Unknown

Dataset Information

0

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


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. Further, 1 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 3 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 for Learning Health System Sciences (CLHSS) at the University of Minnesota partnered with M Health Fairview to design, build, and test the 3 versions of the OPY tool: social influence, precommitment, and testimonial version. The tool is being built using the Epic Care Companion (Epic Inc) platform and interacts with the patient through their existing MyChart (Epic Systems Corporation) personal health record 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

This study is being funded and supported by the CLHSS Rapid Prospective Evaluation and Digital Technology Innovation Programs, and M Health Fairview. Support and coordination provided by CLHSS include the structure of engagement, survey development, data collection, statistical analysis, and dissemination. The project was initially started in August 2022. The pilot was launched in February 2023 and is still running, with the data last counted in August 2023. 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 personal health record.

Trial registration

ClinicalTrials.gov NCT06124079; https://clinicaltrials.gov/study/NCT06124079.

International registered report identifier (irrid)

PRR1-10.2196/52882.

SUBMITTER: Rizvi RF 

PROVIDER: S-EPMC10960208 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Rizvi Rubina Fatima RF   Schoephoerster Jamee Ann JA   Desphande Sagar Satish SS   Usher Michael M   Oien Andy Elaine AE   Peters Maya Marie MM   Loth Matthew Scott MS   Bahr Matthew William MW   Ventz Steffen S   Koopmeiners Joseph Stephen JS   Melton Genevieve B GB  

JMIR research protocols 20240308


<h4>Background</h4>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. Further, 1 explanation for this is that existing interventions target those who are opiate-dependent but do not prevent opioid-naïve patients from becoming addicted.<h4>Objective</h4>Leveraging behavioral economics at the patient level could help patients successf  ...[more]

Similar Datasets

| 2321206 | ecrin-mdr-crc
| S-EPMC10337375 | biostudies-literature
| S-EPMC9264428 | biostudies-literature
| S-EPMC3685876 | biostudies-literature
| S-EPMC8168526 | biostudies-literature
| S-EPMC10406162 | biostudies-literature
| S-EPMC5085883 | biostudies-literature
2021-04-25 | GSE171683 | GEO
| S-EPMC3516178 | biostudies-literature
| S-EPMC6368898 | biostudies-literature