Preventing Medication Dispensing Errors in Pharmacy Practice with Interpretable Machine Intelligence: Wave 2
2 other identifiers
interventional
30
1 country
1
Brief Summary
Pharmacists currently perform an independent double-check to identify drug-selection errors before they can reach the patient. However, the use of machine intelligence (MI) to support this cognitive decision-making work by pharmacists does not exist in practice. This research is being conducted to examine the effectiveness machine intelligence (MI) advice on to determine if its impact on pharmacists' work performance and cognitive demand.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Feb 2023
Shorter than P25 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
February 1, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
May 12, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
May 12, 2023
CompletedFirst Submitted
Initial submission to the registry
January 21, 2025
CompletedFirst Posted
Study publicly available on registry
January 28, 2025
CompletedJanuary 28, 2025
January 1, 2025
3 months
January 21, 2025
January 21, 2025
Conditions
Outcome Measures
Primary Outcomes (3)
Cognitive effort
Difference in cognitive effort measured by duration of fixation and fixation count
1 day - Single study visit
Decision accuracy
Difference in detection rate measured by number of medication verification errors
1 day - Single study visit
Trust change
Difference in trust as measured by visual analog scale will be calculated based on AI advice accuracy. Participants will indicate their level of trust in the AI advice after every trial on a scale from 1-100, with higher scores indicating greater levels of trust.
1 day - Single study visit
Secondary Outcomes (1)
Reaction time
1 day - Single study visit
Study Arms (2)
Interpretable MI
EXPERIMENTALParticipants receive interpretable machine intelligence to complete the medication verification task.
Uninterpretable MI
EXPERIMENTALParticipants receive uninterpretable (i.e., black-box) machine intelligence to complete the medication verification task.
Interventions
Participants will complete the medication verification task without any MI help
Participants receive interpretable machine intelligence assistance to complete the medication verification tasks.
Participants receive uninterpretable (i.e., black-box) machine intelligence assistance to complete the medication verification tasks.
Eligibility Criteria
You may qualify if:
- Licensed pharmacist in the United States
- Age 18 years and older at screening
- PC/Laptop with Microsoft Windows 10 or Mac (Macbook, iMac) with MacOS with Google Chrome 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.
You may not qualify if:
- Eyeglasses with more than one power (bifocals, trifocals, progressives, layered lenses, or regression lenses)
- Cataracts, intraocular implants, glaucoma, or permanently dilated pupil
- Require a screen reader/magnifier or other assistive technology to use the computer
- Eye surgery (e.g., corneal)
- Eye movement or alignment abnormalities (lazy eye, strabismus, nystagmus)
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Corey Lesterlead
- National Library of Medicine (NLM)collaborator
Study Sites (1)
University of Michigan
Ann Arbor, Michigan, 48109, United States
Related Publications (1)
Tsai CC, Kim JY, Chen Q, Rowell B, Yang XJ, Kontar R, Whitaker M, Lester C. Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial. J Med Internet Res. 2025 Jan 31;27:e59946. doi: 10.2196/59946.
PMID: 39888668DERIVED
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- OTHER
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR INVESTIGATOR
- PI Title
- Assistant Professor of Clinical Pharmacy
Study Record Dates
First Submitted
January 21, 2025
First Posted
January 28, 2025
Study Start
February 1, 2023
Primary Completion
May 12, 2023
Study Completion
May 12, 2023
Last Updated
January 28, 2025
Record last verified: 2025-01