# Enhancing quality of antimicrobial prescribing through ‘Ask Eolas’ (language model): a user-testing and simulation evaluation

## TL;DR

A new AI tool called Ask Eolas improves antibiotic prescribing accuracy and reduces errors compared to traditional methods, boosting clinician confidence and usability.

## Contribution

Ask Eolas, an AI-powered clinical decision support system, achieves zero prescribing errors in a simulation study compared to existing tools.

## Key findings

- Ask Eolas achieved zero prescribing errors versus six and eight errors in comparator groups.
- Clinicians using Ask Eolas showed improved usability, confidence, and system transparency.
- The number needed to treat was 1.9, indicating significant error reduction with Ask Eolas.

## 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.