The ChatGPT may free time needed by the interventional radiologist for administration / documentation

A study on the RSNA PICC line reporting template

Authors

  • Jan F Senge Department of Mathematics and Computer Science, University of Bremen, Bremen, Germany https://orcid.org/0000-0002-2889-5489
  • Matthew T McMurray Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Switzerland https://orcid.org/0009-0003-4710-8377
  • Fabian Haupt Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Switzerland https://orcid.org/0000-0002-2401-922X
  • Philipe S. Breiding University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Switzerland https://orcid.org/0000-0002-6985-0332
  • Claus Beisbart Center for Artificial Intelligence in Medicine, University of Bern, Bern, Switzerland https://orcid.org/0000-0003-2731-6200
  • Keivan Daneshvar Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Switzerland https://orcid.org/0000-0002-0345-0379
  • Alois Komarek Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Switzerland
  • Gerd Nöldge Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Switzerland https://orcid.org/0009-0001-4186-4986
  • Frank Mosler Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Switzerland https://orcid.org/0000-0002-2039-4911
  • Wolfram Andreas Bosbach Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Switzerland https://orcid.org/0000-0003-4182-3516

DOI:

https://doi.org/10.59667/sjoranm.v7i2.12

Keywords:

large language models, interventional radiology, automation of administration and documentation

Abstract

Motive: Documentation and administration, unpleasant necessities, take a substantial part of the working time in the subspecialty of interventional radiology. With increasing future demand for clinical radiology predicted, time savings from use of text drafting technologies could be a valuable contribution towards our field.

Method: Three cases of peripherally inserted central catheter (PICC) line insertion were defined for the present study. The current version of ChatGPT was tasked with drafting reports, following the Radiological Society of North America (RSNA) template.

Key results: Score card evaluation by human radiologists indicates that time savings in documentation / administration can be expected without loss of quality from using ChatGPT. Further, automatically generated texts were not assessed to be clearly identifiable as AI-produced.

Conclusions: Patients, doctors, and hospital administrators would welcome a reduction of the time that interventional radiologists need for documentation and administration these days. If AI-tools as tested in the present study are brought into clinical application, questions about trust into those systems eg with regard to medical complications will have to be addressed.

References

UVA Radiology and Medical Imaging, Ed., “What is interventional radiology?,” Inside View. https://blog.radiology.virginia.edu/interventional-radiologist-definition/ (accessed Jun. 17, 2023).

Medical College of Wisconsin, “PICC Insertion,” RSNA RadReport, 2012. https://radreport.org/home/188/2012-05-29 00:00:00 (accessed May 03, 2023).

OpenAI LLC, Ed., “ChatGPT — Release Notes (May 3).” https://help.openai.com/en/articles/6825453-chatgpt-release-notes (accessed May 04, 2023).

S. Woolhandler and D. U. Himmelstein, “Administrative work consumes one-sixth of u.s. physicians’ working hours and lowers their career satisfaction,” Int. J. Heal. Serv., vol. 44, no. 4, pp. 635–642, 2014, doi: 10.2190/HS.44.4.a.

S. M. Erickson, B. Rockwern, M. Koltov, R. M. Mclean, and M. Practice, “Putting Patients First by Reducing Administrative Tasks in Health Care: A Position Paper of the American College of Physicians Putting Patients First by Reducing Administrative Tasks in Health Care: A Position Paper of the American College of Physicians,” Ann. Intern. Med., vol. 166, no. 9, pp. 659–661, 2017, doi: 10.7326/M16-2697.

M. Henderson, “Radiology Facing a Global Shortage,” RSNA News, 2023. https://www.rsna.org/news/2022/may/global-radiologist-shortage (accessed May 16, 2023).

G. Sutherland, N. Russell, R. Gibbard, and A. Dobrescu, The Value of Radiology , Part II - The Conference Board of Canada, no. June. Ottawa, CAN, 2019.

K. Zuse, “Aus mechanischen Schaltgliedern aufgebautes Speicherwerk,” DE924107, 1937

A. M. Turing, “I.-Computing machinery and intelligence,” Mind - A Q. Rev. Psychol. Philos., vol. 236, pp. 433–460, 1950.

J. McCarthy, M. L. Minsky, N. Rochester, and C. E. Shannon, “A Proposal For The Dartmouth Summer Research Project On Artificial Intelligence,” 1955. http://jmc.stanford.edu/articles/dartmouth/dartmouth.pdf (accessed Oct. 30, 2021).

D. Glowacka, A. Howes, J. P. Jokinen, A. Oulasvirta, and Ö. Azimsek, “RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction,” Ext. Abstr. 2021 CHI Conf. Hum. Factors Comput. Syst., pp. 1–3, 2021, doi: 10.1145/3411763.3441323.

