Association of Project ECHO Training With Buprenorphine Prescribing by Primary Care Clinicians in Minnesota for Treating Opioid Use Disorder.

Importance: Buprenorphine is an approved medication for opioid use disorder (MOUD); however, prescribing buprenorphine is limited by a requirement to obtain a waiver to prescribe it (hereinafter, "DATA [Drug Abuse Treatment Act]-waiver") and a lack of knowledge of the best practices among clinicians. Objective: To examine how Project ECHO (Extension for Community Healthcare Outcomes) telementoring is associated with changes in DATA-waiver attainment and buprenorphine prescribing among primary care clinicians in Minnesota. Design, Setting, and Participants: In this retrospective matched-cohort study of 918 clinicians, ECHO-trained clinicians were enrolled on the date they first attended ECHO (January 3, 2018, to June 11, 2020); comparison clinicians were assigned an enrollment date from the distribution of the first ECHO sessions. The baseline period was 12 months preceding enrollment, with follow-up for 18 months or until June 30, 2020. The ECHO-trained clinicians were a population-based sample of primary care clinicians who treated Medicaid patients in Minnesota 12 months prior to the initiation of ECHO training. This analysis used propensity score matching to select comparison clinicians who were similar across demographic and clinical practice characteristics at baseline in a 2:1 ratio. Follow-up was available for 167 ECHO-trained clinicians (54.6%) and 330 comparison clinicians (53.9%) at 18 months. Exposures: ECHO-trained clinicians attended at least 1 weekly, hour-long ECHO session. Comparison clinicians never participated in any ECHO sessions. Main Outcomes and Measures: DATA-waiver attainment, any buprenorphine prescribing, and the percentage of patients with opioid use disorder (OUD) who were prescribed buprenorphine. Results: The final sample included 918 clinicians (ECHO-trained [306]; comparison [612]), of whom 620 (67.5%) practiced outside the metropolitan Twin Cities (Minneapolis-St Paul) region. The mean (SD) age of the ECHO-trained clinicians was 46.0 (12.1) years and that of the comparison clinicians was 45.7 (12.3) years. Relative to the changes among the matched comparison clinicians, the ECHO-trained clinicians were more likely to obtain a DATA-waiver (difference-in-differences, 22.7 percentage points; 95% CI, 15.5-29.9 percentage points; P < .001) and prescribe any buprenorphine (16.5 percentage points; 95% CI, 10.4-22.5 percentage points; P < .001) after 6 quarters of follow-up. ECHO-trained clinicians prescribed buprenorphine to a greater share of patients with OUD (a difference of 7.6 percentage points per month; 95% CI, 4.6-10.6 percentage points per month; P < .001), relative to that prescribed by the comparison clinicians. Conclusions and Relevance: According to the findings of this matched-cohort study, ECHO telementoring may be associated with greater prescribing of buprenorphine by primary care clinicians. These findings suggest that Project ECHO training could be a useful tool for expanding access to MOUD.

Prevalence and Medication Treatment of Opioid Use Disorder Among Primary Care Patients with Hepatitis C and HIV.

BACKGROUND: Hepatitis C and HIV are associated with opioid use disorders (OUD) and injection drug use. Medications for OUD can prevent the spread of HCV and HIV. OBJECTIVE: To describe the prevalence of documented OUD, as well as receipt of office-based medication treatment, among primary care patients with HCV or HIV. DESIGN: Retrospective observational cohort study using electronic health record and insurance data. PARTICIPANTS: Adults ≥ 18 years with ≥ 2 visits to primary care during the study (2014-2016) at 6 healthcare systems across five states (CO, CA, OR, WA, and MN). MAIN MEASURES: The primary outcome was the diagnosis of OUD; the secondary outcome was OUD treatment with buprenorphine or oral/injectable naltrexone. Prevalence of OUD and OUD treatment was calculated across four groups: HCV only; HIV only; HCV and HIV; and neither HCV nor HIV. In addition, adjusted odds ratios (AOR) of OUD treatment associated with HCV and HIV (separately) were estimated, adjusting for age, gender, race/ethnicity, and site. KEY RESULTS: The sample included 1,368,604 persons, of whom 10,042 had HCV, 5821 HIV, and 422 both. The prevalence of diagnosed OUD varied across groups: 11.9% (95% CI: 11.3%, 12.5%) for those with HCV; 1.6% (1.3%, 2.0%) for those with HIV; 8.8% (6.2%, 11.9%) for those with both; and 0.92% (0.91%, 0.94%) among those with neither. Among those with diagnosed OUD, the prevalence of OUD medication treatment was 20.9%, 16.0%, 10.8%, and 22.3%, for those with HCV, HIV, both, and neither, respectively. HCV was not associated with OUD treatment (AOR = 1.03; 0.88, 1.21), whereas patients with HIV had a lower probability of OUD treatment (AOR = 0.43; 0.26, 0.72). CONCLUSIONS: Among patients receiving primary care, those diagnosed with HCV and HIV were more likely to have documented OUD than those without. Patients with HIV were less likely to have documented medication treatment for OUD.

Developing a clinical decision support for opioid use disorders: a NIDA center for the clinical trials network working group report.

There is an urgent need for strategies to address the US epidemic of prescription opioid, heroin and fentanyl-related overdoses, misuse, addiction, and diversion. Evidence-based treatment such as medications for opioid use disorder (MOUD) are available but lack numbers of providers offering these services to meet the demands. Availability of electronic health record (EHR) systems has greatly increased and led to innovative quality improvement initiatives but this has not yet been optimized to address the opioid epidemic or to treat opioid use disorder (OUD). This report from a clinical decision support (CDS) working group convened by the NIDA Center for the Clinical Trials Network aims to converge electronic technology in the EHR with the urgent need to improve screening, identification, and treatment of OUD in primary care settings through the development of a CDS algorithm that could be implemented as a tool in the EHR. This aim is consistent with federal, state and local government and private sector efforts to improve access and quality of MOUD treatment for OUD, existing clinical quality and HEDIS measures for OUD or drug and alcohol use disorders, and with a recent draft grade B recommendation from the US Preventative Services Task Force (USPSTF) for screening for illicit drug use in adults when appropriate diagnosis, treatment and care services can be offered or referred. Through a face-to-face expert panel meeting and multiple follow-up conference calls, the working group drafted CDS algorithms for clinical care felt to be essential for screening, diagnosis, and management of OUD in primary care. The CDS algorithm was reviewed by addiction specialists and primary care providers and revised based on their input. A clinical decision support tool for OUD screening, assessment, and treatment within primary care systems may help improve healthcare delivery to help address the current epidemic of opioid misuse and overdose that has outpaced the capacity of specialized treatment settings. A semi-structured outline of clinical decision support for OUD was developed to facilitate implementation within the EHR. Further work for adaptation at specific sites and for testing is needed.