Use of a Telemedicine Bridge Clinic to Engage Patients in Opioid Use Disorder Treatment.

OBJECTIVES: We aimed to assess the feasibility of using a telemedicine bridge clinic model as a low-barrier mechanism to initiate patients on medication treatment for opioid use disorder (MOUD) while facilitating engagement in long-term treatment. METHODS: We established a telemedicine bridge clinic after the U.S. Drug Enforcement Administration temporarily suspended regulations limiting initial treatment of patients with buprenorphine via both audiovisual and audio-only technology during the COVID-19 public health emergency. The rate of engagement in medication treatment for opioid use disorder MOUD based upon review of the Prescription Drug Monitoring Program is described. Referral sources, technology utilization, and payer mix are also presented. RESULTS: The Bridge Clinic scheduled 208 new patient visits and physicians evaluated 200, a show rate of 96% from April 2020 to July 2021. Of the 200 patients who were treated, 192 (96%) were diagnosed with opioid use disorder. Most patients (159/200, 79%) scheduled audio-only visits. At least 1 prescription for buprenorphine was filled by 185/192 (96%) of opioid use disorder patients within 30 days of the telemedicine visit and 147/192 (77%) of patients filled 2 or more prescriptions. Most patients were covered by Medicaid (62%) or were uninsured (19%). There was no significant difference in outcomes for patients evaluated by audio-only vs. audiovisual techniques. CONCLUSION: A Bridge Clinic using audiovisual and audio-only telemedicine served a high-risk, vulnerable population and facilitated engagement in evidence-based MOUD.

Elevated COVID19 mortality risk in detroit area hospitals among patients from census tracts with extreme socioeconomic vulnerability.

BACKGROUND: the incidence of novel coronavirus disease (COVID19) is elevated in areas with heightened socioeconomic vulnerability. Early reports from US hospitals also implicated social disadvantage and chronic disease history as COVID19 mortality risk factors. However, the relationship between race and COVID19 mortality remains unclear. METHODS: we examined in-hospital COVID19 mortality risk factors in a multi-hospital tertiary health care system that serves greater Detroit, Michigan, a predominantly African American city with high rates of poverty and chronic disease. Consecutive adult patients who presented to emergency departments and tested positive for COVID19 from 3/11/2020 through 4/18/2020 were included. Using log-binomial regression, we assessed the relationship between in-hospital mortality and residence in census tracts that were flagged for extreme socioeconomic vulnerability, patient-level demographics, and clinical comorbidities. FINDINGS: a total of 1,015 adults tested positive for COVID19 during the study period; 80% identified as Black people, 52% were male and 53% were ≥ 65 years of age. The median body mass index was 30•4 and the median Charlson Comorbidity Index score was 4. Patients from census tracts that were flagged for vulnerability related to socioeconomic status had a higher mortality rate than their peers who resided in less vulnerable census tracts (ß 0.26, standard error (SE) 0.11, degrees of freedom (df) 378, t-value (t) 2.27, exp(ß) 1.29, p-value 0.02). Adjustment for age category, Black race, sex and/or the Charlson Comorbidity Index score category reduced the magnitude of association by less than 10% [exp(ß) 1.29 vs. 1.21]. Black race [p = 0.38] and sex [p = 0.62] were not associated with mortality in this sample. INTERPRETATION: people who lived in areas flagged for extreme socioeconomic vulnerability had elevated mortality risk in our predominantly African-American cohort of COVID19 patients who were able to seek hospital care during the so-called 'first wave' of the pandemic. By contrast, Black race was not associated with mortality in our sample.