- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06795477
Preventing Medication Dispensing Errors in Pharmacy Practice with Interpretable Machine Intelligence: Wave 2
January 21, 2025 updated by: Corey Lester
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.
Study Overview
Status
Completed
Conditions
Intervention / Treatment
Study Type
Interventional
Enrollment (Actual)
30
Phase
- Not Applicable
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
-
Michigan
-
Ann Arbor, Michigan, United States, 48109
- University of Michigan
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
No
Description
Inclusion Criteria:
- 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.
Exclusion Criteria:
- 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)
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Other
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: Interpretable MI
Participants receive interpretable machine intelligence to complete the medication verification task.
|
Participants will complete the medication verification task without any MI help
Participants receive interpretable machine intelligence assistance to complete the medication verification tasks.
|
|
Experimental: Uninterpretable MI
Participants receive uninterpretable (i.e., black-box) machine intelligence to complete the medication verification task.
|
Participants will complete the medication verification task without any MI help
Participants receive uninterpretable (i.e., black-box) machine intelligence assistance to complete the medication verification tasks.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Decision accuracy
Time Frame: 1 day - Single study visit
|
Difference in detection rate measured by number of medication verification errors
|
1 day - Single study visit
|
|
Trust change
Time Frame: 1 day - Single study visit
|
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
|
|
Cognitive effort
Time Frame: 1 day - Single study visit
|
Difference in cognitive effort measured by duration of fixation and fixation count
|
1 day - Single study visit
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Reaction time
Time Frame: 1 day - Single study visit
|
Difference in task time measured by the number of seconds from starting the task to accepting or rejecting a medication image
|
1 day - Single study visit
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
February 1, 2023
Primary Completion (Actual)
May 12, 2023
Study Completion (Actual)
May 12, 2023
Study Registration Dates
First Submitted
January 21, 2025
First Submitted That Met QC Criteria
January 21, 2025
First Posted (Actual)
March 25, 2025
Study Record Updates
Last Update Posted (Actual)
March 25, 2025
Last Update Submitted That Met QC Criteria
January 21, 2025
Last Verified
January 1, 2025
More Information
Terms related to this study
Other Study ID Numbers
- HUM00213493
- 5R01LM013624 (U.S. NIH Grant/Contract)
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
Clinical Trials on Machine Intelligence in the Pharmacy
-
University of MichiganNational Library of Medicine (NLM)CompletedPreventing Medication Dispensing Errors in Pharmacy Practice With Interpretable Machine IntelligenceMachine Intelligence in the PharmacyUnited States
-
University Hospital Inselspital, BerneCSEM Centre Suisse d'Electronique et de Microtechnique SA - Recherche et...UnknownTo Introduce Artificial Intelligence (AI) and Machine Learning in Cardiotocography (CTG) Interpretation to Improve Clinical UseSwitzerland
-
University of North Carolina, Chapel HillMerck Sharp & Dohme LLCCompletedEvaluating Attitudes Toward HPV Vaccinations in Pharmacies | Evaluating the Provision of HPV Vaccines in a PharmacyUnited States
-
University of PennsylvaniaCompletedArtificial Intelligence | Machine Learning | Diagnostic ImagingUnited States
-
AHEPA University HospitalGeorge Papanicolaou Hospital; University General Hospital of Heraklion; University... and other collaboratorsRecruitingArtificial Intelligence | Machine Learning | Electronic Medical RecordsGreece
-
Istituto Ortopedico RizzoliNot yet recruitingMachine Learning | Predictive Model | Joint Replacement | Artificial Intelligence (AI)Italy
-
Royal Devon and Exeter NHS Foundation TrustActive, not recruitingKeratoconus | Keratoconus, Artificial Intelligence, Support Vector MachineUnited Kingdom
-
luyunRecruitingPostoperative Complications | Artificial Intelligence | Risk Factors | Machine Learning | Risk Assessment | Operative Surgical ProcedureChina
-
Hazem Yassin ClinicsAhmed I ElSayeghEnrolling by invitationKeratoconus | Machine Learning | Refractive Surgery | Ophthalmology | Diagnostic Accuracy | Clinical Decision Support | Artifical IntelligenceEgypt
-
Radboud University Medical CenterPrime Dental Alliance EindhovenNot yet recruitingArtificial Intelligence Supported Image Reviewing | Artificial Intelligence (AI) in DiagnosisNetherlands
Clinical Trials on No MI Help
-
University of MichiganNational Library of Medicine (NLM)CompletedPreventing Medication Dispensing Errors in Pharmacy Practice With Interpretable Machine IntelligenceMachine Intelligence in the PharmacyUnited States
-
Rutgers, The State University of New JerseyNational Institute on Drug Abuse (NIDA); University of UtahRecruitingTobacco Use | Opioid Use | Polysubstance AbuseUnited States
-
Richard L. Roudebush VA Medical CenterVA Connecticut Healthcare SystemNot yet recruiting
-
Istituto Clinico HumanitasRecruitingKnee Osteoarthritis | Arthrogenic Muscle InhibitionsItaly
-
VA Office of Research and DevelopmentVA Palo Alto Health Care SystemCompleted
-
Karolinska InstitutetMinistry of Health and Social Affairs, SwedenCompleted
-
Massachusetts General HospitalRecruitingHeart Failure | Heart Failure NYHA Class II | Heart Failure NYHA Class III | Heart Failure NYHA Class IUnited States
-
University of NebraskaWithdrawn
-
CoolTech LLCObvioHealthCompletedMigraine | Migraine Without Aura | Migraine With Aura | Episodic MigraineUnited States
-
University of MichiganPatient-Centered Outcomes Research Institute; University of Pennsylvania; University... and other collaboratorsRecruitingDelirium | Neurocognitive Disorders | Alzheimer Disease | Caregiver Burden | Aging | Mild Cognitive Impairment | Patient Satisfaction | Implementation Science | Family Members | Family SupportUnited States