Background The majority of individuals with opioid use disorder (OUD) face access barriers to evidence-based treatment, and the COVID-19 pandemic has exacerbated the United States (US) opioid overdose crisis. However, the pandemic has also ushered in rapid transitions to telehealth in the USA, including for substance use disorder treatment with buprenorphine. These changes have the potential to mitigate barriers to care or to exacerbate pre-existing treatment inequities. The objective of this study was to qualitatively explore Philadelphia-based low-barrier, harm-reduction oriented, opioid use disorder (OUD) treatment provider perspectives about and experiences with telehealth during the COVID-19 pandemic, and to assess their desire to offer telehealth to patients at their programs in the future. Methods We interviewed 22 OUD treatment prescribers and staff working outpatient programs offering OUD treatment with buprenorphine in Philadelphia during July and August 2020. All participants worked at low-barrier treatment programs that provide buprenorphine using a harm reduction-oriented approach and without mandating counseling or other requirements as a condition of treatment. We analyzed the data using thematic content analysis. Results Our analysis yielded three themes: 1/ Easier access for some: telehealth facilitates care for many patients who have difficulty attending in-person appointments due to logistical and psychological barriers; 2/ A layered digital divide: engagement with telehealth can be seriously limited by patients’ access to and comfort with technology; and 3/ Clinician control: despite some clinic staff beliefs that patients should have the freedom to choose their treatment modality, patients’ access to treatment via telehealth may hinge on clinician perceptions of patient “stability” rather than patient preferences. Conclusions Telehealth may address many access issues, however, barriers to implementation remain, including patient ability and desire to attend healthcare appointments virtually. In addition, the potential for telehealth models to extend OUD care to patients currently underserved by in-person models may partially depend on clinician comfort treating patients deemed “unstable” via this modality. The ability of telehealth to expand access to OUD care for individuals who have previously struggled to engage with in-person care will likely be limited if these patients are not given the opportunity to receive treatment via telehealth.

IMPORTANCE Curbing COVID-19 transmission is currently the greatest global public health challenge. Consumer digital tools used to collect data, such as the Apple-Google digital contact tracing program, offer opportunities to reduce COVID-19 transmission but introduce privacy concerns.OBJECTIVE To assess uses of consumer digital information for COVID-19 control that US adults find acceptable and the factors associated with higher or lower approval of use of this information. DESIGN, SETTING, AND PARTICIPANTSThis cross-sectional survey study obtained data from a nationally representative sample of 6284 US adults recruited by email from the web-based Ipsos KnowledgePanel in July 2020. Respondents evaluated scenarios reflecting uses of digital data for COVID-19 control (case identification, digital contact tracing, policy setting, and enforcement of quarantines). MAIN OUTCOMES AND MEASURES Levels of support for use of personal digital data in 9 scenariosto mitigate the spread of COVID-19 infection, rated on a Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Multivariable linear regression models were fitted for each scenario and included factors hypothesized to be associated with views about digital data use for COVID-19 mitigation measures. Black and Hispanic survey respondents were oversampled; thus, poststratification weights were used so that results are representative of the general US population. RESULTSOf 6284 individuals invited to participate in the study, 3547 responded, for a completion rate of 56%. A total of 1762 participants (52%) were female, 715 (21%) identified as Black, 790 (23%) identified as Hispanic, and 1224 (36%) were 60 years or older; mean (SD) age was 51.7 (16.6) years.Approval of scenarios was low, ranging from 28% to 43% (52%-67% when neutral responses were included). Differences were found based on digital data source (smartphone vs social media: coefficient, 0.29 [95% CI, 0.23-0.35]; P < .001; smart thermometer vs social media: coefficient, 0.09 [95% CI, 0.03-0.16]; P = .004). County COVID-19 rates (coefficient, −0.02; 95% CI, −0.16 to 0.13 for quartile 4 compared with quartile 1) and prior family diagnosis of COVID-19 (coefficient, 0.00; 95% CI, −0.25 to 0.25) were not associated with support. Compared with self-described liberal individuals, conservative (coefficient, −0.81; 95% CI, −0.96 to −0.66; P < .001) and moderate (coefficient, −0.52; 95% CI, −0.67 to −0.38; P < .001) individuals were less likely to support the scenarios. Similarly, large political differences were observed in support of the Apple-Google digital contact tracing program, with less support from conservative (coefficient, −0.99; 95% CI, −1.11 to −0.87; P < .001) and moderate (coefficient, −0.59; 95% CI, −0.69 to −0.48; P < .001) individuals compared with liberal individuals. Respondents from racial/ethnic minority groups were more supportive of the scenarios than were White, non-Hispanic respondents. For example, compared with White respondents, Black respondents were more supportive of the A...

Key Points Question What is the role of patient preference in racial disparities in opioid prescribing for patients with acute pain, and does providing clinicians with additional data about their patients mitigate disparities? Findings In this secondary analysis of 1012 patients with acute pain who were recruited for a multicenter randomized clinical trial, Black patients were less likely than White patients to receive a prescription for opioids, regardless of their treatment preference. These disparities were not mitigated by providing clinicians with additional data about their patients’ preferences and risks. Meaning This study’s findings suggest that differences in patient preference do not explain racial disparities in opioid prescribing; further research is needed to assess the factors associated with these disparities.

Objectives. To compare the effectiveness of 3 approaches for communicating opioid risk during an emergency department visit for a common painful condition. Methods. This parallel, multicenter randomized controlled trial was conducted at 6 geographically disparate emergency department sites in the United States. Participants included adult patients between 18 and 70 years of age presenting with kidney stone or musculoskeletal back pain. Participants were randomly assigned to 1 of 3 risk communication strategies: (1) a personalized probabilistic risk visual aid, (2) a visual aid and a video narrative, or 3) general risk information. The primary outcomes were accuracy of risk recall, reported opioid use, and treatment preference at time of discharge. Results. A total of 1301 participants were enrolled between June 2017 and August 2019. There was no difference in risk recall at 14 days between the narrative and probabilistic groups (43.7% vs 38.8%; absolute risk reduction = 4.9%; 95% confidence interval [CI] = −2.98, 12.75). The narrative group had lower rates of preference for opioids at discharge than the general risk information group (25.9% vs 33.0%; difference = 7.1%; 95% CI = 0.64, 0.97). There were no differences in reported opioid use at 14 days between the narrative, probabilistic, and general risk groups (10.5%, 10.3%, and 13.3%, respectively; P = .44). Conclusions. An emergency medicine communication tool incorporating probabilistic risk and patient narratives was more effective than general information in mitigating preferences for opioids in the treatment of pain but was not more effective with respect to opioid use or risk recall. Trial Registration. Clinical Trials.gov identifier: NCT03134092. (Am J Public Health. 2022;112(S1):S45–S55. https://doi.org/10.2105/AJPH.2021.306511 )