CONTEXT: Adverse childhood experiences (ACEs), substance use disorders (SUDs), and overdose are interconnected issues impacting individuals and communities at multiple levels of the social ecology and across generations. Few studies describe approaches that intentionally and simultaneously address these issues. PROGRAM: This paper examines activities of 15 sites across the country that were designed to simultaneously prevent ACEs, SUD, and overdose. This paper describes the work at the intersection as well as gaps and opportunities. Describing ways to implement intersectional programming may assist other organizations in taking similar steps in their communities. IMPLEMENTATION: From December 2020 through July 15, 2023, funded sites received technical assistance from the National Association of County and City Health Officials and the Centers for Disease Control and Prevention for 18 months to support the implementation, adaptation, and/or expansion of evidence-based programs to address ACEs, SUD, and overdose. EVALUATION: Activities were coded to identify intersectional interventions that addressed ACEs, SUD, and overdose. Most of the ACEs prevention strategies and overdose prevention priority areas/guiding principles from which communities could choose were represented. Most activities were implemented with caregivers and families and addressed ACEs through interventions to lessen harm or to promote social norms. Primary prevention and coordination of resources were the most used overdose prevention priority area/guiding principle. DISCUSSION: It is possible to address the intersection of ACEs, SUD, and overdose on a local level. Opportunities to further address the intersection include incorporating more secondary and tertiary prevention strategies, expanding economic supports, and increasing the work focused on equity.

BACKGROUND: Medications for Opioid Use Disorder (MOUD) are an effective method to treat persons with opioid use disorder (OUD). Longer treatment times are associated with better health outcomes, yet treatment retention rates remain low. This study aimed to assess patient characteristics and experiences associated with retention in treatment. METHODS: Data were from an observational cohort study of OUD treatments. Among persons receiving buprenorphine or methadone, log-binomial regression models assessed the relationship between patient characteristics and experiences and three retention outcomes: retention in any OUD treatment, retention in the index treatment (OUD treatment being administered at the time when patients were screened for study eligibility), and 6-month retention in the index treatment. RESULTS: Individuals being treated with methadone at the start of the study compared to those treated with buprenorphine were more likely to remain in their same index treatment at the 18-month follow-up (aPR = 1.35; 95 % CI = 1.11-1.65), and to have remained on their index treatment for 6-months or longer (aPR = 1.22; 95 % CI = 1.14-1.32), but were not significantly more likely to remain in any OUD treatment overall. Individuals residing five miles or less from treatment were more likely to have been retained in any OUD treatment (aPR = 1.06; 95 % CI = 1.00-1.12), to remain in their index treatment at the 18-month follow-up (aPR = 1.21; 95 % CI = 1.08-1.36), and to have remained in their index treatment for 6 months or more (aPR = 1.08; 95 % CI = 1.02-1.13). Individuals without health insurance were less likely to be retained in any OUD treatment (aPR = 0.86; 95 % CI = 0.78-0.95). CONCLUSION: The prevalence of retention in any OUD treatment was higher for individuals residing five miles or less from treatment. These findings expand on previous studies that have shown distance to and location of treatment sites can impact treatment access and retention. Lack of health insurance was also associated with lower retention in any OUD treatment in this study. Given the high burden associated with overdose deaths, it is important to understand and address barriers to retention in treatment.

BACKGROUND: Differences in availability of medications for opioid use disorder (MOUD) buprenorphine and methadone exist. Factors that may influence such differences in availability include sociodemographic characteristics but research in this area is limited. We explore the association between county-level sociodemographic factors and MOUD treatment availability. METHODS: County-level Drug Enforcement Administration (DEA) data were used to determine the presence or absence of buprenorphine treatment or opioid treatment programs (OTPs) and the level of availability of these types of treatment in a county. Hurdle models were used to examine the associations of our covariates with any MOUD treatment availability and level of available treatment. RESULTS: The odds of a county having OTP availability were higher for counties with higher percentages of non-Hispanic Black and Hispanic populations and higher drug overdose death rates. Counties with higher percentages of persons in poverty and drug overdose death rates had higher odds of maximum potential buprenorphine treatment capacity, while counties with high percentages of persons without health insurance, with disability, and rural counties had lower odds. CONCLUSIONS: There are significant differences in the county-level availability of OTPs and buprenorphine treatment. Our findings expand on prior studies illustrating that barriers to accessing treatment persist and are not evenly distributed among sociodemographic groups, further study is needed to examine if barriers of availability translate to barriers in receiving treatment. Given the escalating overdose crisis in the U.S., expanding equitable availability of MOUD is critical. Informed strategies are needed to reach areas and populations in greatest need.

