Narrativizing Care: Exploring Narrative Medicine for Designing AI-Mediated Remote Patient Monitoring
Abstract
This paper examines how care is enacted and understood within Remote Patient Monitoring (RPM) systems, which promise efficiency and autonomy but fragment care into data flows. Drawing on ethnographic fieldwork in a Dutch hospital’s RPM program for myocardial infarction patients, we analyze how stories, reassurance, and contextual interpretation unfold alongside structured data, revealing the promise and limits of AI-mediated care. Using narrative medicine’s triad of attention, representation, and affiliation, we identify how extractive data models overlook patients’ lived realities and relational dimensions of care. We propose three design provocations for exploring the application of AI in RPM systems: narrative layers which situate data within evolving stories, shared story construction which supports co-authored records, and temporal storytelling which captures care as an ongoing narrative. We argue narrativization is central and not supplementary to relational care, and position narrative medicine as a design lens for creating AI infrastructures that sustain human connection.
Keywords
RPM, Relational Care, Narrative Medicine, Artificial Intelligence (AI)
DOI
https://doi.org/10.21606/drs.2026.1500
Citation
Ranjbar, S., Capel, T., Lloyd, P., Atsma, D.E., Ben Allouch, S., and Raijmakers, J. (2026) Narrativizing Care: Exploring Narrative Medicine for Designing AI-Mediated Remote Patient Monitoring, in Simeone, L., Gray, C. M., Verhoeven, A., de Götzen, A., Bakırlıoğlu, Y., Zohar, H., Stead, M., and Buwert, P. (eds.), DRS2026: Edinburgh, 8–12 June, Edinburgh, United Kingdom. https://doi.org/10.21606/drs.2026.1500
Creative Commons License
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Included in
Narrativizing Care: Exploring Narrative Medicine for Designing AI-Mediated Remote Patient Monitoring
This paper examines how care is enacted and understood within Remote Patient Monitoring (RPM) systems, which promise efficiency and autonomy but fragment care into data flows. Drawing on ethnographic fieldwork in a Dutch hospital’s RPM program for myocardial infarction patients, we analyze how stories, reassurance, and contextual interpretation unfold alongside structured data, revealing the promise and limits of AI-mediated care. Using narrative medicine’s triad of attention, representation, and affiliation, we identify how extractive data models overlook patients’ lived realities and relational dimensions of care. We propose three design provocations for exploring the application of AI in RPM systems: narrative layers which situate data within evolving stories, shared story construction which supports co-authored records, and temporal storytelling which captures care as an ongoing narrative. We argue narrativization is central and not supplementary to relational care, and position narrative medicine as a design lens for creating AI infrastructures that sustain human connection.