Analyzing national and state opioid abuse treatment completion with multilevel modeling

Abstract

The misuse of opioids has become a national public health emergency in the United States. Successfully completing a program of treatment at a substance abuse treatment facility is associated with better long-term outcomes, but a significant portion of opioid use patients are discharged without successfully completing treatment. The objective of this study is to evaluate factors associated with treatment success. We used the Treatment Episodes Datasets: Discharges (TEDS-D) dataset, a national sample of discharges from substance abuse treatment centers, and the National Survey of Substance Abuse Treatment Services (N-SSATS) dataset, an annual survey of all known substance use treatment facilities, for the years 2013 and 2014. A random slope, random intercept multilevel model was used to estimate the effects of patient- and state-level variables on treatment completion. We find that a patient is more likely to complete treatment if that patient is older, employed, has private insurance, waited less time before entering treatment, is not receiving medication-assisted treatment, and is in residential care. In addition, we find that patients living in with states with higher levels of Vivitrol adoption are more likely to complete treatment. Our findings could encourage policymakers and treatment facilities to consider prioritizing Vivitrol adoption. At the same time, our results demonstrate substantial variation of predictors across states and suggest the need for further research into the relationship between state contexts and the predictors of successful opioid use treatment.