BACKGROUND: COVID-19 stay-at-home orders may reduce access to substance use treatment and naloxone, an opioid overdose reversal drug. The objective of this analysis was to compare monthly trends in pharmacy-based dispensing rates of medications for opioid use disorder (MOUD) (buprenorphine and extended-release [ER] naltrexone) and naloxone in the United States during March 2019-December 2020 by age and sex. METHODS: We calculated monthly prescription dispensing rates per 100,000 persons using IQVIA New to Brand. We used Joinpoint regression to calculate monthly percent change in dispensing rates and Wilcoxon Rank Sum tests to examine differences in median monthly rates overall, and by age and sex between March 2019-December 2019 and March 2020-December 2020. RESULTS: Buprenorphine dispensing increased among those aged 40-64 years and ≥ 65 years from March 2019 to December 2020. Median rates of total ER naltrexone dispensing were lower in March 2020-December 2020 compared to March 2019-December 2019 for the total population, and for females and males. From March 2019 to December 2020, ER naltrexone dispensing decreased and naloxone dispensing increased for those aged 20-39 years. CONCLUSIONS: Dispensing ER naltrexone declined during the study period. Given the increase in substance use during the COVID-19 pandemic, maintaining equivalent access to MOUD may not be adequate to accommodate rising numbers of new patients with opioid use disorder. Access to all MOUD and naloxone could be further expanded to meet potential needs during and after the public health emergency, given their importance in preventing opioid overdose-related harms.

INTRODUCTION: Sociodemographic factors and chronic conditions associated with coronavirus disease 2019 (COVID-19) among persons with substance use disorder (PWSUD) are not well understood. We identified risk factors associated with COVID-19 among PWSUD with hospital visits. METHODS: Using the Premier Healthcare Database Special COVID-19 Release, we conducted a case-control study using ICD-10-CM codes to identify PWSUD aged 12 years and older with hospital visits for any reason during April-December 2020. Multivariable logistic regression was used to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CI) to identify factors associated with COVID-19 diagnosis among PWSUD (age, sex, race/ethnicity, U.S. Census Region, urban/rural classification, insurance payor type, comorbidities, and substance use disorder [SUD] type), and then stratified by SUD type. RESULTS: From April-December 2020, 18,298 (1.3%) of 1,429,154 persons with SUD in the database had a COVID-19 diagnosis. Among PWSUD, opioid use disorder (OUD; aOR = 1.24, 95% CI = 1.18-1.32), alcohol use disorder (AUD; aOR = 1.16, 95% CI = 1.11-1.22), cocaine or other stimulant use disorder (COUD; aOR = 1.28, 95% CI = 1.22-1.34), and multiple SUDs (aOR = 1.20, 95% CI = 1.15-1.26) were associated with higher odds of COVID-19, as were comorbidities such as chronic lower respiratory disease (aOR = 1.32, 95% CI = 1.26-1.37), chronic hepatitis (aOR = 1.45, 95% CI = 1.34-1.57), and diabetes (aOR = 1.78, 95% CI = 1.71-1.86). CONCLUSIONS: Among a sample of PWSUD, OUD, AUD, COUD, multiple SUDs, and associated comorbidities were associated with COVID-19 diagnosis. Integration of COVID-related care, care of other comorbidities, and SUD treatment may benefit PWSUD. Future studies are needed to better understand COVID-19 prevention in this population and to reduce disparities among subpopulations at increased risk.

Background: While overall opioid prescribing has been decreasing in the United States, the rates of prescribing at the county level have been variable. Previous studies show that social determinants of health (the social and economic conditions in which we live) may play a role in opioid prescribing; however, researchers have not examined this relationship across US counties. This cross-sectional study seeks to determine whether county-level sociodemographic characteristics (e.g., economic, housing, social environment, healthcare environment, and population characteristics) are associated with county level differences in opioid dispensing. Methods: Data from 2,881 counties in the United States from 2017 to 2018 were used for this study. Opioid dispensing was measured using morphine milligram equivalents (MME) per capita. Spatial error models were used to measure the association between county-level sociodemographic characteristics and MME per capita while adjusting for spatial correlation between neighboring counties. Results: In the adjusted model, counties with a higher percentage of people below the poverty line, with less than a 4-year college degree, and without health insurance were associated with higher MME dispensed per capita, as were counties with higher percentages of families headed by a single parent, persons separated or divorced, and those with disabilities. Conversely, minority race/ethnicity and rural population were associated with lower opioid dispensing. Conclusions: County-level sociodemographics can differ in their association with opioid dispensing, hence examining which county-level factors help in improving opioid prescribing, and implementing overdose prevention strategies that tackle these factors is important. © 2021