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

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.

NCT Number	NCT07456930
Lead Sponsor	Tools4Patient
Conditions	Opioid Use Disorder
Enrollment	295 participants
Start Date	2026-06-01
Primary Completion	2026-12 (estimated)
Study Completion	2026-12 (estimated)
Updated on ClinicalTrials.gov	2026-03-18