Literature Collection

INTRODUCTION: Access to medication assisted treatment (MAT) for opioid use disorder (OUD) in the United States is a significant challenge for many individuals attempting to recover and improve their lives. Access to treatment is especially challenging in rural areas characterized by lack of programs, few prescribers, and transportation barriers. This study aims to better understand the roles that transportation, Medicaid-funded non-emergency medical transportation (NEMT), and telehealth play in facilitating access to MAT in West Virginia (WV). METHODS: We developed this survey using an exploratory sequential mixed methods approach following a review of current peer-reviewed literature plus information gained from 3 semi-structured interviews and follow-up discussions with 5 individuals with lived experience in MAT. Survey results from 225 individuals provided rich context on the influence of transportation in enrolling and remaining in treatment, use of NEMT, and experiences using telehealth. Data were collected from February through August 2021. RESULTS: We found that transportation is a significant factor in entering into and remaining in treatment, with 170 (75.9%) respondents agreeing or strongly agreeing that having transportation was a factor in deciding to go into a MAT program, and 176 (71.1%) agreeing or strongly agreeing that having transportation helps them stay in treatment. NEMT was used by one-quarter (n = 52, 25.7%) of respondents. Only 13 (27.1%) noted that they were picked up on time and only 14 (29.2%) noted that it got them to their appointment on time. Two thirds of respondents (n = 134, 66.3%) had participated in MAT services via telehealth video or telephone visits. More preferred in-person visits to telehealth visits but a substantial number either preferred telehealth or reported no preference. However, 18 (13.6%) reported various challenges in using telehealth. CONCLUSIONS: This study confirms that transportation plays a significant role in many people's decisions to enter and remain in treatment for OUD in WV. Additionally, for those who rely on NEMT, services can be unreliable. Finally, findings demonstrate the need for individualized care and options for accessing treatment for OUD in both in-person and telehealth-based modalities. Programs and payers should examine all possible options to ensure access to care and recovery.

BACKGROUND: Improving access to treatment for opioid use disorder is a national priority, but little is known about the barriers encountered by patients seeking buprenorphine-naloxone ("buprenorphine") treatment. OBJECTIVE: To assess real-world access to buprenorphine treatment for uninsured or Medicaid-covered patients reporting current heroin use. DESIGN: Audit survey ("secret shopper" study). SETTING: 6 U.S. jurisdictions with a high burden of opioid-related mortality (Massachusetts, Maryland, New Hampshire, West Virginia, Ohio, and the District of Columbia). PARTICIPANTS: From July to November 2018, callers contacted 546 publicly listed buprenorphine prescribers twice, posing as uninsured or Medicaid-covered patients seeking buprenorphine treatment. MEASUREMENTS: Rates of new appointments offered, whether buprenorphine prescription was possible at the first visit, and wait times. RESULTS: Among 1092 contacts with 546 clinicians, schedulers were reached for 849 calls (78% response rate). Clinicians offered new appointments to 54% of Medicaid contacts and 62% of uninsured-self-pay contacts, whereas 27% of Medicaid and 41% of uninsured-self-pay contacts were offered an appointment with the possibility of buprenorphine prescription at the first visit. The median wait time to the first appointment was 6 days (interquartile range [IQR], 2 to 10 days) for Medicaid contacts and 5 days (IQR, 1 to 9 days) for uninsured-self-pay contacts. These wait times were similar regardless of clinician type or payer status. The median wait time from first contact to possible buprenorphine induction was 8 days (IQR, 4 to 15 days) for Medicaid and 7 days (IQR, 3 to 14 days) for uninsured-self-pay contacts. LIMITATION: The survey sample included only publicly listed buprenorphine prescribers. CONCLUSION: Many buprenorphine prescribers did not offer new appointments or rapid buprenorphine access to callers reporting active heroin use, particularly those with Medicaid coverage. Nevertheless, wait times were not long, implying that opportunities may exist to increase access by using the existing prescriber workforce.

