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Introduction:Telehealth is becoming integral to health care delivery, which may create a higher need for better internet. This is the first study to examine whether users are willing to spend more on their internet if they are (1) more experienced in using telehealth, (2) more optimistic about telehealth benefits, and (3) less concerned about the difficulty of using telehealth. Methods:We surveyed 5,200 Americans about their willingness to pay (WTP) for internet speed and quality on the one hand, and their (1) prior use of telehealth, (2) opinion about the benefits of telehealth, and (3) opinion about the difficulties of using telehealth. We stratified the sample using the three aspects above and conducted a conjoint analysis to estimate the WTP for internet speed and quality within each stratum. Results:Compared with respondents who had never used telehealth, respondents who had used five to six different types of telehealth services were willing to spend 50.4% more on their internet plans. Users who most firmly believed in the benefits of telehealth were willing to spend 59.2% more than the most pessimistic users. Users who had the lowest concerns about the difficulty of using telehealth were willing to spend 114% more than users with the most perceived difficulty. Discussion:We found strong ties between the WTP for internet and prior telehealth use and perceptions of telehealth benefits and barriers. Thus, internet expenditures may be influenced by users' anticipation of using telehealth. Future studies may investigate the causality of the relationship. [ABSTRACT FROM AUTHOR]

Introduction:The COVID-19 pandemic brought about renewed interest and investment in telehealth, while also highlighting persistent health disparities in the Southern states. Little is known about the characteristics of those utilizing telehealth services in Arkansas, a rural Southern state. We sought to compare the characteristics of telehealth utilizers and nonutilizers among Medicare beneficiaries in Arkansas before the COVID-19 public health emergency to provide a baseline for future research investigating disparities in telehealth utilization. Methods:We used Arkansas Medicare beneficiary data (2018–2019) to model telehealth use. We included interactions to assess how the association between the number of chronic conditions and telehealth was moderated by race/ethnicity and rurality, adjusted for covariates. Results:Overall telehealth utilization in 2019 was low (n = 4,463; 1.1%). The adjusted odds of utilizing telehealth was higher for non-Hispanic Black/African Americans (vs. white, adjusted odds ratio [aOR] = 1.34, 95% confidence interval [CI] = 1.17–1.52), rural beneficiaries (aOR = 1.99, 95% CI = 1.79–2.21), and those with more chronic conditions (aOR = 1.23, 95% CI = 1.21–1.25). Race/ethnicity and rurality were significant moderators, such that the association between the number of chronic conditions and telehealth was strongest among white and among rural beneficiaries. Discussion:Among the 2019 Arkansas Medicare beneficiaries, having more chronic conditions was most strongly associated with telehealth use among white and rural individuals, while the effect was not as pronounced for Black/African American and urban individuals. Our findings suggest that advances in telehealth are not benefiting all Americans equally, with aging minoritized communities continuing to engage with more strained and underresourced health systems. Future research should investigate how upstream factors such as structural racism perpetuate poor health outcomes. [ABSTRACT FROM AUTHOR]

Purpose:To assess the factors associated with offering remote patient monitoring (RPM) services. Methods:We integrated three datasets: (1) 2019–2020 Area Health Resource Files, (2) 2019 American Community Survey, and (3) 2019 American Hospitals Association annual survey using county Federal Information Processing Standards code to evaluate associations between hospital characteristics and county-level demographic factors with provision of (1) post-discharge, (2) chronic care, (3) other RPM services, and (4) any of these three RPM service categories. These outcomes were analyzed using multi-level, mixed-effects multivariate logistic regression modeling to account for county-level clustering of hospitals. Findings:Among 3,381 hospitals, 1,354 (40.0%) provided any RPM services. Being part of a clinically integrated network (CIN) and private, non-profit (vs. public) ownership were respectively associated with 104.5% (95% confidence interval [CI]: 69.4–146.8%; p < 0.001) and 30.4% (95% CI: 2.5–66.0%; p = 0.031) higher odds of providing any RPM services. Critical access hospital (CAH) designation, for-profit (vs. public) ownership, and location in the South (vs. Northeast) were associated with significantly lowering odds of providing any RPM services by 36.2% (95% CI: 14.2–52.6%; p = 0.003), 70.1% (95% CI: 56.0–79.6%; p < 0.001), and 34.0% (95% CI: 2.8–55.1%; p = 0.035), respectively. Similar trends were found with the various RPM service categories. Conclusions:The factors most associated with provision of any RPM services were hospital-level factors. Specifically, being part of a CIN and private, non-profit ownership had the highest positive associations with offering RPM services whereas location in the South and CAH designation had the strongest negative associations. Further studies are needed to understand the reasons behind these associations. [ABSTRACT FROM AUTHOR]

