Effect of Uncertainty-Aware AI Models on Pharmacists’ Reaction Time and Decision-Making in a Web-Based Mock Medication Verification Task: Randomized Controlled Trial

Pharmacists' performance and reaction times varied by AI type and AI accuracy. Overall, uncertainty-aware AI resulted in faster decision-making and acted as a safeguard against bad AI advice to approve a misfilled medication. Conversely, black-box AI had the longest reaction times, and user performance degraded in the presence of bad AI advice. However, uncertainty-aware AI could result in unnecessary double-checks, but it is preferred over false negative advice, where patients receive the wrong medication. These results highlight the importance of well-designed AI that addresses users' needs, enhances performance, and avoids overreliance on AI.

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Publication Details

Journal
JMIR Medical Informatics
Published
2025-03-08
DOI
https://doi.org/10.2196/64902
Citations
3
Primary Topic
Patient Safety and Medication Errors
Type
article
Field-Weighted Citation Impact
7.55
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article

Effect of Uncertainty-Aware AI Models on Pharmacists’ Reaction Time and Decision-Making in a Web-Based Mock Medication Verification Task: Randomized Controlled Trial

Corey A. Lester, Qiyuan Chen, Yifan Zheng, Vincent D. Marshall et al.
3 citations
JMIR Medical Informatics
Patient Safety and Medication Errors
7.55
article

Effect of Uncertainty-Aware AI Models on Pharmacists’ Reaction Time and Decision-Making in a Web-Based Mock Medication Verification Task: Randomized Controlled Trial

Corey A. Lester, Qiyuan Chen, Yifan Zheng, Vincent D. Marshall, Brigid Rowell, X. Jessie Yang, Raed Al Kontar, Zoe Co, Jin Yong Kim
article en
3 citations

Abstract

Pharmacists' performance and reaction times varied by AI type and AI accuracy. Overall, uncertainty-aware AI resulted in faster decision-making and acted as a safeguard against bad AI advice to approve a misfilled medication. Conversely, black-box AI had the longest reaction times, and user performance degraded in the presence of bad AI advice. However, uncertainty-aware AI could result in unnecessary double-checks, but it is preferred over false negative advice, where patients receive the wrong medication. These results highlight the importance of well-designed AI that addresses users' needs, enhances performance, and avoids overreliance on AI.

JMIR Medical InformaticsVol. 13
University of Michigan (US), Michigan Medicine (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Patient Safety and Medication Errors
7.55
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