Disparities in expected driving time to opioid treatment and treatment completion: findings from an exploratory study

Al-Ibrahim, Abdullah; Marsh, Jeanne C.; Amaro, Hortensia; Kong, Yinfei; Khachikian, Tenie; Guerrero, Erick G.

doi:10.1186/s12913-022-07886-7

Cited by 5 publications

(4 citation statements)

References 30 publications

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“…These "high minority" programs also tend to be located in lower income and under-resourced minority communities [53][54][55]. Worse outcomes in highly diverse programs may therefore be explained by factors, such as low-capacity programs serving high-service need clients (clients with mental health, employment, and childcare service needs) [56].…”

Section: Discussionmentioning

confidence: 99%

Workforce Diversity and disparities in wait time and retention among opioid treatment programs

Guerrero¹,

Kong

Frimpong

et al. 2022

Subst Abuse Treat Prev Policy

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Background Workforce diversity is a key strategy to improve treatment engagement among members of racial and ethnic minority groups. In this study, we seek to determine whether workforce diversity plays a role in reducing racial and ethnic differences in wait time to treatment entry and retention in different types of opioid use disorder treatment programs. Methods We conducted comparative and predictive analysis in a subsample of outpatient opioid treatment programs (OTPs), who completed access and retention survey questions in four waves of the National Drug Abuse Treatment System Survey (162 OTPs in 2000, 173 OTPs in 2005, 282 OTPs in 2014, and 300 OTPs in 2017). We sought to assess the associations between workforce diversity on wait time and retention, accounting for the role of Medicaid expansion and the moderating role of program ownership type (i.e., public, non-profit, for-profit) among OTPs located across the United States. Results We found significant differences in wait time to treatment entry and retention in treatment across waves. Average number of waiting days decreased in 2014 and 2017; post Medicaid expansion per the Affordable Care Act, while retention rates varied across years. Key findings show that programs with high diversity, measured by higher percent of African American staff and a higher percent of African American clients, were associated with longer wait times to enter treatment, compared to low diversity programs. Programs with higher percent of Latino staff and a higher percent of Latino clients were associated with lower retention in treatment compared with low diversity programs. However, program ownership type (public, non-profit and for-profit) played a moderating role. Public programs with higher percent of African American staff were associated with lower wait time, while non-profit programs with higher percent of Latino staff were related to higher retention. Conclusions Findings show decreases in wait time over the years with significant variation in retention during the same period. Concordance in high workforce and client diversity was associated with higher wait time and lower retention. But these relations inverted (low wait time and high retention) in public and non-profit programs with high staff diversity. Findings have implications for building resources and service capacity among OTPs that serve a higher proportion of minority clients.

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Section: Discussionmentioning

confidence: 99%

Workforce Diversity and disparities in wait time and retention among opioid treatment programs

Guerrero¹,

Kong

Frimpong

et al. 2022

Subst Abuse Treat Prev Policy

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“…Prior studies examining transportation barriers for OUD have investigated differences in travel time by car or public transit between proxies for individual treatment need and treatment services . A few studies have demonstrated the impact of distance or travel time by car to OUD treatment and adverse outcomes, with 1 of these studies assessing the impact by individual demographics . However, these studies have not integrated the following 2 key features of travel burdens.…”

Section: Introductionmentioning

confidence: 99%

“… 5 , 6 , 7 , 8 , 9 , 10 A few studies have demonstrated the impact of distance or travel time by car to OUD treatment and adverse outcomes, with 1 of these studies assessing the impact by individual demographics. 11 , 12 , 13 However, these studies have not integrated the following 2 key features of travel burdens. First, the hours of operation in OTPs introduce constraints to accessing services and require awareness of the variation in transit schedules.…”

Section: Introductionmentioning

confidence: 99%

Accessibility of Opioid Treatment Programs Based on Conventional vs Perceived Travel Time Measures

Kim,

Lee,

Thornhill

et al. 2024

JAMA Netw Open

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ImportanceTransportation barriers have long been associated with poorer health outcomes; this burden is especially acute for individuals with opioid use disorder (OUD), a chronic disease often associated with low socioeconomic status. Conventional travel time analyses may not fully account for experiential components of travel, thereby understating the true travel burden and overstating treatment accessibility to opioid treatment programs (OTPs).ObjectiveTo develop a metric of feels-like accessibility for those using public transit to access OTPs that accounts for the realistic travel burden on individuals with OUD.Design, Setting, and ParticipantsThis cross-sectional study integrated high-resolution transit schedules and operating hours of OTPs to measure feels-like accessibility. Feels-like accessibility considers the differential outcomes of out-of-vehicle travel components and more realistically reflects individuals’ transportation burden than conventional accessibility measures. Gini indices and spatial regression models were used to investigate inequities in accessibility. Geocoded data for residential addresses of 1018 overdose fatalities in Connecticut in 2019 were used as a proxy for the treatment needs of individuals with OUD. Data were analyzed between May and August 2023.Main Outcomes and MeasuresConventional and feels-like accessibility scores.ExposuresFluctuations in public transit frequencies over the course of the day and the limited operating hours of the OTPs.ResultsOf the 1018 individuals in the study, the mean (SD) age at death was 43.7 (12.6) years, 784 individuals (77%) were men, 111 (11%) were African American, and 889 (87%) were White, with other racial and ethnic categories including 18 individuals (2%). A total of 264 individuals in the sample (26%) could not access an OTP within 180 minutes. For those who could access these facilities, the average 1-way travel time was 45.6 minutes, with individuals spending approximately 70% of their trip duration on out-of-vehicle travel components. The conventional accessibility metric underestimates individuals’ travel burden to OTPs as well as the inequity in accessibility compared with the feels-like accessibility metric. For example, the median (range) conventional accessibility score, defined as the number of OTPs within 120 minutes of transit travel time, was 5.0 (0.0-17.0); the median (range) feels-like accessibility score, defined as the number of OTPs within 120 minutes of transit travel time weighted to account for in- and out-of-vehicle segments, was 1.0 (0.0-10.0). There is a considerable temporal variation in travel time and accessibility depending on the departure times.Conclusions and RelevanceIn this cross-sectional study of travel burdens, the calculated feels-like accessibility scores, which consider the differential outcomes of out-of-vehicle travel components (eg, walking and waiting), could better and more realistically reflect passengers’ transportation burden. Policy recommendations derived from the conventional accessibility metric could be misleading, and decision-makers should use feels-like accessibility metrics that adequately capture individuals’ travel burdens. In the context of access to OTPs, the findings from this study suggest that opening new OTP sites to address gaps in access due to distance to services or extending hours of operation at existing sites may ameliorate the travel burden for individuals.

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“…Following publication of the original article [ 1 ], the authors identified an error in the third sentence in the Results section of the Abstract.…”

mentioning

confidence: 99%

Correction to: Disparities in expected driving time to opioid treatment and treatment completion: findings from an exploratory study

Al-Ibrahim

Marsh

Amaro³

et al. 2022

BMC Health Serv Res

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Disparities in expected driving time to opioid treatment and treatment completion: findings from an exploratory study

Cited by 5 publications

References 30 publications

Workforce Diversity and disparities in wait time and retention among opioid treatment programs

Workforce Diversity and disparities in wait time and retention among opioid treatment programs

Accessibility of Opioid Treatment Programs Based on Conventional vs Perceived Travel Time Measures

Correction to: Disparities in expected driving time to opioid treatment and treatment completion: findings from an exploratory study

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