Actively Recruiting
Machine-Learning Prediction and Reducing Overdoses With EHR Nudges
Led by University of Pittsburgh · Updated on 2026-03-20
1350
Participants Needed
1
Research Sites
63 weeks
Total Duration
On this page
Sponsors
U
University of Pittsburgh
Lead Sponsor
N
National Institute on Drug Abuse (NIDA)
Collaborating Sponsor
AI-Summary
What this Trial Is About
The goal of this cluster randomized clinical trial is to test a clinician-targeted behavioral nudge intervention in the Electronic Health Record (EHR) for patients who are identified by a machine-learning based risk prediction model as having an elevated risk for an opioid overdose. The clinical trial will evaluate the effectiveness of providing a flag in the EHR to identify individuals at elevated risk with and without behavioral nudges/best practice alerts (BPAs) as compared to usual care by primary care clinicians. The primary goals of the study are to improve opioid prescribing safety and reduce overdose risk.
CONDITIONS
Official Title
Machine-Learning Prediction and Reducing Overdoses With EHR Nudges
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Received an opioid prescription within the past year
- Age 18 years or older at the time of the opioid prescription
- At least one visit to an internal medicine or family care practice within the past year
You will not qualify if you...
- Diagnosis of malignant cancer within the past year
- Enrollment in hospice care
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
University of Pittsburgh
Pittsburgh, Pennsylvania, United States, 15213
Actively Recruiting
Research Team
L
Lead Research Program Coordinator, CP3
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
SINGLE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
HEALTH_SERVICES_RESEARCH
Number of Arms
3
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