NCT07456930

Real-World Evaluation of Compl-AI for Predicting Early Medication Dropout in Opioid Use Disorder Treatment

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

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 295 (estimated)
• Sponsor: Tools4Patient · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Opioid Use Disorder

Timeline

• Start date: 2026-06-01
• Primary completion: 2026-12-01
• Completion: 2026-12-01
• First posted: 2026-03-09
• Last updated: 2026-03-18

Locations

2 sites across 1 country: United States