Cost of start-up activities to implement a community-level opioid overdose reduction intervention in the HEALing Communities Study.

BACKGROUND: Communities That HEAL (CTH) is a novel, data-driven community-engaged intervention designed to reduce opioid overdose deaths by increasing community engagement, adoption of an integrated set of evidence-based practices, and delivering a communications campaign across healthcare, behavioral-health, criminal-legal, and other community-based settings. The implementation of such a complex initiative requires up-front investments of time and other expenditures (i.e., start-up costs). Despite the importance of these start-up costs in investment decisions to stakeholders, they are typically excluded from cost-effectiveness analyses. The objective of this study is to report a detailed analysis of CTH start-up costs pre-intervention implementation and to describe the relevance of these data for stakeholders to determine implementation feasibility. METHODS: This study is guided by the community perspective, reflecting the investments that a real-world community would need to incur to implement the CTH intervention. We adopted an activity-based costing approach, in which resources related to hiring, training, purchasing, and community dashboard creation were identified through macro- and micro-costing techniques from 34 communities with high rates of fatal opioid overdoses, across four states-Kentucky, Massachusetts, New York, and Ohio. Resources were identified and assigned a unit cost using administrative and semi-structured-interview data. All cost estimates were reported in 2019 dollars. RESULTS: State-level average and median start-up cost (representing 8-10 communities per state) were $268,657 and $175,683, respectively. Hiring and training represented 40%, equipment and infrastructure costs represented 24%, and dashboard creation represented 36% of the total average start-up cost. Comparatively, hiring and training represented 49%, purchasing costs represented 18%, and dashboard creation represented 34% of the total median start-up cost. CONCLUSION: We identified three distinct CTH hiring models that affected start-up costs: hospital-academic (Massachusetts), university-academic (Kentucky and Ohio), and community-leveraged (New York). Hiring, training, and purchasing start-up costs were lowest in New York due to existing local infrastructure. Community-based implementation similar to the New York model may have lower start-up costs due to leveraging of existing infrastructure, relationships, and support from local health departments.

Motivation and context of concurrent stimulant and opioid use among persons who use drugs in the rural United States: a multi-site qualitative inquiry.

BACKGROUND: In recent years, stimulant use has increased among persons who use opioids in the rural U.S., leading to high rates of overdose and death. We sought to understand motivations and contexts for stimulant use among persons who use opioids in a large, geographically diverse sample of persons who use drugs (PWUD) in the rural settings. METHODS: We conducted semi-structured individual interviews with PWUD at 8 U.S. sites spanning 10 states and 65 counties. Content areas included general substance use, injection drug use, changes in drug use, and harm reduction practices. We used an iterative open-coding process to comprehensively itemize and categorize content shared by participants related to concurrent use. RESULTS: We interviewed 349 PWUD (64% male, mean age 36). Of those discussing current use of stimulants in the context of opioid use (n = 137, 39%), the stimulant most used was methamphetamine (78%) followed by cocaine/crack (26%). Motivations for co-use included: 1) change in drug markets and cost considerations; 2) recreational goals, e.g., seeking stronger effects after heightened opioid tolerance; 3) practical goals, such as a desire to balance or alleviate the effects of the other drug, including the use of stimulants to avoid/reverse opioid overdose, and/or control symptoms of opioid withdrawal; and 4) functional goals, such as being simultaneously energized and pain-free in order to remain productive for employment. CONCLUSION: In a rural U.S. cohort of PWUD, use of both stimulants and opioids was highly prevalent. Reasons for dual use found in the rural context compared to urban studies included changes in drug availability, functional/productivity goals, and the use of methamphetamine to offset opioid overdose. Education efforts and harm reduction services and treatment, such as access to naloxone, fentanyl test strips, and accessible drug treatment for combined opioid and stimulant use, are urgently needed in the rural U.S. to reduce overdose and other adverse outcomes.

Public Health Interventions and Overdose-Related Outcomes Among Persons With Opioid Use Disorder.

Importance: Given the high number of opioid overdose deaths in the US and the complex epidemiology of opioid use disorder (OUD), systems models can serve as a tool to identify opportunities for public health interventions. Objective: To estimate the projected 3-year association between public health interventions and opioid overdose-related outcomes among persons with OUD. Design, Setting, and Participants: This decision analytical model used a simulation model of the estimated US population aged 12 years and older with OUD that was developed and analyzed between January 2019 and December 2023. The model was parameterized and calibrated using 2019 to 2020 data and used to estimate the relative change in outcomes associated with simulated public health interventions implemented between 2021 and 2023. Main Outcomes and Measures: Projected OUD and medications for OUD (MOUD) prevalence in 2023 and number of nonfatal and fatal opioid-involved overdoses among persons with OUD between 2021 and 2023. Results: In a baseline scenario assuming parameters calibrated using 2019 to 2020 data remained constant, the model projected more than 16 million persons with OUD not receiving MOUD treatment and nearly 1.7 million persons receiving MOUD treatment in 2023. Additionally, the model projected over 5 million nonfatal and over 145 000 fatal opioid-involved overdoses among persons with OUD between 2021 and 2023. When simulating combinations of interventions that involved reducing overdose rates by 50%, the model projected decreases of up to 35.2% in nonfatal and 36.6% in fatal opioid-involved overdoses among persons with OUD. Interventions specific to persons with OUD not currently receiving MOUD treatment demonstrated the greatest reduction in numbers of nonfatal and fatal overdoses. Combinations of interventions that increased MOUD initiation and decreased OUD recurrence were projected to reduce OUD prevalence by up to 23.4%, increase MOUD prevalence by up to 137.1%, and reduce nonfatal and fatal opioid-involved overdoses among persons with OUD by 6.7% and 3.5%, respectively. Conclusions and Relevance: In this decision analytical model study of persons with OUD, findings suggested that expansion of evidence-based interventions that directly reduce the risk of overdose fatality among persons with OUD, such as through harm reduction efforts, could engender the highest reductions in fatal overdoses in the short-term. Interventions aimed at increasing MOUD initiation and retention of persons in treatment projected considerable improvement in MOUD and OUD prevalence but could require a longer time horizon for substantial reductions in opioid-involved overdoses.