• We propose a curve-fitting technique that complements existing estimation tools. • The average WTP for 1 Mbps faster internet is $1.13 per month. • The average WTP for a 1-tier quality upgrade is $45.52 per month. • Users with the lowest speed/quality benefit the most from a given internet subsidy. • WTP largely varies based on income and employment status. This paper adds to a growing literature on the willingness to pay (WTP) for internet services. We surveyed 5,200 respondents across four demographically diverse United States (US) states, and developed a curve-fitting WTP estimation technique that builds on existing conjoint analysis models. We find that users are willing to pay an extra $1.13 per month for a 1 megabits per second (Mbps) faster internet and $45.52 per month for better connection quality. We document a strong non-linearity: a given speed increment generates the most value for users with the slowest internet but confers negligible value on users with the fastest internet. Specifically, improving speed from 1 Mbps to 25 Mbps creates 2.32 times more value than improving from 25 Mbps to 100 Mbps. A similar non-linearity arises in terms of internet quality. We report large WTP discrepancies by income levels and employment status. The results corroborate that internet subsidies are most impactful if they first assist users with the poorest internet access. In this sense, subsidizing the right population could be as important as – if not more important than – raising funds to subsidize internet access. [ABSTRACT FROM AUTHOR]

Healthcare providers (HCPs) and patients are increasingly relying on telehealth services (healthcare provision over the internet) to provide and seek care. It turns internet access disparities into a health equity concern, i.e., poor internet access can contribute to poor health. In response, two federal programs in the United States – Healthcare Connect Fund and the Telecom Program – subsidize internet access for HCPs in rural or remote areas. I use a two-part pricing approach to examine the evolution of internet speed and price for HCPs that received internet subsidies during 2014–2020. I find that HCP internet is annually getting 30.77% faster and 5.23% cheaper. During the same period, the cost to subscribe to an internet service and the cost to raise bandwidth have annually fallen by 5.02% and 7.83%, respectively. A comparison of the trends between rural and urban HCPs suggests that the rural/urban divide in internet access has shrunk during the study years. It indicates that the subsidy programs likely have achieved their stated goal of improving rural internet. • I study the evolution of internet speed and price for healthcare providers who received internet subsidies. • During 2014–2020 their internet became 30.77% faster and 5.23% cheaper annually. • The subsidies did not improve internet speed beyond the national average. • The subsidies helped mitigate the rural/urban discrepancy in internet access. [ABSTRACT FROM AUTHOR]

Introduction: Telehealth has the potential to mitigate the lack of health care access in rural and underserved communities; however, telehealth is only viable where sufficiently high-speed internet broadband is available to patients. Existing broadband data sets may not accurately reflect the state of broadband, particularly in rural communities. We examined consumer internet speed test data from two organizations to see if the number of tests per 1,000 residents varied across county-level rurality., Methods: We analyzed county-level data from Measurement Labs (M-Lab) and Ookla for Good (Ookla fixed and mobile) across the calendar years 2020 and 2021. We used the number of tests conducted per 1,000 residents within United States counties as the outcome variable, and Rural-Urban Continuum Codes (RUCC) as the main independent variable of interest., Results: Using negative binomial models with robust standard errors, we found that the number of fixed speed tests conducted per 1,000 residents was generally lower in rural counties relative to counties with over one million residents. However, we found no associations between any categories of county-level rurality for the number of mobile tests conducted per 1,000 residents. Patterns of association with other covariates emerged as significant in some models and not in others, suggesting key differences among users generating speed tests among these data sources., Conclusions: Our findings demonstrate the poor representation of residents from very rural counties in M-Lab and Ookla fixed data sets of user-generated internet speed tests. Additional data are needed to inform broadband infrastructure investment to identify those communities most left behind by broadband expansion efforts., (© The Author(s) 2024. Published by Mary Ann Liebert, Inc.)