R. Doshi, K. Amin, P. Khosla, S. Bajaj, S. Chheang, and H. P. Forman, “Utilizing Large Language Models to Simplify Radiology Reports : a comparative analysis,” medRxiv Prepr., 2023, doi: 10.1101/2023.06.04.23290786.

R. Bhayana, F. S. Krishna, and R. R. Bleakney, “Performance of ChatGPT on a Radiology Board-style Examination : Insights into Current Strengths and Limitations,” Radiology, vol. 307, no. 5, p. e230582, 2023.

Q. Lyu, J. Tan, M. E. Zapadka, J. Ponnatapura, C. Niu, K. J. Myers, G. Wang, and C. T. Whitlow, “Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential,” Vis. Comput. Ind. Biomed. Art, vol. 6, no. 9, pp. 1–10, 2023, doi: 10.1186/s42492-023-00136-5.

M. Barat, P. Soyer, and A. Dohan, “Appropriateness of Recommendations Provided by ChatGPT to Interventional Radiologists,” Can. Assoc. Radiol. J., pp. 1–6, 2023, doi: 10.1177/08465371231170133.

W. A. Bosbach, J. F. Senge, B. Nemeth, S. H. Omar, M. Mitrakovic, C. Beisbart, A. Horvath, J. T. Heverhagen, and K. Daneshvar, “Ability of ChatGPT to generate competent radiology reports for distal radius fracture by use of RSNA template items and integrated AO classifier,” Curr. Probl. Diagn. Radiol., 2023, [Online]. Available: https://doi.org/10.1067/j.cpradiol.2023.04.001

W. A. Bosbach, J. F. Senge, B. Nemeth, S. H. Omar, M. Mitrakovic, C. Beisbart, A. Horvath, J. T. Heverhagen, and K. Daneshvar, “Online supplement to manuscript: ‘Ability of ChatGPT to generate competent radiology reports for distal radius fracture by use of RSNA template items and integrated AO classifier.’ Current problems in diagnostic radiology (2023).,” zenodo, 2023, doi: 10.5281/zenodo.7908791.

OpenAI LLC, Ed., “ChatGPT — Release Notes (Jan 9).” https://help.openai.com/en/articles/6825453-chatgpt-release-notes (accessed Jan. 11, 2023).

E. Rudkowsky, M. Haselmayer, M. Wastian, M. Jenny, Š. Emrich, and M. Sedlmair, “More than bags of words: Sentiment analysis with word embeddings,” Commun. Methods Meas., vol. 12, no. 2–3, pp. 140–157, 2018.

K. L. Gwet, Handbook of inter-rater reliability: The definitive guide to measuring the extent of agreement among raters. Gaithersburg, MD (USA): Advanced Analytics, LLC, 2014.

K. Gwet and A. Fergadis, “irrCAC - Chance-corrected Agreement Coefficients,” 2023. https://irrcac.readthedocs.io/en/latest/index.html# (accessed Mar. 05, 2023).

W. A. Bosbach, J. F. Senge, and P. Dlotko, Eds., “2022 Proceedings of the 4th International Conference on Trauma Surgery Technology: Mathematics in medical diagnostics,” 2022, pp. 1–36. doi: 10.5281/zenodo.7191419.

W. A. Bosbach, M. Heinrich, R. Kolisch, and C. Heiss, “Maximization of Open Hospital Capacity under Shortage of SARS-CoV-2 Vaccines-An Open Access, Stochastic Simulation Tool,” Vaccines, vol. 9, no. 6, p. 546, 2021, doi: 10.3390/vaccines9060546.

W. A. Bosbach, “Open-access supplement: Maximisation of open hospital capacity under shortage of SARS-CoV-2 vaccines,” zenodo, 2021, doi: 10.5281/zenodo.4589333.

J. J. Hatherley, “Limits of trust in medical AI,” J. Med. Ethics, vol. 46, no. 7, pp. 478–481, 2020, doi: 10.1136/medethics-2019-105935.

M. Verdicchio and A. Perin, “When Doctors and AI Interact: on Human Responsibility for Artificial Risks,” Philos. Technol., vol. 35, no. 11, pp. 1–28, 2022, doi: 10.1007/s13347-022-00506-6.

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Published

2024-04-27

How to Cite

The ChatGPT may free time needed by the interventional radiologist for administration / documentation: A study on the RSNA PICC line reporting template. (2024). Swiss Journal of Radiology and Nuclear Medicine, 7(2), 14. https://doi.org/10.59667/sjoranm.v7i2.12

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