Enhancing quality of antimicrobial prescribing through ‘Ask Eolas’ (language model): a user-testing and simulation evaluation
File(s)
Published version
Author(s)
Waldock, William
Gilchrist, Mark
Ashrafian, Hutan
Darzi, Ara
Franklin, Bryony Dean
Type
Journal Article
Abstract
We aimed to assess prescribing accuracy, error reduction, usability, and clinician confidence of Ask Eolas (a retrieval-augmented generation-enhanced AI-CDSS) compared to existing antimicrobial guidance tools. We conducted a structured simulation single-site study evaluating Ask Eolas across 45 prescribing cases with healthcare professionals to assess prescribing accuracy. Among 45 participants, Ask Eolas achieved zero prescribing errors versus six and eight documented errors in the two comparator groups (Eolas App and PDF Guidelines), respectively (p < 0.001). The number needed to treat was 1.9 for Ask Eolas versus traditional guidelines, indicating one additional error-free prescription for every two clinicians switching to Ask Eolas. Ask Eolas significantly improved prescribing accuracy while enhancing usability, clinician confidence, and system transparency compared to existing tools. These findings align with TRUST-AI framework principles for safe AI-CDSS deployment, supporting further investigation through real-world implementation studies incorporating live data integration, confidence calibration systems, and comprehensive auditability features in antimicrobial stewardship programmes.
Date Issued
2026-03-03
Date Acceptance
2026-02-02
Citation
npj Antimicrobials and Resistance, 2026, 4
ISSN
2731-8745
Publisher
Nature Portfolio
Journal / Book Title
npj Antimicrobials and Resistance
Volume
4
Copyright Statement
© The Author(s) 2026. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Publication Status
Published
Article Number
16
Date Publish Online
2026-03-03