Clarifying validation terminologies in healthcare
Validation is a cornerstone of reliability and trust in diagnostics, yet discipline-specific assumptions and unspoken contextual differences often lead to miscommunication, misalignment, and avoidable delays. As AI/ML becomes more integrated into healthcare, there is a growing necessity to re-examine how the term validation is used and understood. We highlight inconsistencies in the use of the term validation through an analysis of 94 themes across five domains, including Communication Science (n = 12), AI/ML (n = 26), Clinical and Laboratory Practice (n = 19), Regulatory Science (n = 22), and Business (n = 15). We emphasize how persistent reliance on domain-specific implied definitions impedes interdisciplinary alignment. Rather than advocating for a single definition, we derived five consensus proposals that collectively advocate for more specific and context-aware additions to the term validation to support clarity, reliability, and compliance across disciplines. Our goal is to support clearer communication and provide useful strategies that inform the development, regulation, and use of digital health technologies.
Authors
- Jansen N. Seheult (ORCID: https://orcid.org/0000-0002-6850-7495)
- April Khademi
- Fabienne Lucas (ORCID: https://orcid.org/0000-0002-4388-0349)
- Sandra Buetow
- Jithesh V. Veetil
- Belinda Lennerz (ORCID: https://orcid.org/0000-0002-8021-7984)
- David S. McClintock (ORCID: https://orcid.org/0000-0003-4297-4367)
- Keith A. Wharton (ORCID: https://orcid.org/0000-0003-0374-1114)
- Shannon M. Bennett (ORCID: https://orcid.org/0000-0002-5008-6637)
- Staci J. Kearney (ORCID: https://orcid.org/0000-0003-2707-2349)
- Kim Blenman (ORCID: https://orcid.org/0000-0001-6070-0728)
- Norman Zerbe (ORCID: https://orcid.org/0000-0002-0314-3037)
- Amanda Dy
- Monika Lamba Saini (ORCID: https://orcid.org/0000-0002-2822-3893)
- Matthew G Hanna
- R. Salgado
- Sunil Singhal
- Andrew J. Bredemeyer
- M. E. de Baca
- Kevin Schap
Institutions
- College of American Pathologists (US)
- University of Washington (US)
- Robert Koch Institute (DE)
- Peter MacCallum Cancer Centre (AU)
- Yale University (US)
- Morrison Tech (US)
- Adc Therapeutics (Switzerland) (CH)
- Mayo Clinic in Arizona (US)
- Vector Institute (CA)
- University of Pittsburgh Medical Center (US)
- Synergetics (Belgium) (BE)
- CS Diagnostics (DE)
- Toronto Metropolitan University (CA)
- Charité - Universitätsmedizin Berlin (DE)
- Repligen (United States) (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-03-05
- DOI
- https://doi.org/10.1038/s41746-026-02471-2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Bundesministerium für Gesundheit
- Natural Sciences and Engineering Research Council of Canada