The Influence of Telehealth for Better Health Across Communities

McElroy, Jane A.; Day, Tamara M; Becevic, Mirna

doi:10.5888/pcd17.200254

Cited by 33 publications

(28 citation statements)

References 17 publications

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“…Our study results are limited to telehealth use among the subset of older adults who reported using the internet in the previous 30 days. Audio-only telephone-based telehealth communication, which has become common during the COVID-19 emergency [16] was not measured in this study. Despite these limitations, our findings reinforce the relevance of broadband internet as a consequential factor in equitable access to telehealth and suggest possibilities from policies and programs to extend broadband internet availability and affordability [17,18].…”

Section: Discussionmentioning

confidence: 99%

Neighborhood Broadband and Use of Telehealth Among Older Adults: Cross-sectional Study of National Survey Data Linked With Census Data

et al. 2021

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Background The COVID-19 pandemic has amplified the role of telehealth in health care delivery. Regional variation in internet access and telehealth use are well-documented, but the effect of neighborhood factors, including the pervasiveness of broadband internet, on older adults’ telehealth usage in the context of internet access is not known. Objective This study aimed to investigate how individual and neighborhood characteristics, including the pervasiveness of neighborhood broadband internet subscription, are associated with engagement in telehealth among older adults with internet access. Methods In this cross-sectional study, we included 5117 community-living older adults aged ≥65 years, who participated in the 2017 National Health and Aging Trends Study with census tract–level data for participants’ places of residence from the American Community Survey. Results Of an estimated 35.3 million community-living older adults, 21.1 million (59.7%) were internet users, and of this group, more than one-third (35.8%) engaged in telehealth. In a multivariable regression model adjusted for individual- and neighborhood-level factors, age, education, income, and the pervasiveness of neighborhood broadband internet subscription were associated with engagement in telehealth, while race, health, county metropolitan status, and neighborhood social deprivation were not. Among internet users, living in a neighborhood at the lowest (versus highest) tertile of broadband internet subscription was associated with being 40% less likely to engage in telehealth (adjusted odds ratio 0.61, 95% CI 0.42-0.87), all else equal. Conclusions Neighborhood broadband internet stands out as a mutable characteristic that is consequential to engagement in telehealth.

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Section: Discussionmentioning

confidence: 99%

Neighborhood Broadband and Use of Telehealth Among Older Adults: Cross-sectional Study of National Survey Data Linked With Census Data

et al. 2021

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“…With the immediate need for remote care due to the COVID-19 pandemic, many TM restrictions have been waived, and health care systems have rapidly modified their practice to include digital technologies (e.g., telephone, video chat) for remote primary care and specialty services, including medication treatment for OUD (MOUD). In recent years and even more so now, in concert with the rapid uptake of TM, many articles and commentaries [ 3 , 4 ] have been advocating for wider and greater use of TM to improve access to health care and have suggested that broad use of TM during the pandemic should be sustained. While increasing access to care through TM for people with OUD, especially in rural areas severely impacted by the opioid crisis is desirable, research on the implementation and effectiveness of TM-based MOUD is limited.…”

Section: Introductionmentioning

confidence: 99%

Is telemedicine the answer to rural expansion of medication treatment for opioid use disorder? Early experiences in the feasibility study phase of a National Drug Abuse Treatment Clinical Trials Network Trial

Hser

Ober

Dopp

et al. 2021

Addict Sci Clin Pract

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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.

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“…Characteristics of studies. 41,52,54,55,62,69,77,91,102,105,114,117,122] 14 (11.1) April [17,18,21,30,38,42,43,51,53,61,63-65,68,70,73,75,76,81,82,86,87,90,95,100,101,116,125,129,130,138] 31 (24.6) May [13,20,22,24,25,27-29,31,32,34,36,37,40,44,46,48,50,56,58,67,72,78-80,83,84,89,94,96, 99,103,104,108,113,120,124,132,137] 39 (31.0) June[15,16,23,33,35,39,45,47,49,57,59,66,71,74,85,88,93,97,106,107,109,112,123,126,128,131,[133][134][135][136] [16,18,20,25,30,31,36,37,39,41,46,47,49,50,56,58,67,69,70,…”

