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Decision Support for Health Professionals (2316) Clinical Information and Decision Making (3858) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (281) Pharmacology and Pharmaceutics (163) Machine Learning (3311) Artificial Intelligence (4945) Registered Report (1569)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64902, first published .
Pharmacist in white coat at computer in pharmacy with shelves of medicine.

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

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

Authors of this article:

Corey Lester1 Author Orcid Image ;   Brigid Rowell1 Author Orcid Image ;   Yifan Zheng1 Author Orcid Image ;   Zoe Co1, 2 Author Orcid Image ;   Vincent Marshall1 Author Orcid Image ;   Jin Yong Kim3 Author Orcid Image ;   Qiyuan Chen3 Author Orcid Image ;   Raed Kontar3 Author Orcid Image ;   X Jessie Yang3 Author Orcid Image
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  1. Grundy D. Harnessing reasoning-based AI for digital entrepreneurship in creative authorship. Artificial Intelligence in Education 2026;2(2):1 View
  2. Whitaker M, Rowell B, Kim J, Al Kontar R, Yang X, Lester C. Pharmacists' propensity to trust automated technologies: A demographic analysis. Journal of the American Pharmacists Association 2026;66(2):103011 View
  3. Chen X, Jin P, Mai H, Liang S, Ping Y, Wang C, Zhao Y. Artificial intelligence in pharmaceutical administration and clinical pharmacy: A comprehensive review of advancements, challenges, and future directions. Intelligent Pharmacy 2026;4(3):235 View
  4. Sheriff Y. Ahmed , Jamshid Pardaev . Human-AI Decision Dynamics: How Risk Propensity and Trust Impact Choices Through Decision Fatigue, Conditional on AI Understanding. Decision Making: Applications in Management and Engineering 2025;8(2):96 View
  5. Hariri Y, Nasser H, Zahra F. Keeping the Patient Visible when Pharmacy Services Become Data-Driven. Archives of Pharmacy Practice 2025;16(2):53 View
  6. Petrova E, Georgiev I, Stoyanov N, Kolev P. The Digital Pharmacist Proxy and the Clinical Acts That Must Remain Human. Archives of Pharmacy Practice 2026;17(2):67 View
  7. Kim J, Rowell B, Whitaker M, Chen Q, Al Kontar R, Lester C, Yang X. Effects of AI Assistance Timing on Pharmacists’ Trust in Automated Pill Recognition Technology: Within-Participants Experimental Study. JMIR Human Factors 2026;13:e92822 View
  8. Wilson E, Jong F, Peters L. Generative AI in Pharmacotherapy: Why Evidence Traceability, Verification Burden, Uncertainty, and Human Override Define the Boundary Between Clinical Assistance and Medication-Safety Risk. Annals of Pharmacy Practice and Pharmacotherapy 2026;6(1):51 View
  9. Ali A, Gharbi S, Jebali N. When Does AI-Assisted Medication Review Add Clinical Value? An Evidence-Mapping Review of Prescription Screening, Automation Error, Verification Workload, Pharmacist Oversight, and Patient-Level Consequences, 2017–2026. Annals of Pharmacy Practice and Pharmacotherapy 2026;6(1):189 View
  10. Erfani G, McCready J, Gibson B, Steven A, Unsworth J, Siira H, Jarva E, Mikkonen K, Tomietto M. The impact of patient-facing digital health interventions on patient safety outcomes: a meta-analysis of meta-analyses. Oxford Open Digital Health 2026;4 View
  11. Nguyen O, Wiegmann D, Haddad J, Doerr S, Ahmad A, Oguss M, Akel M, Wieben A, Reid J, Allan J, Edelson D, Churpek M. Development and usability testing of a machine learning clinical decision support tool for suggesting etiologies and treatment of clinical deterioration. Journal of Critical Care 2027;97:155748 View

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  1. Badhe A, Chavan N, Bharti M, Kumar A. 2026 International Conference on Emerging Technologies and Future Innovations (ETFI). Improving the Quality of Healthcare through AI-Driven Predictive Monitoring View