Literature Collection

The COVID-19 pandemic struck in the midst of an ongoing opioid epidemic. To offset disruption to life-saving treatment for opioid use disorder (OUD), several federal agencies granted exemptions to existing federal regulations. This included loosening restrictions on medications for OUD (MOUD), including methadone and buprenorphine. In this commentary, we briefly review policy and practice guidelines for treating OUD prior to the onset of the COVID-19 pandemic. We then outline specific MOUD treatment policy and practice exemptions that went into effect in February and March 2020, and discuss the ways in which these unprecedented changes have dramatically changed MOUD treatment. Given the unprecedented nature of these changes, and unknown outcomes to date, we advocate for a data-driven approach to guide future policy and practice recommendations regarding MOUD. We outline several critical clinical, research, and policy questions that can inform MOUD treatment in a post-COVID-19 era.

IMPORTANCE: Amid rapid and widespread adoption of telehealth-based opioid treatment (TBOT), there is an urgent need for rigorous studies exploring the feasibility and characteristics of urine drug screening (UDS). OBJECTIVE: To investigate administration patterns and results of UDS to assess feasibility of UDS and patient outcomes in a TBOT setting. DESIGN: This observational cohort study was conducted between January 1, 2021, and December 6, 2022, and included patients with opioid use disorder treated in Ophelia, a TBOT treatment platform in 14 states. Data analysis was performed from January to March 2023. MAIN OUTCOMES AND MEASURES: Number and percentage of patients with UDS within 30, 90, and 180 days of intake, grouped by adherence to clinical protocols. Associations were assessed between baseline characteristics and UDS completion and opioid positivity in first 30 days using χ2 tests. Baseline and 180-day follow-up UDS results were compared using McNemar tests. RESULTS: Among 3395 patients (mean [SD] age, 38.2 [9.3] years, mostly male [54.1%], non-Hispanic White [81.5%], urban-residing [80.3%], and cash-pay at intake [74.0%]), 2782 (83.3%) completed a UDS within 30 days (90.0% among protocol-adherent patients, 67.0% among protocol-nonadherent patients). A total of 2750 of 2817 (97.6%) patients retained more than 90 days completed 1 or more UDS, as did 2307 of 2314 (99.7%) patients retained more than 180 days. Younger patients, patients of a racial and ethnic minority group, those living in urban areas, and cash-pay patients were less likely to complete a UDS in the first 30 days. Buprenorphine positivity increased (from 96.9% to 98.4%, P = .004) and opioid positivity declined (from 7.9% to 3.3%, P < .001) over time. CONCLUSIONS AND RELEVANCE: In this cohort study of patients with opioid use disorder receiving buprenorphine in a remote care environment, UDS was highly feasible, though early UDS completion rates varied across demographic subgroups. The prevalence of unexpected UDS results was low and declined over time in treatment.

An empiric evidence base is lacking regarding the relationship between insurance status, payment source, and outcomes among patients with opioid use disorder (OUD) on telehealth platforms. Such information gaps may lead to unintended impacts of policy changes. Following the phase-out of the COVID-19 Public Health Emergency, states were allowed to redetermine Medicaid eligibility and disenroll individuals. Yet, financial barriers remain a common and significant hurdle for patients with OUD and are associated with worse outcomes. We studied 3842 patients entering care in 2022 at Ophelia Health, one of the nation's largest OUD telehealth companies, to assess associations between insurance status and 6-month retention. In multivariable analyses, in-network patients who could use insurance benefits were more likely to be retained compared with cash-pay patients (adjusted risk ratio [aRR]: 1.50; 95% CI: 1.40-1.62; P < .001). Among a subsample of 882 patients for whom more detailed insurance data were available (due to phased-in electronic health record updates), in-network patients were also more likely to be retained at 6 months compared with insured, yet out-of-network patients (aRR: 1.86; 95% CI: 1.54-2.23; P < .001). Findings show that insurance status, and specifically the use of in-network benefits, is associated with superior retention and suggest that Medicaid disenrollment and insurance plan hesitation to engage with telehealth providers may undermine the nation's response to the opioid crisis.