mentioning

confidence: 99%

“…Characteristics of technologies in the studies. [13-22,25,26,28,30,31,33,34,36-45,47,49-51,54-59,62-64,66-76,78,79,82-89,92,93,96,97, 99-103,105,107-116,118,119] 29,32,35,46,52,53,60,61,65,77,80,90,95,104,106,117] 17 (15.7) Both[20,25,29,34,41,44,45,47,49,51,56,58,61,69,70,73,76,80,81,83,86,[89][90][91][93][94][95]101,[104][105][106][107]114,115,119,120,122,123,[125][126][127][128]131,132,135,136] 46 (58.2) Built for purpose[14-16,18,20,23-26,31,34,37-39,47,50,53,54,57,62-64,67,69-72,74-77,87,90,96,97,100,101,107, 108,111,113,115,117,120,137] [26,29,44,45,52,75,78,81,85,88,89,93-95,103,104,106-109,117-119,121,122,124,126-136,138] 17,20-24,26-33,35,40,42,43,46,49,52,53,55,59-62,65-68,74,76,77,79,81,82,84,8...…”

mentioning

confidence: 99%

Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review

Abd‐Alrazaq¹,

Hassan²,

Abuelezz³

et al. 2021

J Med Internet Res

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Background Technologies have been extensively implemented to provide health care services for all types of clinical conditions during the COVID-19 pandemic. While several reviews have been conducted regarding technologies used during the COVID-19 pandemic, they were limited by focusing either on a specific technology (or features) or proposed rather than implemented technologies. Objective This review aims to provide an overview of technologies, as reported in the literature, implemented during the first wave of the COVID-19 pandemic. Methods We conducted a scoping review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) Extension for Scoping Reviews. Studies were retrieved by searching 8 electronic databases, checking the reference lists of included studies and relevant reviews (backward reference list checking), and checking studies that cited included studies (forward reference list checking). The search terms were chosen based on the target intervention (ie, technologies) and the target disease (ie, COVID-19). We included English publications that focused on technologies or digital tools implemented during the COVID-19 pandemic to provide health-related services regardless of target health condition, user, or setting. Two reviewers independently assessed the eligibility of studies and extracted data from eligible papers. We used a narrative approach to synthesize extracted data. Results Of 7374 retrieved papers, 126 were deemed eligible. Telemedicine was the most common type of technology (107/126, 84.9%) implemented in the first wave of the COVID-19 pandemic, and the most common mode of telemedicine was synchronous (100/108, 92.6%). The most common purpose of the technologies was providing consultation (75/126, 59.5%), followed by following up with patients (45/126, 35.7%), and monitoring their health status (22/126, 17.4%). Zoom (22/126, 17.5%) and WhatsApp (12/126, 9.5%) were the most commonly used videoconferencing and social media platforms, respectively. Both health care professionals and health consumers were the most common target users (103/126, 81.7%). The health condition most frequently targeted was COVID-19 (38/126, 30.2%), followed by any physical health conditions (21/126, 16.7%), and mental health conditions (13/126, 10.3%). Technologies were web-based in 84.1% of the studies (106/126). Technologies could be used through 11 modes, and the most common were mobile apps (86/126, 68.3%), desktop apps (73/126, 57.9%), telephone calls (49/126, 38.9%), and websites (45/126, 35.7%). Conclusions Technologies played a crucial role in mitigating the challenges faced during the COVID-19 pandemic. We did not find papers describing the implementation of other technologies (eg, contact-tracing apps, drones, blockchain) during the first wave. Furthermore, technologies in this review were used for other purposes (eg, drugs and vaccines discovery, social distancing, and immunity passport). Future research on studies on these technologies and purposes is recommended, and further reviews are required to investigate technologies implemented in subsequent waves of the pandemic.

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The Influence of Telehealth for Better Health Across Communities

Cited by 33 publications

References 17 publications

Neighborhood Broadband and Use of Telehealth Among Older Adults: Cross-sectional Study of National Survey Data Linked With Census Data

Neighborhood Broadband and Use of Telehealth Among Older Adults: Cross-sectional Study of National Survey Data Linked With Census Data

Is telemedicine the answer to rural expansion of medication treatment for opioid use disorder? Early experiences in the feasibility study phase of a National Drug Abuse Treatment Clinical Trials Network Trial

Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review

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