Preventing Medication Dispensing Errors in Pharmacy Practice With Interpretable Machine Intelligence
NCT ID: NCT06245044
Last Updated: 2025-11-26
Study Results
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View full resultsBasic Information
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COMPLETED
NA
68 participants
INTERVENTIONAL
2024-04-11
2024-12-04
Brief Summary
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Detailed Description
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To facilitate the long-term symbiotic relationship between the pharmacists and the MI system, proper trust needs to be established. While trust has been identified as the central factor for effective human-machine teaming, issues arise when humans place unjustified trust in automated technologies do not place enough trust in them. Over trust in automation can lead to complacency and automation bias. For instance, the pharmacists may rely on the MI system to the extent that they blindly accept any recommendation by the system. Under trust can result in pharmacist disuse and potential abandonment of the MI system.
Furthermore, little is known about the timing of the MI advice on pharmacists' work performance. For example, showing the MI's advice while the pharmacist is performing the medication verification task may yield different results than showing the MI's advice after the pharmacist made their decision.
The study investigators have developed a MI system for medication images classification. The objective of this study is to examine the effectiveness of the timing of MI advice to determine if it results in lower task time, increased accuracy, and increased trust in the MI.
Conditions
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Study Design
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RANDOMIZED
CROSSOVER
OTHER
NONE
Study Groups
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No MI Help
No MI help will be presented during the verification tasks
No MI Help
Participants will complete the medication verification task without any MI help
Scenario #1
Participants will receive MI in the form of a pop-up message if their decision differs from the MI's determination.
Scenario #2
MI help will be displayed concurrently with the filled and reference images.
Scenario #1
MI help will be presented in the form of a pop-up message the participant's decision differs from the MI's determination.
No MI Help
Participants will complete the medication verification task without any MI help
Scenario #1
Participants will receive MI in the form of a pop-up message if their decision differs from the MI's determination.
Scenario #2
MI help will be displayed concurrently with the filled and reference images.
Scenario #2
MI help will be displayed concurrently with the filled and reference images.
No MI Help
Participants will complete the medication verification task without any MI help
Scenario #1
Participants will receive MI in the form of a pop-up message if their decision differs from the MI's determination.
Scenario #2
MI help will be displayed concurrently with the filled and reference images.
Interventions
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No MI Help
Participants will complete the medication verification task without any MI help
Scenario #1
Participants will receive MI in the form of a pop-up message if their decision differs from the MI's determination.
Scenario #2
MI help will be displayed concurrently with the filled and reference images.
Eligibility Criteria
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Inclusion Criteria
* Age 18 years and older at screening
* PC/Laptop with Microsoft Windows 10 or Mac (Macbook, iMac) with MacOS with Google Chrome, Edge, Opera, Safari, or Firefox web browser installed on the device
* Screen resolution of 1024x968 pixels or more
* A laptop integrated webcam or USB webcam is also required for the eye tracking purpose.
Exclusion Criteria
* Eyeglasses
* Uncorrected cataracts, intraocular implants, glaucoma, or permanently dilated pupil
* Require a screen reader/magnifier or other assistive technology to use the computer
* Eye movement or alignment abnormalities (lazy eye, strabismus, nystagmus)
18 Years
ALL
No
Sponsors
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University of Michigan
OTHER
National Library of Medicine (NLM)
NIH
Responsible Party
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Corey Lester
Assistant Professor of Clinical Pharmacy
Principal Investigators
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Corey A Lester, PharmD, PhD
Role: PRINCIPAL_INVESTIGATOR
University of Michigan
Locations
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University of Michigan
Ann Arbor, Michigan, United States
Countries
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Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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HUM00241223
Identifier Type: -
Identifier Source: org_study_id
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