Background: Health systems and providers across America are increasingly employing telehealth technologies to better serve medically underserved low-income, minority, and rural populations at the highest risk for health disparities. The Patient-Centered Outcomes Research Institute (PCORI) has invested US $386 million in comparative effectiveness research in telehealth, yet little is known about the key early lessons garnered from this research regarding the best practices in using telehealth to address disparities. Objective: This paper describes preliminary lessons from the body of research using study findings and case studies drawn from PCORI seminal patient-centered outcomes research (PCOR) initiatives. The primary purpose was to identify common barriers and facilitators to implementing telehealth technologies in populations at risk for disparities. Methods: A systematic scoping review of telehealth studies addressing disparities was performed. It was guided by the Arksey and O’Malley Scoping Review Framework and focused on PCORI’s active portfolio of telehealth studies and key PCOR identified by study investigators. We drew on this broad literature using illustrative examples from early PCOR experience and published literature to assess barriers and facilitators to implementing telehealth in populations at risk for disparities, using the active implementation framework to extract data. Major themes regarding how telehealth interventions can overcome barriers to telehealth adoption and implementation were identified through this review using an iterative Delphi process to achieve consensus among the PCORI investigators participating in the study. Results: PCORI has funded 89 comparative effectiveness studies in telehealth, of which 41 assessed the use of telehealth to improve outcomes for populations at risk for health disparities. These 41 studies employed various overlapping modalities including mobile devices (29/41, 71%), web-based interventions (30/41, 73%), real-time videoconferencing (15/41, 37%), remote patient monitoring (8/41, 20%), and store-and-forward (ie, asynchronous electronic transmission) interventions (4/41, 10%). The studies targeted one or more of PCORI’s priority populations, including racial and ethnic minorities (31/41, 41%), people living in rural areas, and those with low income/low socioeconomic status, low health literacy, or disabilities. Major themes identified across these studies included the importance of patient-centered design, cultural tailoring of telehealth solutions, delivering telehealth through trusted intermediaries, partnering with payers to expand telehealth reimbursement, and ensuring confidential sharing of private information. Conclusions: Early PCOR evidence suggests that the most effective health system- and provider-level telehealth implementation solutions to address disparities employ patient-centered and culturally tailored telehealth solutions whose development is actively guided by the patients themselves to meet the needs of specific communities and populations. Further, this evidence shows that the best practices in telehealth implementation include delivery of telehealth through trusted intermediaries, close partnership with payers to facilitate reimbursement and sustainability, and safeguards to ensure patient-guided confidential sharing of personal health information.

Objective Health information exchange (HIE) systems are being developed across the nation. Understanding approaches taken by existing successful exch

We aimed to assess use of and interest in mobile health (mHealth) technology and in-person services for diabetes self-care in vulnerable populations. We delivered a self-administered cross-sectional survey. Participants were recruited at two primary care practices (P1 and P2) with P1 located in a medically underserved area and P2 in an affluent suburb. Two-sample t-tests and chi-square tests were used with p < 0.05 significant. In addition, a secondary analysis was performed to analyse differences in use and interest in mHealth by age. Of 75 eligible patients, 60 completed the survey (80% response rate). P1 patients had significantly higher interest in three of five categories of in-person diabetes support services, one of four categories of health-related text messages (TM), and three of eight categories of mHealth applications (p < 0.05). Smartphone users reported higher interest in TM (p = 0.004) and mHealth applications for diabetes self-care (p = 0.004). Younger patients were more likely to have a smartphone (p < 0.006), use the Internet (p < 0.0012), use smartphone applications (p < 0.0004), and to be interested in using applications to manage their diabetes (p < 0.004). This study shows substantial patient interest in TM and mHealth applications for diabetes self-care and suggests that patients in underserved areas may have particularly high interest in using mHealth solutions in primary care. Younger patients and smartphone users were more likely to be interested in using applications to manage their diabetes. As more patients use smartphones, interest in using mHealth to support patient self-care and strengthen primary care infrastructure will continue to grow.