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Completed

NCT Number: NCT04477304

Application of Economics & Social Psychology to Improve Opioid Prescribing Safety Trial 1: EHR Nudges

The opioid epidemic has had a tremendous negative impact on the health of persons in the U.S. The objective of the trial 1 of Application of Economics & Social psychology to improve Opioid Prescribing Safety (AESOPS-T1), is to discourage unnecessary opioid prescribing through the application of "behavioral insights"-empirically-tested social and psychological interventions that affect choice.

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Key information

Conditions

Opioid Abuse, Unspecified Chemically-Induced Disorders Mental Disorders Narcotic-Related Disorders Opioid-Related Disorders Substance-Related Disorders

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Northwestern University

Chicago, Illinois, 60611, United States

About this study

A multisite study, AESOPS-T1 randomizes clinics to behavioral intervention or control. Clinics randomized to the behavioral intervention arm receive electronic health record (EHR)-based nudges. Eligible participants are clinicians who practice ambulatory primary care at the participating clinical sites in Illinois and California. At the time of opioid prescribing, clinicians in clinics randomized to the intervention group will be prompted with an EHR nudge when the prescribing history for the patient falls into one of the following three mutually exclusive categories: Opioid naïve, At-risk for long-term use, or Long-term opioid recipient. These EHR-based nudges include accountable justification, defaults and precommitments. The control arm receives no EHR-based intervention. Both arms receive guideline education. The primary outcome is the change in clinician aggregate weekly milligram morphine equivalent (MME) dose and the secondary outcome is the proportion of dosages that equal or exceed 50 MME per day. These outcomes will be estimated by treatment arm with an intent-to-treat difference-in-differences framework using a mixed-effects regression model on clinician MME daily dose. The intervention period will be 18-months, with a 6-month follow-up period to measure the persistence of effects after the interventions conclude.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Providers of clinics that see patients ≥ 18 years old and for whom clinic leadership agrees to participate.

Exclusion criteria

  • Visits will be excluded from intervention when the patient has active cancer.

Treatment and study plan

Opioid Naive, OR

Behavioral

Visits where the order is for an included opioid and there is no prior opioid prescription with a start date of greater than 1 day and less than 91 days and clinician is on the clinic list as a treating member of the clinic

At-risk for long-term use, OR

Behavioral

Visit where the order is for an included opioid, there is a prior opioid prescription with a start date greater than 1 day and less than 91 days, and there is no prior opioid prescription with a start date greater than 90 days and clinician is on the clinic list as a treating member of the clinic

Long-term opioid recipient

Behavioral

Total opioid doses are at least 50 MME per day, there are two or more prior opioid prescriptions with two different start dates both greater than 1 day and less than 91 days, and there is a prior opioid prescription with a start date greater than 90 days and less than 181 days and clinician is on the clinic list as a treating member of the clinic

Primary outcomes

  1. Change in Average Per-clinician Log Total Weekly MME Between Baseline and Intervention for Opioid Naïve and At-Risk Patients (Below 50 MME Daily Dose Rxs)

    Time frame: 6-month baseline and 18-month intervention

    Change = (18-month intervention average of natural log MME summed per-clinician, per-week - 6-month baseline average of natural log MME summed per-clinician, per-week). Log(total MME) = log(Rx strength x number of pills x opioid conversion factor)

  2. Change in Average Per-clinician Log Total Weekly MME Between Baseline and Intervention for Chronic Opioid Patients (=> 50 MME Daily Dose Rxs)

    Time frame: 6-month baseline and 18-month intervention

    Change = (18-month intervention average of natural log MME summed per-clinician, per-week - 6-month baseline average of natural log MME summed per-clinician, per-week). Log(total MME) = log(Rx strength x number of pills x opioid conversion factor)

Secondary outcomes

  1. Change in Average Per-clinician Weekly Proportion of Chronic Patients Prescribed a High Dose Opioid (=> 50 MME Daily Dose Rxs) Between Baseline and Intervention

    Time frame: 6-month baseline and 18-month intervention

    Change = (18-month intervention average per-clinician weekly proportion - 6-month baseline average per-clinician weekly proportion). Proportion = number of chronic patients who received Rx => 50 MME per-clinician, per-week/total patients who received opioid Rx per-clinician, per-week

Other outcomes

  1. Change in Average Per-clinician Log Total Weekly MME Between Baseline and Post-intervention for Opioid Naïve and At-Risk Patients (Below 50 MME Daily Dose Rxs)

    Time frame: 6-month baseline and 6-month post-intervention

    Change = (6-month post-intervention average of natural log MME summed per-clinician, per-week - the 18-month baseline average of natural log MME summed per-clinician, per-week). Log(total MME) = log(Rx strength x number of pills x opioid conversion factor)

  2. Change in Average Per-clinician Weekly Proportion of Chronic Patients Prescribed a High Dose Opioid (=> 50 MME Daily Dose Rxs) Between Baseline and Post-intervention

    Time frame: 6-month baseline and 6-month post-intervention

    Change = (6-month post-intervention average per-clinician weekly proportion - 6-month baseline average per-clinician weekly proportion). Proportion = number of chronic patients who received Rx => 50 MME per-clinician, per-week/total patients who received opioid Rx per-clinician, per-week

  3. Change in Average Per-clinician Log Total Weekly MME Between Baseline and Post-intervention for Chronic Opioid Patients (=> 50 MME Daily Dose Rxs)

    Time frame: 6-month baseline and 6-month post-intervention

    Change = (6-month post-intervention average of natural log MME summed per-clinician, per-week - the 6-month baseline average of natural log MME summed per-clinician, per-week). Log(total MME) = log(Rx strength x number of pills x opioid conversion factor)

Sponsors and collaborators

Lead sponsor

University of Southern California

Other

Collaborators

  • AltaMed Health Services Corporation
  • National Institute on Aging (NIA)
  • Northwestern University

Registry information

Official study title

Application of Economics & Social Psychology to Improve Opioid Prescribing Safety Trial 1: Electronic Health Record Nudges

Acronym: AESOPS-T1

Important dates

Study start
2020
Primary completion
2023
Study completion
2023
First posted
Jul 20, 2020
Registry last updated
Aug 7, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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