Using machine learning to reduce opioid overdoses through EHR alerts
Machine-Learning Prediction and Reducing Overdoses With EHR Nudges
This study is testing whether alerts in electronic health records can help doctors better support patients at high risk for opioid overdoses and reduce the chances of overdose.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 1350 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | University of Pittsburgh Academic / other |
| Locations | 1 site (Pittsburgh, Pennsylvania) |
| Trial ID | NCT06806163 on ClinicalTrials.gov |
What this trial studies
This clinical trial aims to evaluate the effectiveness of a behavioral nudge intervention embedded in Electronic Health Records (EHR) for patients identified as high-risk for opioid overdose using a machine-learning risk prediction model. The study will compare the outcomes of patients receiving an elevated-risk flag with and without behavioral nudges against those receiving usual care from primary care clinicians. By addressing the challenges of identifying high-risk individuals and changing clinician behavior, the trial seeks to improve opioid prescribing safety and reduce overdose risks.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 and older who have received an opioid prescription within the past year and have visited a primary care practice.
Not a fit: Patients with a diagnosis of malignant cancer within the past year or those enrolled in hospice care may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could significantly reduce the incidence of opioid overdoses by improving clinician awareness and prescribing practices.
How similar studies have performed: While there have been various interventions aimed at reducing opioid overdoses, this specific combination of machine learning and behavioral nudges represents a novel approach that has not been extensively tested.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * 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 Exclusion Criteria: * Diagnosis of malignant cancer within the past year * Enrollment in hospice care
Where this trial is running
Pittsburgh, Pennsylvania
- University of Pittsburgh — Pittsburgh, Pennsylvania, United States (Recruiting)
Study contacts
- Principal investigator: Walid F Gellad, MD, MPH — University of Pittsburgh Center for Pharmaceutical Policy and Prescribing
- Study coordinator: Lead Research Program Coordinator, CP3
- Email: cp3@pitt.edu
- Phone: (412) 692-4889
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.