Consensus-based Algorithms to Address Opioid Misuse Behaviors Among Individuals Prescribed Long-term Opioid Therapy

Consensus-based Algorithms to Address Opioid Misuse Behaviors Among Individuals Prescribed Long-term Opioid Therapy: Developing Implementation Strategies and Pilot Testing

The NIH Helping to End Addiction Long-term (HEAL) initiative has identified a critical next step to addressing the opioid crisis: improving treatments for opioid misuse behaviors (e.g., using more opioids than prescribed, illicit substance use) in patients prescribed long-term opioid therapy for chronic pain. In previous work, the investigators have developed innovative consensus-based algorithms to manage these behaviors. By developing implementation strategies for these algorithms, this project is directly responsive to the HEAL initiative and promises to reduce opioid misuse-related harms.

Study Overview

• Status: Completed
• Conditions: Chronic Pain; Opioid Misuse
• Intervention / Treatment: Behavioral: Pilot study of algorithms implementation package

Detailed Description

Despite a growing understanding of the risks of long-term opioid therapy (LTOT), it continues to be frequently prescribed and remains a mainstay of treatment for chronic pain. The Centers for Disease and Control (CDC) Guideline for Prescribing Opioids for Chronic Pain is geared toward primary care providers and has been adopted as the standard of care by many healthcare organizations and insurers. Importantly, it encourages monitoring of patients on LTOT for opioid-related harms. By implementing monitoring, primary care providers may uncover various concerning behaviors, sometimes called aberrant drug-related behaviors or opioid misuse behaviors, that arise among individuals prescribed LTOT for chronic pain. These behaviors (e.g., missed appointments, using more opioid medication than prescribed, asking for an increase in opioid dose, aggressive behavior, and alcohol and other substance use) are common, concerning, and may represent unsafe use of LTOT or a developing opioid use disorder (OUD). However, the CDC Guideline and other existing evidence do not provide specific, detailed guidance about how to address concerning behaviors when they occur. Therefore, there is a critical need to understand how to best respond to these behaviors. The long-term goal of our program of research is to reduce LTOT-related harms, particularly from opioid misuse, and diminish their impact on the U.S. opioid epidemic. As a first step toward accomplishing this goal, the investigators conducted a Delphi study to rigorously establish consensus-based approaches to managing common and challenging concerning behaviors, from which algorithms were created. Identifying and operationalizing implementation strategies using an evidence-based framework are the critical next steps that must occur before any testing of the algorithms.

The investigators successfully uncovered optimal implementation strategies through primary care provider experiences with Standardized Patients (SPs) followed by Consolidated Framework for Implementation Research (CFIR)- and Expert Recommendations for Implementing Change (ERIC)-guided individual interviews. Using our prior expertise developing clinic-wide opioid risk reduction strategies and a Patient-Provider advisory board, the investigators developed a comprehensive "implementation package" that can be delivered to primary care practices.

The investigators now aim to conduct a pilot trial to test the algorithm implementation package. Guided by the CFIR-based implementation plan and using the implementation package that the investigators developed, pilot trial will be conducted to investigate feasibility, acceptability, and preliminary effectiveness of the algorithm implementation package.

• Study Type: Interventional
• Enrollment (Actual): 49
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Pennsylvania
    • Pittsburgh, Pennsylvania, United States, 15231
      • University of Pittsburgh

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Clinicians practicing at UPMC community primary care clinics.

Exclusion Criteria:

• Clinicians not practicing at UPMC community primary care clinics.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Implementation Bundle; The 'Implementation Bundle' was integrated into all three participating clinics over six to nine months.	Behavioral: Pilot study of algorithms implementation package; The algorithm implementation package includes a link to the algorithms in the Electronic Health Record, Smartphrases, audited feedback, and instructions.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Feasibility of Algorithms	The number of algorithms used by physicians was assessed via a survey administered at the end of the 6- or 9-month implementation period, measuring self-reported toolkit utilization during the study. Our primary feasibility benchmark will be that 80% of physicians report using at least one algorithm during the study period.	At the end of the 6- or 9-month implementation period
Acceptability of Algorithms	Acceptability of the algorithms was assessed via a self-report survey administered at the end of the 6- or 9-month implementation period, measuring physicians' awareness of the algorithms and self-reported toolkit use within six months of implementation. Our primary acceptability benchmark is that at least 80% of physicians report awareness of the algorithm implementation and at least 50% report using the algorithms during the study period. Additionally, qualitative interviews with physicians and staff provided further insights, which were analyzed using thematic analysis.	At the end of the 6- or 9-month implementation period

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Preliminary Effectiveness of Algorithms - MME Reduction ≥10%	Number of long-term opioid therapy (LTOT) patients whose 90-day average Morphine Milligram Equivalents (MME) decreased at or above a margin of 10% from the start of the reporting period to the end of the reporting period.	Pre-implementation (12 months), implementation (6 to 9 months), post-implementation (12 months)
Preliminary Effectiveness - Average MME Within Last 90 Days	Average morphine milligram equivalents (MME) among long-term opioid therapy (LTOT) patients during the last 90 days of each period.	Pre-implementation (12 months), implementation (6 or 9 months), post-implementation (12 months)
Preliminary Effectiveness of Algorithms - Opioid Discontinuation	Number of long-term opioid therapy (LTOT) patients whose 90-day average Morphine Milligram Equivalents (MME) at the start of this reporting period was 0.	Pre-implementation (12 months), implementation (6 to 9 months), post-implementation (12 months)
Preliminary Effectiveness of the Algorithms - New OUD Diagnoses	New opioid use disorder (OUD) diagnoses documented in the electronic health record (EHR) among all patients seen by participating physicians, by period. No new OUD diagnoses were documented in any period.	Pre-implementation (12 months), implementation (6 to 9 months), post-implementation (12 months)

Collaborators and Investigators

• Sponsor: University of Pittsburgh
• Collaborators: National Institute on Drug Abuse (NIDA)
• Investigators: Principal Investigator: Jessica Merlin, University of Pittsburgh

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2022
• Primary Completion (Actual): September 30, 2023
• Study Completion (Actual): September 30, 2024

Study Registration Dates

• First Submitted: November 28, 2021
• First Submitted That Met QC Criteria: December 21, 2021
• First Posted (Actual): January 10, 2022

Study Record Updates

• Last Update Posted (Estimated): January 8, 2026
• Last Update Submitted That Met QC Criteria: December 15, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Chronic Pain; Long-Term Opioid Therapy; Algorithms; Opioid Misuse
• Additional Relevant MeSH Terms: Narcotic-Related Disorders; Pain; Neurologic Manifestations; Mental Disorders; Substance-Related Disorders; Chemically-Induced Disorders; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Opioid-Related Disorders; Chronic Pain
• Other Study ID Numbers: STUDY20030189; R34DA050004 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No