Objective To understand patient experience of federal regulatory changes governing methadone and buprenorphine (MOUD) access in Arizona during the COVID-19 pandemic. Methods This community-based participatory and action research study involved one-hour, audio-recorded field interviews conducted with 131 people who used methadone and/or buprenorphine to address opioid use disorder at some point during COVID (January 1, 2020- March 31, 2021) in Arizona. Transcribed data were analyzed using a priori codes focused on federally recommended flexibilities governing MOUD access. Data were quantitated to investigate associations with COVID risk and services access. Results Telehealth was reported by 71.0% of participants, but the majority were required to come to the clinic to attend video appointments with an offsite provider. Risk for severe COVID outcomes was reported by 40.5% of the sample. Thirty-eight percent of the sample and 39.7% of methadone patients were required to be at the clinic daily to get medication and 47.6% were at high risk for COVID severe outcomes. About half (54.2%) of methadone patients indicated that some form of multi-day take home dosing was offered at their clinic, and 45.8% were offered an extra day or two of multi-day doses; but no participants received the federally allowed 14- or 28-day methadone take-home doses for unstable and stable patients respectively. All participants expressed that daily clinic visits interrupted their work and home lives and desired more take-home dosing and home delivery options. Conclusions MOUD patients in Arizona were not offered many of the federally allowed flexibilities for access that were designed to reduce their need to be at the clinic. To understand the impact of these recommended treatment changes in Arizona, and other states where they were not well implemented, federal and state regulators must mandate these changes and support MOUD providers to implement them.

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IntroductionQuitlines are standard care for smoking cessation; however, retaining clients in services is a problem. Little is known about factors that may predict dropout.AimsTo examine predictors of retention while in-program and at follow-up for clients enrolling in a state quitline.MethodsThis was a retrospective analysis of quitline enrolled clients from 2011 to 2017 (N = 49,347). Client retention in-program was categorized as (a) low adherence to treatment (receiving zero coaching calls), moderate (1–2 calls), and high adherence (3+ calls). Dropout at follow-up included participants who were not reached for the 7-month follow-up.ResultsMore than half the sample dropped out during treatment; 61% were not reached for follow-up. Women (odds ratio (OR) = 1.21; 95% confidence interval (CI) = [1.16, 127]) and those with high levels of nicotine dependence (OR = 1.03; 95% CI = [1.02, 1.04]) were more likely to have moderate adherence to treatment (1–2 coaching calls). Dropout at follow-up was more likely among clients who used nicotine replacement therapy (OR = 1.14; 95% CI = [1.09, 1.19]) and less likely among those who had high treatment adherence (OR = 0.41; 95% CI = [0.39, 0.42]).ConclusionGiven the relapsing nature of tobacco use and the harms related to tobacco use, quitlines can improve their impact by offering tailored services to enhance client engagement and retention in-treatment and at follow-up.

IntroductionQuitlines are an integral part of tobacco treatment programs and reach groups of smokers who have a wide range of barriers to cessation. Although tobacco dependence is chronic and relapsing, little research exists on factors that predict the likelihood of clients re-engaging and reconnecting with quitlines for treatment. The objective of this study was to describe factors that predict the re-enrollment of clients in Arizona’s state quitline.MethodsThis was a retrospective analysis of data collected from clients (N = 49,284) enrolled in the Arizona Smokers’ Helpline from January 2011 through June 2016. We used logistic regression to analyze predictors of re-enrollment in services after controlling for theoretically relevant baseline variables (eg, nicotine dependence, smokers in the home) and follow-up variables (eg, program use, quit outcome).ResultsCompared with clients who reported being quit after their first enrollment, clients who reported not being quit were almost 3 times as likely to re-enroll (odds ratio = 2.89; 95% confidence interval, 2.54–3.30). Other predictors were having a chronic condition or a mental health condition, greater nicotine dependence, and lower levels of social support. Women and clients not having other smokers in the home were more likely to re-enroll than were men and clients not living with other smokers.ConclusionUnderstanding baseline and in-program factors that predict client-initiated re-enrollment can help quitlines tailor strategies to proactively re-engage clients who may have difficulty maintaining long-term abstinence.

Medication for Opioid Use Disorder (MOUD) is recommended, but not always accessible to those who desire treatment. This study assessed the impact of expanding access to buprenorphine through federally qualified health centers (FQHCs) in Arizona. We calculated mean drive-times to Arizona opioid treatment (OTP) locations, office-based opioid treatment (OBOT) locations, and FQHCs clinics using January 2020 location data. FQHCs were designated as OBOT or non-OBOT clinics to explore opportunities to expand treatment access to non-OBOT clinics (potential OBOTs) to further reduce drive-times for rural and underserved populations. We found that OTPs had the largest mean drive times (16.4 minutes), followed by OBOTs (7.1 minutes) and potential OBOTs (6.1 minutes). Drive times were shortest in urban block groups for all treatment types and the largest differences existed between OTPs and OBOTs (50.6 minutes) in small rural and in isolated rural areas. OBOTs are essential points of care for opioid use disorder treatment. They reduce drive times by over 50% across all urban and rural areas. Expanding buprenorphine through rural potential OBOT sites may further reduce drive times to treatment and address a critical need among underserved populations.