The aim of this study was to assess the availability of medications for opioid use disorder (MOUD) and other services for pregnant people in jails in counties heavily impacted by opioid overdose in the United States. Counties were selected based on absolute number and population rate of opioid-overdose fatalities. Structured interviews were completed with representatives from 174 jails that house pregnant women. Descriptive statistics examine MOUD availability and differences in service provision and community-level characteristics based on MOUD availability. Most jails in the study sample (84.5%) had MOUD available for pregnant people; however, less than half of these jails ensured continuity of care. Jails without MOUD available are more likely to provide non-MOUD substance use services. These jails are more often located in smaller, rural counties in the Midwest and have higher rates of White residents and lower rates of Hispanic and African American residents. Gaps in MOUD availability in jails and continuity of care violate medical guidelines for treatment of pregnant patients with opioid use disorder and increase their risk of overdose. In addition, there are disparities across communities in access to MOUD for pregnant people in jails.

IMPORTANCE: With increasing rates of opioid use disorder (OUD) and overdose deaths in the US, increased access to medications for OUD (MOUD) is paramount. Rigorous effectiveness evaluations of large-scale implementation initiatives using quasi-experimental designs are needed to inform expansion efforts. OBJECTIVE: To evaluate a US Department of Veterans Affairs (VA) initiative to increase MOUD use in nonaddiction clinics. DESIGN, SETTING, AND PARTICIPANTS: This quality improvement initiative used interrupted time series design to compare trends in MOUD receipt. Primary care, pain, and mental health clinics in the VA health care system (n = 35) located at 18 intervention facilities and nonintervention comparison clinics (n = 35) were matched on preimplementation MOUD prescribing trends, clinic size, and facility complexity. The cohort of patients with OUD who received care in intervention or comparison clinics in the year after September 1, 2018, were evaluated. The preimplementation period extended from September 1, 2017, through August 31, 2018, and the postimplementation period from September 1, 2018, through August 31, 2019. EXPOSURES: The multifaceted implementation intervention included education, external facilitation, and quarterly reports. MAIN OUTCOMES AND MEASURES: The main outcomes were the proportion of patients receiving MOUD and the number of patients per clinician prescribing MOUD. Segmented logistic regression evaluated monthly proportions of MOUD receipt 1 year before and after initiative launch, adjusting for demographic and clinical covariates. Poisson regression models examined yearly changes in clinician prescribing over the same time frame. RESULTS: Overall, 7488 patients were seen in intervention clinics (mean [SD] age, 53.3 [14.2] years; 6858 [91.6%] male; 1476 [19.7%] Black, 417 [5.6%] Hispanic; 5162 [68.9%] White; 239 [3.2%] other race [including American Indian or Alaska Native, Asian, Native Hawaiian or other Pacific Islander, and multiple races]; and 194 [2.6%] unknown) and 7558 in comparison clinics (mean [SD] age, 53.4 [14.0] years; 6943 [91.9%] male; 1463 [19.4%] Black; 405 [5.4%] Hispanic; 5196 [68.9%] White; 244 [3.2%] other race; 250 [3.3%] unknown). During the preimplementation year, the proportion of patients receiving MOUD in intervention clinics increased monthly by 5.0% (adjusted odds ratio [AOR], 1.05; 95% CI, 1.03-1.07). Accounting for this preimplementation trend, the proportion of patients receiving MOUD increased monthly by an additional 2.3% (AOR, 1.02; 95% CI, 1.00-1.04) during the implementation year. Comparison clinics increased by 2.6% monthly before implementation (AOR, 1.03; 95% CI, 1.01-1.04), with no changes detected after implementation. Although preimplementation-year trends in monthly MOUD receipt were similar in intervention and comparison clinics, greater increases were seen in intervention clinics after implementation (AOR, 1.04; 95% CI, 1.01-1.08). Patients treated with MOUD per clinician in intervention clinics saw greater increases from before to after implementation compared with comparison clinics (incidence rate ratio, 1.50; 95% CI, 1.28-1.77). CONCLUSIONS AND RELEVANCE: A multifaceted implementation initiative in nonaddiction clinics was associated with increased MOUD prescribing. Findings suggest that engagement of clinicians in general clinical settings may increase MOUD access.