Currently accepted at: JMIR Medical Education
Date Submitted: Apr 15, 2026
Date Accepted: Aug 18, 2026
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/98383
The final accepted version (not copyedited yet) is in this tab.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Health data workflow literacy: the missing foundation for AI-ready health professions education
ABSTRACT
Background:
Medical schools worldwide are integrating artificial intelligence into their curricula, but this effort addresses the top of the competency stack while ignoring its foundation. A meaningful capacity to work with AI tools requires prior mastery of data handling, structuring, and sharing practices that are rarely taught systematically.
Objective:
This paper argues that health data workflow literacy — the practical ability to manage, structure, and share data in reproducible and interoperable ways — should be recognised as a core interprofessional competency in health professions education, distinct from and prerequisite to AI literacy.
Methods:
I define health data workflow literacy and its component competencies; analyse the gap in current frameworks (IPEC, WHO, AAMC); and illustrate how these competencies can be taught using free, open-source tools, drawing on teaching experience at the Faculty of Medicine of the University of Porto.
Results:
Current competency frameworks address clinical informatics and AI literacy but omit the intermediate layer of data workflow literacy. This gap leads to graduates who can discuss AI conceptually but cannot structure a dataset, manage references as machine-readable metadata, track changes to an analysis, or produce a reproducible report. Free tools such as Zotero, Git, and Quarto can teach these competencies within existing courses without requiring dedicated informatics tracks.
Conclusions:
Health data workflow literacy is a prerequisite for meaningful engagement with AI tools, clinical information systems, and interprofessional collaboration. It should be embedded longitudinally in health professions curricula and explicitly included in major competency frameworks. The tools to address this gap are available and free; what is needed is curricular and institutional will.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.