IMPORTANCE: There is limited information about trends in the treatment of opioid use disorder (OUD) among Medicaid enrollees. OBJECTIVE: To examine the use of medications for OUD and potential indicators of quality of care in multiple states. DESIGN, SETTING, AND PARTICIPANTS: Exploratory serial cross-sectional study of 1 024 301 Medicaid enrollees in 11 states aged 12 through 64 years (not eligible for Medicare) with International Classification of Diseases, Ninth Revision (ICD-9 or ICD-10) codes for OUD from 2014 through 2018. Each state used generalized estimating equations to estimate associations between enrollee characteristics and outcome measure prevalence, subsequently pooled to generate global estimates using random effects meta-analyses. EXPOSURES: Calendar year, demographic characteristics, eligibility groups, and comorbidities. MAIN OUTCOMES AND MEASURES: Use of medications for OUD (buprenorphine, methadone, or naltrexone); potential indicators of good quality (OUD medication continuity for 180 days, behavioral health counseling, urine drug tests); potential indicators of poor quality (prescribing of opioid analgesics and benzodiazepines). RESULTS: In 2018, 41.7% of Medicaid enrollees with OUD were aged 21 through 34 years, 51.2% were female, 76.1% were non-Hispanic White, 50.7% were eligible through Medicaid expansion, and 50.6% had other substance use disorders. Prevalence of OUD increased in these 11 states from 3.3% (290 628 of 8 737 082) in 2014 to 5.0% (527 983 of 10 585 790) in 2018. The pooled prevalence of enrollees with OUD receiving medication treatment increased from 47.8% in 2014 (range across states, 35.3% to 74.5%) to 57.1% in 2018 (range, 45.7% to 71.7%). The overall prevalence of enrollees receiving 180 days of continuous medications for OUD did not significantly change from the 2014-2015 to 2017-2018 periods (-0.01 prevalence difference, 95% CI, -0.03 to 0.02) with state variability in trend (90% prediction interval, -0.08 to 0.06). Non-Hispanic Black enrollees had lower OUD medication use than White enrollees (prevalence ratio [PR], 0.72; 95% CI, 0.64 to 0.81; P < .001; 90% prediction interval, 0.52 to 1.00). Pregnant women had higher use of OUD medications (PR, 1.18; 95% CI, 1.11-1.25; P < .001; 90% prediction interval, 1.01-1.38) and medication continuity (PR, 1.14; 95% CI, 1.10-1.17, P < .001; 90% prediction interval, 1.06-1.22) than did other eligibility groups. CONCLUSIONS AND RELEVANCE: Among US Medicaid enrollees in 11 states, the prevalence of medication use for treatment of opioid use disorder increased from 2014 through 2018. The pattern in other states requires further research.

OBJECTIVES: Provision of smoking-cessation treatment is limited in office-based buprenorphine maintenance treatment (BMT) settings. This study describes smoking and smoking-cessation behaviors among patients receiving office-based BMT. METHODS: Cross-sectional study of patients receiving office-based BMT at a community health center in the Bronx, NY. We interviewed patients assessing sociodemographic, and substance use and tobacco use characteristics, including methods used for smoking cessation. We reported simple frequencies and explored associations of BMT characteristics with smoking behaviors. RESULTS: Of 68 patients, 87.7% were current cigarette smokers, 7.9% were former smokers, and 4.4% had never smoked. Of lifetime smokers, 83.1% reported at least 1 prior quit attempt, and 78.5% had used medication (75.4% used nicotine replacement therapy, 29.2% varenicline, and 9.2% bupropion). Ten patients (15.4%) reported using electronic cigarettes to try to quit smoking. Stopping "cold turkey" (40.0%) and gradually decreasing the number of cigarettes smoked (32.3%) were nonpharmacological methods of quitting tried most often. Use of behavioral support, including stop-smoking programs and counseling, was low. Higher dose and longer duration of BMT was associated with greater smoking frequency. CONCLUSIONS: Patients receiving BMT have a high prevalence of cigarette smoking, though most have tried to quit, and have prior experience with pharmacotherapy for smoking cessation. Efforts to optimize smoking-cessation treatments among BMT patients are needed.