Machine-Learning Prediction and Reducing Overdoses With EHR Nudges (mPROVEN)

University of Pittsburgh

Status: Enrolling

Conditions: Opioid Overdose; Opioid Use Disorder; Opioids; Opioid Use

Treatments: Behavioral: EHR-Embedded Elevated-Risk Flag with Behavioral Nudges; Behavioral: EHR-Embedded Elevated-Risk Flag; Behavioral: Usual Care

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT06806163

STUDY22040068

R01DA044985-04 (U.S. NIH Grant/Contract)

Details and patient eligibility

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.

Full description

In response to the opioid overdose crisis, health systems have instituted multiple interventions to reduce patient risk, including decreasing unsafe opioid prescribing among high-risk patients and dispensing naloxone. However, these interventions face two key challenges. First, there are limited and poorly performing tools to identify who is truly at risk of overdose, leading to burdensome interventions targeting an overly broad population or missing key high-risk individuals. Second, even with more accurate identification of high-risk patients, highly effective strategies to change clinician behavior remain limited. Common cognitive biases may underlie clinicians' lack of response to risk factors for overdose.

This project aims to address both of these limitations by combining more accurate risk prediction tools to identify those at elevated risk of opioid overdose with novel "nudge" interventions based on principles of behavioral economics that have been shown to address cognitive biases and change prescribing behavior. The primary hypothesis is that high-risk patients in primary care practices randomized to the elevated-risk flag + nudge intervention will have safer prescribing compared to usual care.

Enrollment: 1,350 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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1,350 participants in 3 patient groups

Usual Care

Active Comparator group

Description:

Patients in the practices randomized to the Usual Care arm will receive standard care practice without change.

Treatment:

Behavioral: Usual Care

EHR-Embedded Elevated-Risk Flag

Experimental group

Description:

An elevated-risk flag will be embedded in the EHR and prominently displayed in the chart during encounters for patients identified as having elevated-risk for opioid overdose.

Treatment:

Behavioral: EHR-Embedded Elevated-Risk Flag

EHR-Embedded Elevated-Risk Flag with Behavioral Nudges

Experimental group

Description:

An elevated-risk flag will be embedded in the EHR and prominently displayed in the chart during encounters for patients identified as having elevated-risk for opioid overdose. This flag will be combined with a set of best practice alerts/behavioral nudges that will trigger when certain conditions are met during encounters with elevated-risk patients.

Treatment:

Behavioral: EHR-Embedded Elevated-Risk Flag with Behavioral Nudges