Predictors of premature treatment termination in a large residential addiction medicine program

Abstract

BackgroundWhile inpatient programs are a common setting for addiction treatment, patients' premature termination is a major concern. Predicting premature treatment termination has the potential to substantially improve patient outcomes by identifying high-risk profiles and suggesting care paths that might reduce dropout. The current study examined the predictors of premature termination from an inpatient addiction medicine service. MethodsIn 1082 patients admitted to a large inpatient addiction medicine service, we used intake assessments of severity of alcohol use disorder, illicit drug use disorder, post-traumatic stress disorder (PTSD), anxiety disorders, and major depressive disorder to predict planned termination (n = 922) or premature termination (n = 160). We used two complementary analytic approaches—traditional binary logistic regression and a data-driven latent profile analysis (LPA). ResultsBinary logistic regression revealed that alcohol use severity, illicit drug use severity, and PTSD severity significantly predicted termination status, although alcohol use severity notably exhibited an inverse relationship. The LPA revealed four distinct profiles, with one profile exhibiting a significantly higher rate of premature termination and another exhibiting a significantly lower rate of premature termination. The high-risk profile was characterized by high drug severity, high comorbid psychopathology (PTSD, depression, and anxiety symptoms), but low alcohol severity. The low-risk profile was characterized by high alcohol severity, but low drug use and low comorbid psychopathology. ConclusionsThese results provide converging evidence that illicit drug severity and psychiatric severity, and particularly PTSD, were associated with premature termination. Moreover, the LPA revealed distinct latent subgroups of patients with meaningfully higher and lower risk of premature termination, suggesting that addiction services should develop strategies for identifying high-risk individuals or develop care paths for high-risk symptom clusters. Approaches that are trauma-informed or otherwise focus on the management of comorbid psychiatric conditions may be particularly appropriate for reducing premature termination.