Machine-Learning Prediction and Reducing Overdoses With EHR Nudges

Recruiting now · Not applicable

Conditions studied: Opioid Overdose, Opioid Use, Opioid Use Disorder, Opioids

In brief

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.

Key facts

Study ID

NCT06806163

Run by

University of Pittsburgh

People needed

1350

Starts

2025-03-10

Expected to finish

2027-02-01

Last updated by the study team

2026-06-17

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• 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 may not qualify if…

• Diagnosis of malignant cancer within the past year
• Enrollment in hospice care

Where it is running

• University of Pittsburgh — Pittsburgh, Pennsylvania, United States (enrolling)

Full record on ClinicalTrials.gov

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