Integrating artificial intelligence in pathology: a qualitative interview study of users' experiences and expectations.

Jojanneke Drogt, Megan Milota, Shoko Vos, Annelien Bredenoord, Karin Jongsma
Author Information
  1. Jojanneke Drogt: Department of Medical Humanities, University Medical Center, Utrecht, The Netherlands. j.m.t.drogt@umcutrecht.nl.
  2. Megan Milota: Department of Medical Humanities, University Medical Center, Utrecht, The Netherlands.
  3. Shoko Vos: Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
  4. Annelien Bredenoord: Department of Medical Humanities, University Medical Center, Utrecht, The Netherlands.
  5. Karin Jongsma: Department of Medical Humanities, University Medical Center, Utrecht, The Netherlands.

Abstract

Recent progress in the development of artificial intelligence (AI) has sparked enthusiasm for its potential use in pathology. As pathology labs are currently starting to shift their focus towards AI implementation, a better understanding how AI tools can be optimally aligned with the medical and social context of pathology daily practice is urgently needed. Strikingly, studies often fail to mention the ways in which AI tools should be integrated in the decision-making processes of pathologists, nor do they address how this can be achieved in an ethically sound way. Moreover, the perspectives of pathologists and other professionals within pathology concerning the integration of AI within pathology remains an underreported topic. This article aims to fill this gap in the literature and presents the first in-depth interview study in which professionals' perspectives on the possibilities, conditions and prerequisites of AI integration in pathology are explicated. The results of this study have led to the formulation of three concrete recommendations to support AI integration, namely: (1) foster a pragmatic attitude toward AI development, (2) provide task-sensitive information and training to health care professionals working in pathology departments and (3) take time to reflect upon users' changing roles and responsibilities.

References

  1. BMC Med Ethics. 2020 Sep 1;21(1):81 [PMID: 32867753]
  2. J Pathol Transl Med. 2020 Mar;54(2):125-134 [PMID: 32045965]
  3. Adv Anat Pathol. 2020 Jul;27(4):241-250 [PMID: 32541594]
  4. Int J Nurs Stud. 2012 Mar;49(3):360-71 [PMID: 21996649]
  5. Arch Pathol Lab Med. 2020 Sep 1;144(9):1037-1040 [PMID: 32579394]
  6. Nurs Health Sci. 2013 Sep;15(3):398-405 [PMID: 23480423]
  7. J Pathol Inform. 2018 Nov 14;9:38 [PMID: 30607305]
  8. Med Teach. 2020 Aug;42(8):846-854 [PMID: 32356468]
  9. Nature. 2021 May;593(7857):33-36 [PMID: 33947992]
  10. Med Image Anal. 2016 Oct;33:170-175 [PMID: 27423409]
  11. Lancet Oncol. 2019 May;20(5):e253-e261 [PMID: 31044723]
  12. J Pathol Inform. 2010 Aug 10;1: [PMID: 20922032]
  13. Yearb Med Inform. 2019 Aug;28(1):14-15 [PMID: 31022746]
  14. J Pathol Inform. 2011;2:36 [PMID: 21886892]
  15. Arch Pathol Lab Med. 2010 Nov;134(11):1666-70 [PMID: 21043820]
  16. J Transl Med. 2020 Jan 9;18(1):14 [PMID: 31918710]
  17. Histopathology. 2019 Feb;74(3):372-376 [PMID: 30270453]
  18. Hum Pathol. 2020 Jan;95:137-148 [PMID: 31682887]
  19. Nurse Educ Today. 2017 Sep;56:29-34 [PMID: 28651100]
  20. Nat Rev Clin Oncol. 2019 Nov;16(11):703-715 [PMID: 31399699]
  21. J Intern Med. 2020 Jul;288(1):62-81 [PMID: 32128929]
  22. Artif Intell Med. 2022 Jan;123:102215 [PMID: 34998513]
  23. BMC Cardiovasc Disord. 2017 Jun 14;17(1):156 [PMID: 28615004]
  24. Diagn Pathol. 2020 Jul 4;15(1):80 [PMID: 32622359]
  25. Histopathology. 2012 Jul;61(1):1-9 [PMID: 21477260]
  26. Int J Qual Health Care. 2007 Dec;19(6):349-57 [PMID: 17872937]
  27. Pathology. 2010;42(6):512-8 [PMID: 20854068]
  28. Hastings Cent Rep. 2019 Jan;49(1):15-21 [PMID: 30790315]
  29. Nurse Educ Today. 2004 Feb;24(2):105-12 [PMID: 14769454]
  30. J Am Med Inform Assoc. 2021 Feb 15;28(2):284-293 [PMID: 33043359]
  31. J Pathol. 2019 Oct;249(2):143-150 [PMID: 31144302]
  32. Lab Invest. 2021 Apr;101(4):412-422 [PMID: 33454724]
  33. Semin Cancer Biol. 2021 Jul;72:226-237 [PMID: 32818626]
  34. Virchows Arch. 2010 Jul;457(1):3-10 [PMID: 20499087]
  35. NPJ Digit Med. 2019 Apr 26;2:28 [PMID: 31304375]
  36. Am J Pathol. 2021 Oct;191(10):1673-1683 [PMID: 34252382]
  37. Soc Sci Med. 2014 Oct;118:17-26 [PMID: 25086422]
  38. Histopathology. 2019 Nov;75(5):621-635 [PMID: 31301690]
  39. Comput Med Imaging Graph. 2021 Mar;88:101820 [PMID: 33453648]
  40. J Med Ethics. 2020 Apr 3;: [PMID: 32245804]
  41. J Pathol Inform. 2013 Jun 29;4:15 [PMID: 23858390]
  42. Front Med (Lausanne). 2020 Oct 20;7:591952 [PMID: 33195357]

MeSH Term

Humans
Artificial Intelligence
Motivation
Qualitative Research

Word Cloud

Created with Highcharts 10.0.0AIpathologyintegrationstudydevelopmentartificialintelligencetoolscanpathologistsperspectivesprofessionalswithininterviewusers'RecentprogresssparkedenthusiasmpotentialuselabscurrentlystartingshiftfocustowardsimplementationbetterunderstandingoptimallyalignedmedicalsocialcontextdailypracticeurgentlyneededStrikinglystudiesoftenfailmentionwaysintegrateddecision-makingprocessesaddressachievedethicallysoundwayMoreoverconcerningremainsunderreportedtopicarticleaimsfillgapliteraturepresentsfirstin-depthprofessionals'possibilitiesconditionsprerequisitesexplicatedresultsledformulationthreeconcreterecommendationssupportnamely:1fosterpragmaticattitudetoward2providetask-sensitiveinformationtraininghealthcareworkingdepartments3taketimereflectuponchangingrolesresponsibilitiesIntegratingpathology:qualitativeexperiencesexpectations

Similar Articles

Cited By