Abstract: Where Do Clients Receive Methadone Treatment? Factors and Implications of Bypassing the Nearest Methadone Treatment (Society for Social Work and Research 27th Annual Conference - Social Work Science and Complex Problems: Battling Inequities + Building Solutions)

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Where Do Clients Receive Methadone Treatment? Factors and Implications of Bypassing the Nearest Methadone Treatment

Friday, January 13, 2023
Hospitality 2 - Room 444, 4th Level (Sheraton Phoenix Downtown)
* noted as presenting author
Abdullah Alibrahim, PhD, Assistant Professor, Kuwait University, Kuwait
Jeanne Marsh, PhD, Professor, University of Chicago, IL
Hortensia Amaro, PhD, Professor, Florida International University, FL
Yinfei Kong, PhD, Associate Professor, California State University, Fullerton, Fullerton, CA
Tenie Khachikian, PhD, Research Associate, University of Chicago, Chicago
Erick Guerrero, PhD, Research Director / Faculty, Research to End Healthcare Disparities Corp, Los Angeles, CA
Background: Enhancing access to MOUD is a national priority given the current epidemic. Yet, to date, there are limited studies on client choice of methadone treatment provider for opioid use disorder (OUD) treatment. Commuting time to treatment is known to influence the likelihood of completing methadone treatment plan requirements. Clients who bypass their closest methadone provider commute longer, potentially reducing the probability of treatment completion and adequate retention. We aim to (1) report bypassing patterns across subgroups of Los Angeles County (LAC) methadone treatment seekers, (2) examine disparities in bypassing rates and opportunities across ethnic and gender groups, and (3) explore associations between bypassing frequency and provider performance such as wait times.

Methods: The study is a retrospective, multi-year, cross-sectional analysis of OUD treatment episodes matched with estimated commuting times between clients’ zipcodes (population-weighted centroid) and treatment facilities. We analyzed discharge survey data from 16,972 outpatient methadone treatment episodes in Los Angeles County in the years 2012 to 2017 and matched them with commuting data from Google Maps. The analytic sample included 32 methadone treatment facilities and 8,627 unique clients. A treatment episode is considered a bypassing episode if the client’s zip code has a closer provider than the one at which the treatment was delivered. If a client bypasses, we calculate the difference in driving time between the closest provider (bypassed) to the methadone provider at which the client received treatment (bypassed to). We calculate rates of bypass and create drive-time-beyond-closest-facility categories for bypassing clients and compare the proportions of each bypassing category across gender and ethnic groups. We geographically represent bypassing categories on a zip code-level map of LAC to visualize the geographic distribution of bypassing rates. We then examine rates by characteristics of the closest provider to highlight potential drivers of bypass in methadone treatment.

Results: Bypass occurs in 49% of episodes – 41% of episodes are driving 5 minutes or more beyond their closest facility. These rates vary significantly across race and gender categories, with black clients having lower bypass rates and less time beyond closes facilities when bypassing. Female Latina clients were found to have lower bypass rates and shorter time beyond the closest facility when bypassing than male Latino clients (p<0.01). We found that black clients were more likely to bypass to methadone providers with longer wait times compared to their closest provider. We also found evidence that black clients have a lower probability of completing a methadone treatment plan when bypassing far beyond their closest methadone provider.

Implications: Despite the importance of understanding clients’ choice of methadone providers, our study is the first to examine the bypassing phenomenon at this scale. Our findings uncover alarming rates of bypass and inefficient allocation of at-risk clients to more distant facilities that have longer wait times. Findings have policy implications for better opioid treatment system design and improved accessibility to quality providers based on proximity to underserved communities.