Characterizing opioid-involved overdose risk in local communities: An opioid overdose vulnerability assessment across Indiana, 2017

Barriers to opioid use disorder treatment among people who use drugs in the rural United States: A qualitative, multi-site study

BACKGROUND

In 2020, 2.8 million people required substance use disorder (SUD) treatment in nonmetropolitan or 'rural' areas in the U.S. Among this population, only 10% received SUD treatment from a specialty facility, and 1 in 500 received medication for opioid use disorder (MOUD). We explored the context surrounding barriers to SUD treatment in the rural United States.

METHODS

We conducted semi-structured, in-depth interviews from 2018 to 2019 to assess barriers to SUD treatment among people who use drugs (PWUD) across seven rural U.S. study sites. Using the social-ecological model (SEM), we examined individual, interpersonal, organizational, community, and policy factors contributing to perceived barriers to SUD treatment. We employed deductive and inductive coding and analytical approaches to identify themes. We also calculated descriptive statistics for participant characteristics and salient themes.

RESULTS

Among 304 participants (55% male, mean age 36 years), we identified barriers to SUD treatment in rural areas across SEM levels. At the individual/interpersonal level, relevant themes included: fear of withdrawal, the need to "get things in order" before entering treatment, close-knit communities and limited confidentiality, networks and settings that perpetuated drug use, and stigma. Organizational-level barriers included: strict facility rules, treatment programs managed like corrections facilities, lack of gender-specific treatment programs, and concerns about jeopardizing employment. Community-level barriers included: limited availability of treatment in local rural communities, long distances and limited transportation, waitlists, and a lack of information about treatment options. Policy-level themes included insurance challenges and system-imposed barriers such as arrest and incarceration.

CONCLUSION

Our findings highlight multi-level barriers to SUD treatment in rural U.S. communities. Salient barriers included the need to travel long distances to treatment, challenges to confidentiality due to small, close-knit communities where people are highly familiar with one another, and high-threshold treatment program practices. Our findings point to the need to facilitate the elimination of treatment barriers at each level of the SEM in rural America.

Spatial access to buprenorphine-waivered prescribers in the HEALing communities study: Enhanced 2-step floating catchment area analyses in Massachusetts, Ohio, and Kentucky

INTRODUCTION

The opioid overdose epidemic continues to impact a large swath of the population in the US. Medications for opioid use disorders (MOUD) are an effective resource to combat the epidemic; however, there is limited research on MOUD treatment access that accounts for both supply of and demand for services. We aimed to examine access to buprenorphine prescribers in the HEALing Communities Study (HCS) Wave 2 communities in Massachusetts, Ohio, and Kentucky during 2021, and the association between buprenorphine access and opioid-related incidents, specifically fatal overdoses and opioid-related responses by emergency medical services (EMS).

METHODS

We calculated Enhanced 2-Step Floating Catchment Area (E2SFCA) accessibility indices for each state, as well as Wave 2 communities in each state, based on the location of providers (buprenorphine-waivered clinicians from the US Drug Enforcement Agency Active Registrants database), population-weighted centroids at the census block group level, and catchment areas defined by the state or community's average commute time. In advance of intervention initiation, we quantified the opioid-related risk environment of communities. We assessed gaps in services by using bivariate Local Moran's I analysis, incorporating accessibility indices and opioid-related incident data.

RESULTS

Massachusetts Wave 2 HCS communities had the highest rates of buprenorphine prescribers per 1000 patients (median: 165.8) compared to Kentucky (38.8) and Ohio (40.1). While urban centers in all three states had higher E2SFCA index scores compared to rural communities, we observed that suburban communities often had limited access. Through bivariate Local Moran's I analysis, we identified numerous locations with low buprenorphine access surrounded by high opioid-related incidents, particularly in communities that surrounded Boston, Massachusetts; Columbus, Ohio; and Louisville, Kentucky.

CONCLUSION

Rural communities demonstrated a great need for additional access to buprenorphine prescribers. However, policymakers should also direct attention toward suburban communities that have experienced significant increases in opioid-related incidents.

Spatial machine learning for predicting physical inactivity prevalence from socioecological determinants in Chicago, Illinois, USA

The increase in physical inactivity prevalence in the USA has been associated with neighborhood characteristics. While several studies have found an association between neighborhood and health, the relative importance of each component related to physical inactivity or how this value varies geographically (i.e., across different neighborhoods) remains unexplored. This study ranks the contribution of seven socioecological neighborhood factors to physical inactivity prevalence in Chicago, Illinois, using machine learning models at the census tract level, and evaluates their predictive capabilities. First, we use geographical random forest (GRF), a recently proposed nonlinear machine learning regression method that assesses each predictive factor's spatial variation and contribution to physical inactivity prevalence. Then, we compare the predictive performance of GRF to geographically weighted artificial neural networks, another recently proposed spatial machine learning algorithm. Our results suggest that poverty is the most important determinant in the Chicago tracts, while on the other hand, green space is the least important determinant in the rise of physical inactivity prevalence. As a result, interventions can be designed and implemented based on specific local circumstances rather than broad concepts that apply to Chicago and other large cities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10109-023-00415-y.

Opioid-Involved Overdose Vulnerability in Wyoming: Measuring Risk in a Rural Environment

BACKGROUND

Between 2009 and 2019 opioid-involved fatal overdose rates increased by 45% and the average opioid dispensing rate in Wyoming was higher than the national average. The opioid crisis is shaped by a complex set of socioeconomic, geopolitical, and health-related variables. We conducted a vulnerability assessment to identify Wyoming counties at higher risk of opioid-related harm, factors associated with this risk, and areas in need of overdose treatment access to inform priority responses.

METHODS

We compiled 2016 to 2018 county-level aggregated and de-identified data. We created risk maps and ran spatial analyses in a geographic information system to depict the spatial distribution of overdose-related measures. We used addresses of opioid treatment programs and buprenorphine providers to develop drive-time maps and ran 2-step floating catchment area analyses to measure accessibility to treatment. We used a straightforward and replicable weighted ranks approach to calculate final county vulnerability scores and rankings from most to least vulnerable.

FINDINGS

We found Hot Springs, Carbon, Natrona, Fremont, and Sweetwater Counties to be most vulnerable to opioid-involved overdose fatalities. Opioid prescribing rates were highest in Hot Springs County (97 per 100 persons), almost two times the national average (51 per 100 persons). Statewide, there were over 90 buprenorphine-waivered providers, however accessibility to these clinicians was limited to urban centers. Most individuals lived further than a four-hour round-trip drive to the nearest methadone treatment program.

CONCLUSIONS

Identifying Wyoming counties with high opioid overdose vulnerabilities and limited access to overdose treatment can inform public health and harm reduction responses.