County-level factors associated with a mismatch between opioid overdose mortality and availability of opioid treatment facilities.

BACKGROUND: Opioid overdose deaths in the United States remain a major public health crisis. Little is known about counties with high rates of opioid overdose mortality but low availability of opioid use disorder (OUD) treatment facilities. We sought to identify characteristics of United States (US) counties with high rates of opioid overdose mortality and low rates of opioid treatment facilities. METHODS: Rates of overdose mortality from 3,130 US counties were compared with availability of opioid treatment facilities that prescribed or allowed medications for OUD (MOUD), from 2018-2019. The outcome variable, "risk-availability mismatch" county, was a binary indicator of a high rate (above national average) of opioid overdose mortality with a low (below national average) rate of opioid treatment facilities. Covariates of interest included county-level sociodemographics and rates of insurance, unemployment, educational attainment, poverty, urbanicity, opioid prescribing, depression, heart disease, Gini index, and Theil index. Multilevel logistic regression, accounting for the clustering of counties within states, was used to determine associations with being a "risk-availability mismatch" county. RESULTS: Of 3,130 counties, 1,203 (38.4%) had high rates of opioid overdose mortality. A total of 1,098 counties (35.1%) lacked a publicly-available opioid treatment facility in 2019. In the adjusted model, counties with an additional 1% of: white residents (odds ratio, OR, 1.02; 95% CI, 1.01-1.03), unemployment (OR, 1.11; 95% CI, 1.05-1.19), and residents without insurance (OR, 1.04; 95% CI, 1.01-1.08) had increased odds of being a mismatch county. Counties that were metropolitan (versus non-metropolitan) had an increased odds of being a mismatch county (OR, 1.85; 95% CI, 1.45-2.38). CONCLUSION: Assessing mismatch between treatment availability and need provides useful information to characterize counties that require greater public health investment. Interventions to reduce overdose mortality are unlikely to be effective if they do not take into account diverse upstream factors, including sociodemographics, disease burden, and geographic context of communities.

Physiologically based modeling reveals different risk of respiratory depression after fentanyl overdose between adults and children.

Despite a rapid increase in pediatric mortality rate from prescription and illicit opioids, there is limited research on the dose-dependent impact of opioids on respiratory depression in children, the leading cause of opioid-associated death. In this article, we extend a previously developed translational model to cover pediatric populations by incorporating age-dependent pharmacokinetic, pharmacodynamic, and physiological changes compared to adults. Our model reproduced previous perioperative clinical findings that adults and children have similar risk of respiratory depression at the same plasma fentanyl concentration when specific endpoints (minute ventilation, CO2 tension in the blood) were used. However, our model points to a potential caveat that, in a perioperative setting, routine use of mechanical ventilation and supplemental oxygen maintained the blood and tissue oxygen partial pressures in patients and prevented the use of oxygen-related endpoints to evaluate the consequences of respiratory depression. In a community setting when such oxygenation procedures are not immediately available, our model suggests that the higher oxygen demand and reduced cerebrovascular reactivity could make children more susceptible to severe hypoxemia and brain hypoxia, even with the same plasma fentanyl concentration as adults. Our work indicates that when developing intervention strategies to protect children from opioid overdose in a community setting, these pediatric-specific factors may need to be considered.

Trends in pediatric prescription-opioid overdoses in U.S. emergency departments from 2008-2020: An epidemiologic study of pediatric opioid overdose ED visits.

BACKGROUND: Opioid overdose was declared a public health emergency in the United States, but much of the focus has been on adults. Child and adolescent exposure and access to unused prescription-opioid medications is a big concern. More research is needed on the trend of pediatric (age 0-17) prescription-opioid overdose emergency department (ED) visits in the United States, particularly during the COVID-19 pandemic year. METHODS: This retrospective epidemiological study used the 2008-2020 Nationwide Emergency Department Sample to provide a national estimate of ED visits related to prescription-opioid overdose. Inclusion criteria were 0-17-year-old patients treated at the ED due to prescription-opioid overdose. Eligible visits were identified if their medical records included any administrative billing codes for prescription-opioid overdose. National estimates were broken down by age groups, sex, geographic region, primary payer, median household income by zip code, ED disposition, and hospital location/teaching status. Incidence rate per 100,000 U.S. children was calculated for age groups, sex, and geographic region. RESULTS: Overall, the prescription-opioid overdose ED visits for patients from 0-17 years old in the United States decreased by 22% from 2008 to 2019, then increased by 12% in 2020. Most patients were discharged to home following their ED visit; however, there was a 42% increase in patients admitted from 2019 to 2020. The prescription-opioid overdose rate per 100,000 U.S. children was highest in the 0 to 1 and 12 to 17 age groups, with the 12 to 17 group increasing by 27% in 2020. ED visits in the West and Midwest saw prescription-opioid visits increase by 58% and 20%, respectively, from 2019-2020. CONCLUSIONS: Prescription-opioid overdose ED visits among U.S. children and adolescents decreased over the past decade until 2019. However, there was a substantial increase in ED visits from 2019 to 2020, suggesting the potential impact due to the then-emerging COVID-19 pandemic. Findings suggest focusing on young children and adolescents to reduce further prescription-opioid overdoses in the United States.