Introduction: The COVID-19 pandemic brought about renewed interest and investment in telehealth, while also highlighting persistent health disparities in the Southern states. Little is known about the characteristics of those utilizing telehealth services in Arkansas, a rural Southern state. We sought to compare the characteristics of telehealth utilizers and nonutilizers among Medicare beneficiaries in Arkansas before the COVID-19 public health emergency to provide a baseline for future research investigating disparities in telehealth utilization. Methods: We used Arkansas Medicare beneficiary data (2018-2019) to model telehealth use. We included interactions to assess how the association between the number of chronic conditions and telehealth was moderated by race/ethnicity and rurality, adjusted for covariates. Results: Overall telehealth utilization in 2019 was low ( n  = 4,463; 1.1%). The adjusted odds of utilizing telehealth was higher for non-Hispanic Black/African Americans (vs. white, adjusted odds ratio [aOR] = 1.34, 95% confidence interval [CI] = 1.17-1.52), rural beneficiaries (aOR = 1.99, 95% CI = 1.79-2.21), and those with more chronic conditions (aOR = 1.23, 95% CI = 1.21-1.25). Race/ethnicity and rurality were significant moderators, such that the association between the number of chronic conditions and telehealth was strongest among white and among rural beneficiaries. Discussion: Among the 2019 Arkansas Medicare beneficiaries, having more chronic conditions was most strongly associated with telehealth use among white and rural individuals, while the effect was not as pronounced for Black/African American and urban individuals. Our findings suggest that advances in telehealth are not benefiting all Americans equally, with aging minoritized communities continuing to engage with more strained and underresourced health systems. Future research should investigate how upstream factors such as structural racism perpetuate poor health outcomes.

Purpose: To assess the factors associated with offering remote patient monitoring (RPM) services. Methods: We integrated three datasets: (1) 2019-2020 Area Health Resource Files, (2) 2019 American Community Survey, and (3) 2019 American Hospitals Association annual survey using county Federal Information Processing Standards code to evaluate associations between hospital characteristics and county-level demographic factors with provision of (1) post-discharge, (2) chronic care, (3) other RPM services, and (4) any of these three RPM service categories. These outcomes were analyzed using multi-level, mixed-effects multivariate logistic regression modeling to account for county-level clustering of hospitals. Findings: Among 3,381 hospitals, 1,354 (40.0%) provided any RPM services. Being part of a clinically integrated network (CIN) and private, non-profit (vs. public) ownership were respectively associated with 104.5% (95% confidence interval [CI]: 69.4-146.8%; p < 0.001) and 30.4% (95% CI: 2.5-66.0%; p  = 0.031) higher odds of providing any RPM services. Critical access hospital (CAH) designation, for-profit (vs. public) ownership, and location in the South (vs. Northeast) were associated with significantly lowering odds of providing any RPM services by 36.2% (95% CI: 14.2-52.6%; p  = 0.003), 70.1% (95% CI: 56.0-79.6%; p < 0.001), and 34.0% (95% CI: 2.8-55.1%; p  = 0.035), respectively. Similar trends were found with the various RPM service categories. Conclusions: The factors most associated with provision of any RPM services were hospital-level factors. Specifically, being part of a CIN and private, non-profit ownership had the highest positive associations with offering RPM services whereas location in the South and CAH designation had the strongest negative associations. Further studies are needed to understand the reasons behind these associations.