Background: This study investigates the impact of workforce diversity, specifically staff identified as Black/African American, on retention in opioid use disorder (OUD) treatment, aiming to enhance patient outcomes. Employing a novel machine learning technique known as 'causal forest,' we explore heterogeneous treatment effects on retention.
Methods: We relied on four waves of the National Drug Abuse Treatment System Survey (NDATSS), a nationally representative longitudinal dataset of treatment programs. We analyzed OUD program data from the years 2000, 2005, 2014 and 2017 (n = 627). Employing the 'causal forest' method, we analyzed the heterogeneity in the relationship between workforce diversity and retention in OUD treatment. Interviews with program directors and clinical supervisors provided the data for this study.
Results: The results reveal diversity-related variations in the association with retention across 61 out of 627 OUD treatment programs (less than 10%). These programs, associated with positive impacts of workforce diversity, were more likely private-for-profit, newer, had lower percentages of Black and Latino clients, lower staff-to-client ratios, higher proportions of staff with graduate degrees, and lower percentages of unemployed clients.
Conclusions: While workforce diversity is crucial, our findings underscore that it alone is insufficient for improving retention in addiction health services research. Programs with characteristics typically linked to positive outcomes are better positioned to maximize the benefits of a diverse workforce in client retention. This research has implications for policy and program design, guiding decisions on resource allocation and workforce diversity to enhance retention rates among Black clients with OUDs.
Keywords: Causal Forest; Heterogeneous Treatment Effect; Opioid Use Disorder; Treatment Retention; Workforce Diversity.