Machine-Learning Prediction and Reducing Overdoses With EHR Nudges
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorUniversity of Pittsburgh
About this trial
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.
Eligibility criteria
Qualifiers
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
Disqualifiers
Diagnosis of malignant cancer within the past year
Enrollment in hospice care
Trial design
Treatments tested in this trial
- EHR-Embedded Elevated-Risk Flag
- EHR-Embedded Elevated-Risk Flag with Behavioral Nudges
- Usual Care
Treatment groups
1,350 Participants
are divided into 3 treatment groupsLocations
1University of Pittsburgh15213, PittsburghPennsylvania, United States
Sponsors and collaborators
University of Pittsburgh
Lead sponsor
National Institute on Drug Abuse (NIDA)
Collaborator
Source ClinicalTrials.gov