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The objective of this study was to estimate the associations of jail-initiated medication for opioid use disorder (MOUD) and patient navigation (PN) with opioid use disorder (OUD) at 6 months post-release. Three randomized trials (combined N = 330) were combined to assess whether MOUD (extended-release naltrexone or interim methadone) initiated prior to release from jail with or without PN would reduce the likelihood of a DSM-5 diagnosis of OUD 6 months post-release relative to enhanced treatment-as-usual (ETAU). Across the three studies, assignment to MOUD compared to ETAU was not associated with an OUD diagnosis at 6 months post-release (69% vs. 75%, respectively, OR = 0.67, 95% CI: 0.42 to 1.20). Similarly, PN compared to MOUD without PN was not associated with an OUD diagnosis (63% vs 77%, respectively, OR = 0.61, 95% CI: 0.27 to 1.53). Results underscore the need to further optimize the effectiveness of MOUD for patients initiating treatment in jail, beginning with an emphasis on post-release treatment adherence. [ABSTRACT FROM AUTHOR]

The article discusses an article by M. R. Larochelle and colleagues about disparities in overdose deaths. Topics include reason that the opioid overdose crisis most heavily affected non-Hispanic White people, major events that could not have been predicted at the time the article by Larochelle and colleagues was written, and lessons learned about the need for timely data on drug use patterns and overdoses to guide interventions.

Background: The National Survey on Drug Use and Health (NSDUH) estimated the prevalence of opioid use disorder (OUD) among the civilian, noninstitutionalized people aged 12 years or older in Massachusetts as 1.2% between 2015 and 2017. Accurate estimation of the prevalence of OUD is critical to the success of treatment and resource planning. Various indirect estimation approaches have been used but are subject to data availability and infrastructurerelated issues. Methods: We used 2015 data from the Massachusetts Public Health Data Warehouse (PHD) to compare the results of two approaches to estimating OUD prevalence in the Massachusetts population. First, we used a seven-dataset capture-recapture analysis under log-linear model parameterization, controlling for the source dependence and effects of age, sex, and county through stratification. Second, we applied a benchmark-multiplier method in a Bayesian framework by linking health care claims data to death certificate data assuming an extrapolation of death rates from observed untreated OUD to unobserved OUD. Results: Our estimates for OUD prevalence among Massachusetts residents (aged 18-64 years) were 4.62% (95% CI = 4.59%, 4.64%) in the capture-recapture approach and 4.29% (95% CrI = 3.49%, 5.32%) in the Bayesian model. Both estimates were approximately four times higher than NSDUH estimates. Conclusion: The synthesis of our findings suggests that the disease surveillance system misses a large portion of the population with OUD. Our study also suggests that concurrent use of multiple methods improves the justification and facilitates the triangulation and interpretation of the resulting estimates. [ABSTRACT FROM AUTHOR]