Purpose To examine characteristics associated with disparities in digital access (i.e., access to high‐speed Internet via a computer or smartphone) in American rural and urban households given that digital access has a direct impact on access to telemedicine‐based services. Methods Using the 2019 American Community Survey, we analyzed the proportions of geographic area, race/ethnicity, and socioeconomic status according to device and high‐speed Internet access. Maximum likelihood logit estimators estimated how these factors influenced device and high‐speed Internet access. Findings Of 105,312,959 households, 32.29% were without a desktop or laptop computer with high‐speed Internet (WDW), 21.51% were without a smartphone with a data plan for wireless Internet (WSW), and 14.02% were without any digital access (WDA). Nonmetropolitan households were significantly more likely to be WDA than metropolitan households (odds ratio [OR] = 1.87; 95% confidence interval [CI]: 1.83‐1.91). Relative to non‐Hispanic Whites, non‐Hispanic Blacks (OR = 1.60; 95% CI: 1.56‐1.64), American Indian or Alaska natives (OR = 2.00; 95% CI: 1.82‐2.19), or Hispanics (OR = 1.70; 95% CI: 1.66‐1.74) were significantly more likely to be WDA. When compared to households with private health insurance coverage, households WDA were significantly more likely to have no insurance (OR = 2.44; 95% CI: 2.36‐2.53) or public insurance coverage (OR = 3.78; 95% CI: 3.70‐3.86). Households with any digital access reported higher income and more family members living at home. Using the same predictors, similar findings were reported for households WDW or WSW. Conclusions Significant disparities in digital access exist among nonmetropolitan households, racial/ethnic minority households, and lower‐income households. The lack of digital access has implications for the accessibility of health care services via telemedicine and thus could exacerbate health disparities.

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Telemedicine (TM) enabled by digital health technologies to provide medical services has been considered a key solution to increasing health care access in rural communities. With the immediate need for remote care due to the COVID-19 pandemic, many health care systems have rapidly incorporated digital technologies to support the delivery of remote care options, including medication treatment for individuals with opioid use disorder (OUD). In responding to the opioid crisis and the COVID-19 pandemic, public health officials and scientific communities strongly support and advocate for greater use of TM-based medication treatment for opioid use disorder (MOUD) to improve access to care and have suggested that broad use of TM during the pandemic should be sustained. Nevertheless, research on the implementation and effectiveness of TM-based MOUD has been limited. To address this knowledge gap, the National Drug Abuse Treatment Clinical Trials Network (CTN) funded (via the NIH HEAL Initiative) a study on Rural Expansion of Medication Treatment for Opioid Use Disorder (Rural MOUD; CTN-0102) to investigate the implementation and effectiveness of adding TM-based MOUD to rural primary care for expanding access to MOUD. In preparation for this large-scale, randomized controlled trial incorporating TM in rural primary care, a feasibility study is being conducted to develop and pilot test implementation procedures. In this commentary, we share some of our experiences, which include several challenges, during the initial two-month period of the feasibility study phase. While these challenges could be due, at least in part, to adjusting to the COVID-19 pandemic and new workflows to accommodate the study, they are notable and could have a substantial impact on the larger, planned pragmatic trial and on TM-based MOUD more broadly. Challenges include low rates of identification of risk for OUD from screening, low rates of referral to TM, digital device and internet access issues, workflow and capacity barriers, and insurance coverage. These challenges also highlight the lack of empirical guidance for best TM practice and quality remote care models. With TM expanding rapidly, understanding implementation and demonstrating what TM approaches are effective are critical for ensuring the best care for persons with OUD.