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

N/ANot Yet RecruitingNCT07456930

Tools4Patient295 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

295

Conditions

Opioid Use Disorder

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Ability to understand and provide written informed consent. * Male and female participant 18 years of age at the time of consent. * Participant with OUD based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V). * Eligible to receive MOUD per site standard of care or currently receiving MOUD initiated prior to study enrollment. Exclusion Criteria: * Cognitive impairment that precludes the ability to provide written informed consent. * Already enrolled in another study/program.

Locations (2)

Outcomes

Primary Outcomes

Proportion of attended MOUD medication visits

Time frame: Observation period will be three (3) months.

Proportion of prescribed doses taken