Clarifying validation terminologies in healthcare.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 41787064.
- Also identified by DOI 10.1038/s41746-026-02471-2 and PMC identifier 13079824.
- Licence recorded as CC BY-NC-ND.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
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.