Do We Have Enough Information? Assessing AI Clinical Decision Support Systems for Implementation in Primary Care

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Authors: Angela M. Coderre-Ball, Anjana Ravi Chandran, Valentina Gnanapragasam, Rebecca Ataman, Karine Baser, Pippy Scott-Meuser
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Abstract

This environmental scan examined commercially available AI clinical decision support solutions (AI-CDSS) across three domains: knowledge base, AI methodology, and privacy. Over half of vendors disclosed some information on their knowledge base, yet few demonstrated rigorous appraisal or alignment with Quality Standards or other evidence-based guidelines. Transparency on AI methods was limited as most cited proprietary algorithms but rarely described training data. Privacy information was more commonly reported but often high-level, with limited detail on compliance, storage location, or restrictions on secondary use. These gaps reveal the obstacles facing decision makers: without standardized, transparent information, organizations and governments cannot reliably evaluate AI-CDSS or provide the support clinicians need for responsible and informed implementation.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Electronic Health Records Systems Artificial Intelligence in Healthcare

Publication details

Journal / source
Studies in health technology and informatics
Volume
334
Pages
73–77
Publication date
12 February 2026
Language
EN
Document type
Book chapter