Assoc Radiol J. 2018;69(1):71–7.

    Article  Google Scholar 

  19. Kopans DB. Double reading. Radiol Clin. 2000;38(4):719–24.

    Article  CAS  Google Scholar 

  20. Anderson E, Muir B, Walsh JS, Kirkpatirick A. The efficacy of double reading mammograms in breast screening. Clin Radiol. 1994;49(4):248–51.

    Article  CAS  Google Scholar 

  21. Bhargavan M, Kaye A, Forman H, Sunshine J. Workload of Radiologists in United States in 2006-2007 and trends since 1991-1992. Radiology. 2009;252(2):458–67.

    Article  Google Scholar 

  22. McDonald RJ, Schwartz KM, Eckel LJ, Diehn FE, Hunt CH, Bartholmai BJ, Erickson BJ, Kallmes DF. The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload. Acad Radiol. 2015;22(9):1191–8.

    Article  Google Scholar 

  23. Kumamaru KK, Machitori A, Koba R, Ijichi S, Nakajima Y, Aoki S. Global and Japanese regional variations in radiologist potential workload for computed tomography and magnetic resonance imaging examinations. Jpn J Radiol. 2018;36(4):273–81.

    Article  Google Scholar 

  24. Levin D, Rao VM, Parker L, Frangos A. The sharp reductions in Medicare payments for noninvasive diagnostic imaging in recent years: will they satisfy the federal policymakers? J Am Coll Radiol. 2012;9(9):643–7.

    Article  Google Scholar 

  25. Hanna T, Lamoureux C, Krupinski EA, Weber S, Johnson J. Effect of shift, schedule, and volume on interpretive accuracy: a retrospective analysis of 2.9 million radiologic examinations. Radiology. 2018;287(1):205–12.

    Article  Google Scholar 

  26. Stec N, Arje A, Moody A, Krupanski E, Tyrrell P. A systematic review of fatigue in radiology: is it a problem? AJR Am J Roentgenol. 2018;210(4):799–806.

    Article  Google Scholar 

  27. Berlin L. Liability of interpreting too many radiographs. Am J Roentgenol. 2000;175:17–22.

    Article  CAS  Google Scholar 

  28. Sokolovskaya E, Shinde T, Ruchman R, Kwak A, Lu S, Shariff Y, Wiggins E, Talangbayan L. The effect of faster reporting speed for imaging studies on the number of misses and interpretation errors: a pilot study. J Am Coll Radiol. 2015;12:683–6.

    Article  Google Scholar 

  29. Muroff LR, Berlin L. Speed versus interpretation accuracy: current thoughts and literature review. AJR. 2019;213(3):490–2.

    Article  Google Scholar 

  30. Chew F, Mulcahy M, Porrino J, Mulcahy H, Relyea-Chew A. Prevalence of burnout among musculoskeletal radiologists. Skelet Radiol. 2017;46(4):497–506.

    Article  Google Scholar 

  31. Thompson G. Measuring performance in radiology. Radiol Bus. 2011. https://www.radiologybusiness.com/topics/business-intelligence/measuring-performance-radiology

  32. Heye T, Gysin V, Boll D, Merkle E. Structured reporting: the voice of the customer in an ongoing debate about the future of radiology reporting. AJR Am J Roentgenol. 2018;211(5):9640970.

    Article  Google Scholar 

  33. Chockley K, Emanuel E. The end of radiology? Three threats to the future practice of radiology. J Am Coll Radiol. 2016;13:1415–20.

    Article  Google Scholar 

  34. Tang A, Tam R, Cadrin-Chenevert A, Guest W, Chong J, Barfett J, Chepelev L, Cairns R, Mitchell JR, Cicero MD, Poudrette MGJJL, Reinhold C, Gallix B, Gray B, Geis R, Canadian Association of Radiologists Artificial Intelligence Working Group. Canadian Association of Radiologists White Paper on artificial intelligence in radiology. Can Assoc Radiol J. 2018;69(2):120–35.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daniel Rosenthal .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Rosenthal, D., Pianykh, O. (2021). From Images to Reports. In: Efficient Radiology. Springer, Cham. https://doi.org/10.1007/978-3-030-53610-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-53610-7_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-53609-1

  • Online ISBN: 978-3-030-53610-7

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics