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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Nov 20, 2023
Open Peer Review Period: Nov 8, 2023 - Jan 3, 2024
Date Accepted: Jan 24, 2024
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Decreasing Opioid Addiction and Diversion Using Behavioral Economics Applied Through a Digital Engagement Solution: Protocol for a Randomized Controlled Trial

Rizvi RF, Schoephoerster JA, Desphande SS, Usher MG, Oien AE, Peters MM, Loth MS, Bahr M, Ventz S, Koopmeiners JS, Melton GB

Decreasing Opioid Addiction and Diversion Using Behavioral Economics Applied Through a Digital Engagement Solution: Protocol for a Randomized Controlled Trial

JMIR Res Protoc 2024;13:e52882

DOI: 10.2196/52882

PMID: 38457203

PMCID: 10960208

Decreasing Opioid Addiction and Diversion Using Behavioral Economics Applied Through a Digital Engagement Solution-Proposal for a Randomized Controlled Trial

  • Rubina Fatima Rizvi; 
  • Jamee Ann Schoephoerster; 
  • Sagar Satish Desphande; 
  • Michael G Usher; 
  • Andy Elaine Oien; 
  • Maya Marie Peters; 
  • Matthew Scott Loth; 
  • Matt Bahr; 
  • Steffen Ventz; 
  • Joseph Stephen Koopmeiners; 
  • Genevieve B Melton

ABSTRACT

Background:

Despite strong and growing interest in ending the ongoing opioid health crisis, there has been limited success in reducing the prevalence of opioid addiction and the number of deaths associated with opioid overdoses. One explanation for this is that existing interventions target those who are opiate-dependent but do not prevent opioid-naïve patients from becoming addicted.

Objective:

Leveraging behavioral economics at the patient level could help patients successfully use, discontinue, and dispose of their opioid medications in an acute pain setting. The primary goal of this project is to evaluate the effect of the three versions of the Opioid Management for You (OPY) tool on measures of opioid use relative to the standard of care by leveraging a pragmatic randomized controlled trial (RCT).

Methods:

A team of researchers from the Center of Learning Health System Sciences (CLHSS) at the University of Minnesota partnered with M Health Fairview (MHFV) to design, build, and test the three versions of the OPY tool: social influence, pre-commitment, and testimonial version. The tool is being built using the Epic Care Companion platform and interacts with the patient through their existing MyChart personal health record (PHR) account, and Epic patient portal, accessed through a phone app or the MyChart website. We have demonstrated feasibility with pilot data of the social influence version of the OPY app by targeting our pilot to a specific cohort of patients undergoing upper-extremity procedures. This study will use a group sequential RCT design to test the impact of this important health system initiative. Patients who meet OPY inclusion criteria will be stratified into low, intermediate, and high risk of opiate use based on their type of surgery.

Results:

The implementation of this intervention has been fully resourced by MHFV. This study is being funded and supported by the CLHSS Rapid Prospective Evaluation (RapidEval) and Digital Technology Innovation Programs. Support and coordination provided by CLHSS include the structure of engagement, survey development, data collection, statistical analysis, and dissemination The pilot was launched in February 2023 and is still running. The actual RCT is planned to start by early 2024.

Conclusions:

Through this RCT, we will test our hypothesis that patient opioid use and diverted prescription opioid availability can both be improved by information delivery applied through a behavioral economics lens via sending nudges directly to the opioid users through their PHR. Clinical Trial: NCT06124079


 Citation

Please cite as:

Rizvi RF, Schoephoerster JA, Desphande SS, Usher MG, Oien AE, Peters MM, Loth MS, Bahr M, Ventz S, Koopmeiners JS, Melton GB

Decreasing Opioid Addiction and Diversion Using Behavioral Economics Applied Through a Digital Engagement Solution: Protocol for a Randomized Controlled Trial

JMIR Res Protoc 2024;13:e52882

DOI: 10.2196/52882

PMID: 38457203

PMCID: 10960208

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