Effect of the Communities That HEAL intervention on receipt of behavioral therapies for opioid use disorder: A cluster randomized wait-list controlled trial

Elsevier

Available online 5 April 2024, 111286

Drug and Alcohol DependenceAuthor links open overlay panel, , , , , , , , , , , , , , , , , , , …HIGHLIGHTS•

Evidence-based practices to reduce opioid overdose deaths implemented in 67 communities.

Outpatient behavioral health services are key element of opioid addiction treatment.

Similar receipt of behavioral services in control and intervention communities.

More research needed to test the impact of comprehensive, community-driven interventions.

ABSTRACTBackground

The U.S. opioid overdose crisis persists. Outpatient behavioral health services (BHS) are essential components of a comprehensive response to opioid use disorder and overdose fatalities. The Helping End Addiction Long-Term (HEALing) Communities Study developed the Communities That HEAL (CTH) intervention to reduce opioid overdose deaths in 67 communities in Kentucky, Ohio, New York, and Massachusetts through the implementation of evidence-based practices (EBPs), including BHS. This paper compares the rate of individuals receiving outpatient BHS in Wave 1 intervention communities (n = 34) to waitlisted Wave 2 communities (n = 33).

Methods

Medicaid data included individuals ≥18 years of age receiving any of five BHS categories: intensive outpatient, outpatient, case management, peer support, and case management or peer support. Negative binomial regression models estimated the rate of receiving each BHS for Wave 1 and Wave 2. Effect modification analyses evaluated changes in the effect of the CTH intervention between Wave 1 and Wave 2 by research site, rurality, age, sex, and race/ethnicity.

Results

No significant differences were detected between intervention and waitlisted communities in the rate of individuals receiving any of the five BHS categories. None of the interaction effects used to test the effect modification were significant.

Conclusions

Several factors should be considered when interpreting results—no significant intervention effects were observed through Medicaid claims data, the best available data source but limited in terms of capturing individuals reached by the intervention. Also, the 12-month evaluation window may have been too brief to see improved outcomes considering the time required to stand-up BHS.

Section snippetsINTRODUCTION

The United States continues to experience an unprecedented drug overdose epidemic, with synthetic opioids—primarily fentanyl—involved in the majority of overdose deaths (Hoots, 2021). Provisional national data from the National Center for Health Statistics project more than 108,000 overdose deaths for the 12-month period ending November 2022, with approximately 81,000 overdose deaths involving opioids (Ahmad et al., 2023). Sociodemographic disparities in fatal overdoses are widening, with rates

METHODS

Methods are summarized in accordance with the Consolidated Standards of Reporting Trials guidelines (Schulz et al., 2010). The CONSORT checklist and flow diagram are included in the supplemental files.

Baseline Characteristics

Baseline characteristics used in the constrained randomization (rurality, rate of opioid overdose deaths, and population) are displayed in Table 1 and support expected balance between the study arms. The baseline distribution of age, sex, and race/ethnicity of residents 18 years of age and older were similar between Wave 1 and Wave 2. Wave 1 had a slightly higher percentage of non-Hispanic Black individuals than Wave 2 (16.4% versus 14.5%), and Wave 2 had a slightly higher percentage of

DISCUSSION

The present study investigated whether the CTH intervention increased rates of receipt for behavioral therapy interventions among adult beneficiaries of Medicaid with OUD—a population at higher risk for opioid-related overdose and overdose fatalities. Using the HCS multisite, parallel-group, community-level cluster randomized, unblinded, waitlist-controlled comparison design, we compared rates of receipt for intensive outpatient, outpatient, case management, peer support, and case management or

Role of Funding Source

This work was supported by the following National Institutes of Health grants: RTI International: UM1DA049394, University of Kentucky: UM1DA049406, Boston Medical Center: UM1DA049412, Columbia University: UM1DA049415, Ohio State University: UM1DA049417. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, the Substance Abuse and Mental Health Services Administration or the NIH HEAL Initiative. Dr.

CRediT authorship contribution statement

Gary A. Zarkin: Writing – review & editing. Derek Blevins: Writing – review & editing. Kristin Woodlock: Conceptualization. Carolina Barbosa: Writing – review & editing. Jeffrey Samet: Writing – review & editing. Lindsay Cogan: Writing – review & editing, Data curation. Bridget Freisthler: Writing – review & editing. Deborah Chassler: Writing – review & editing. Angela Taylor: Writing – review & editing. Nathan Vandergrift: Writing – review & editing, Methodology, Conceptualization. Kat Asman:

Declaration of Competing Interest

Michelle Lofwall has served as a scientific consultant for treatments in development for substance use disorders to Journey Colab, Titan, Braeburn, and Berkshire Biomedical in the last three years. Roger Weiss has consulted to Alkermes.

Acknowledgements

The authors wish to acknowledge the participation of the HEALing Communities Study communities, coalitions, partner organizations and agencies, and Community Advisory Boards, as well as the state government officials who partnered with us on this study.

Declarations of Interest

In last three years, MRL has served as a scientific consultant for treatments in development for substance use disorders to Journey Colab, Titan, Braeburn, and Berkshire Biomedical. RW has consulted to Alkermes.

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