Abstract
Medication for Opioid Use Disorder Treatment (MOUD) has poor adherence and retention. Premature discontinuation from MOUD has significant negative health and societal consequences. Our objective is to develop machine learning and causal models to investigate how variations in treatment type influence treatment discontinuation. The findings of this research help guide evidence-based strategies for improving treatment retention.
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