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Real-World Evaluation of Compl-AI for Predicting Early Medication Dropout in Opioid Use Disorder Treatment
Sponsor: Tools4Patient
Summary
The goal of this observational study is to learn whether the Compl-AI model can accurately predict who is likely to stop their medication for opioid use disorder (MOUD) early in adults receiving real-world treatment for opioid use disorder (OUD). The main questions it aims to answer is: can the model accurately predict early discontinuation of MOUD? Because this study has no comparison groups, all participants receive their usual MOUD as part of routine care. Researchers will observe how participants engage with treatment and how well Compl-AI predicts their outcomes. Participants will complete 4 visits, including a questionnaire about personal experiences during first visit and questions about their substance use and treatment history. During the monthly study visits, the researchers will record in particular the attendance at MOUD medication visits, the medication adherence and any treatment discontinuation.
Official title: Real-World Assessment of Compl-AI in Predicting Early Discontinuation of Medication for Treatment of Opioid Use Disorder (MOUD) in Community and Specialty Treatment Programs
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
295
Start Date
2026-06-01
Completion Date
2026-12
Last Updated
2026-03-18
Healthy Volunteers
No
Conditions
Locations (2)
SOAP MAT, LLC - Central
San Diego, California, United States
SOAP MAT, LLC - Vista
Vista, California, United States