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

NCT07456930 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 295

Last updated 2026-03-18

No results posted yet for this study

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

Sponsors & Collaborators

  • Tools4Patient

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2026-12-31
Completion
2026-12-31

Countries

  • United States

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07456930 on ClinicalTrials.gov