Vol. 25 No. 44 (2026): Artificial Intelligence and health
Originalartikler

Bridging AI and Clinical Practice: Fieldwork Insights from a Non-Interventional stroke Center

PDF (Dansk)
  • Maria Bach Nielsen,
  • Tom Børsen,
  • Casper Knudsen
Maria Bach Nielsen
Aalborg Universitet
DOI: https://doi.org/10.7146/tfss.v25i44.156503

Published 2026-06-26

Keywords

  • Artificial Intelligence in Healthcare,
  • Clinical Workflow Integration,
  • Participatory Design,
  • Techno-Anthropology,
  • Socio-Technical Systems,
  • Digital Health Innovation,
  • Ethnography of Technology,
  • Reflective Implementation
    • ...More
    Less

How to Cite

Bach Nielsen, M., Børsen, T., & Knudsen, C. (2026). Bridging AI and Clinical Practice: Fieldwork Insights from a Non-Interventional stroke Center. Tidsskrift for Forskning I Sygdom Og Samfund - Journal of Research in Sickness and Society, 25(44), 19–47. https://doi.org/10.7146/tfss.v25i44.156503

Copyright (c) 2026 Maria Bach Nielsen, Tom Børsen, Casper Knudsen

Creative Commons License

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

Abstract

Artificial Intelligence (AI) is rapidly entering healthcare, but its impact depends on how it is taken up in clinical environments and whether it aligns with the needs of healthcare professionals. This article draws on rapid ethnographic fieldwork at a large university hospital’s non-interventional stroke center and radiology clinic, to explore the early stages of introducing an AI-based decision support tool in emergency neurology. Using the AI in Practice framework, the analysis focuses on preliminary institutional engagement, workflow contextualization, and the initial steps of reflective planning to examine how AI becomes situated within clinical routines. Through participant observation, interviews, and co-design workshops, the article traces how clinicians respond to AI not as a finished tool, but as a proposition requiring negotiation, interpretation, and adjustment. The material highlights the importance of involving healthcare professionals in shaping AI systems in ways that are accountable, transparent, and responsive to existing practices. Rather than presenting AI as a ready solution,  This article reflects on what it takes for such technologies to make sense in everyday  health care
PDF (Dansk)

References

  1. Adrian, S. W. (2015). Naturligvis? Når lys, hunde og kønsceller sætter naturen til forhandling på fertilitetsklinikken. Kulturstudier, 5(1), 103–127. https://doi.org/10.7146/ks.v5i1.18618
  2. Adrian, S. W., Kroløkke, C., & Herrmann, J. R. (2021). Monstrous Motherhood – Women on the Edge of Reproductive Age. Science as Culture, 30(4), 491–512. https://doi.org/10.1080/09505431.2021.1935842
  3. Barad, K. Michelle. (2007). Meeting the universe halfway: Quantum physics and the entanglement of matter and meaning. Duke University Press.
  4. Børsen, T., & Botin, L. (2013). What is Techno-anthropology? Aalborg University Press. https://books.google.dk/books?id=anPVoAEACAAJ
  5. Cabitza, F., Rasoini, R., & Gensini, G. F. (2017). Unintended Consequences of Machine Learning in Medicine. JAMA : The Journal of the American Medical Association, 318(6), 517–518. https://doi.org/10.1001/jama.2017.7797
  6. Char, D. S., Shah, N. H., & Magnus, D. (2018). Implementing Machine Learning in Health Care—Addressing Ethical Challenges. The New England Journal of Medicine, 378(11), 981–983. https://doi.org/10.1056/NEJMp1714229
  7. Choubey, A., Choubey, S. B., K, P., Daulatabad, V. S., & John, N. (2024). Healthcare Transformation: Artificial Intelligence Is the Dire Imperative of the Day. Cureus, 16(6), e62652. https://doi.org/10.7759/cureus.62652
  8. D’Adderio, L., & Bates, D. W. (2025). Transforming diagnosis through artificial intelligence. Npj Digital Medicine, 8(1), 1–4. https://doi.org/10.1038/s41746-025-01460-1
  9. Fusco, F., Marsilio, M., & Guglielmetti, C. (2023). Co-creation in healthcare: Framing the outcomes and their determinants. Journal of Service Management, 34(6), 1–26. https://doi.org/10.1108/JOSM-06-2021-0212
  10. Greenhalgh, T., Wherton, J., Papoutsi, C., Lynch, J., Hughes, G., A’Court, C., Hinder, S., Fahy, N., Procter, R., & Shaw, S. (2017). Beyond adoption: A new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies. Journal of Medical Internet Research, 19(11), e367–e367. https://doi.org/10.2196/jmir.8775
  11. Greenhalgh, T., Wherton, J., Shaw, S., Papoutsi, C., Vijayaraghavan, S., & Stones, R. (2019). Infrastructure Revisited: An Ethnographic Case Study of how Health Information Infrastructure Shapes and Constrains Technological Innovation. Journal of Medical Internet Research, 21(12), e16093–e16093. https://doi.org/10.2196/16093
  12. Haraway, D. (1988). Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective. Feminist Studies, 14(3), 575–599. https://doi.org/10.2307/3178066
  13. Ihde, D. (1990). Technology and the Lifeworld: From Garden to Earth. Indiana University Press.
  14. Laurisz, N., Ćwiklicki, M., Żabiński, M., Canestrino, R., & Magliocca, P. (2023). Co-Creation in Health 4.0 as a New Solution for a New Era. Healthcare, 11(3), Article 3. https://doi.org/10.3390/healthcare11030363
  15. Mabillard, V., Demartines, N., & Joliat, G.-R. (2022). How Can Reasoned Transparency Enhance Co-Creation in Health Care and Remedy the Pitfalls of Digitization in Doctor-Patient Relationships? International Journal of Health Policy and Management, 11(10), 1986–1990. https://doi.org/10.34172/ijhpm.2020.263
  16. Mol, A. (2002). The Body Multiple: Ontology in Medical Practice. Duke University Press. https://doi.org/10.1215/9780822384151
  17. Nickel, G. C., Wang, S., Kwong, J. C. C., & Kvedar, J. C. (2024). The case for inclusive co-creation in digital health innovation. Npj Digital Medicine, 7(1), 1–2. https://doi.org/10.1038/s41746-024-01256-9
  18. Pink, S., & Morgan, J. (2013). Short-Term Ethnography: Intense Routes to Knowing. Symbolic Interaction, 36(3), 351–361. https://doi.org/10.1002/symb.66
  19. Star, S. leigh. (1999). The Ethnography of Infrastructure. American Behavioral Scientist, 43(3), 377–391. https://doi.org/10.1177/00027649921955326
  20. Suchman, L. (2006). Human-Machine Reconfigurations: Plans and Situated Actions (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511808418
  21. Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. https://doi.org/10.1038/s41591-018-0300-7
  22. Vries, A. van D., Stevens, A., Weijden, T. van der, & Beurskens, A. J. H. M. (2020). How to support a co-creative research approach in order to foster impact. The development of a Co-creation Impact Compass for healthcare researchers. PLOS ONE, 15(10), e0240543. https://doi.org/10.1371/journal.pone.0240543