Are State Telehealth Policies Associated With The Use Of Telehealth Services Among Underserved Populations?

Telehealth is viewed as an important strategy for improving access to care, for rural and underserved populations in particular.^1,2 There is growing evidence that telehealth is an effective way for patients to access primary care providers, specialists, and mental health services.^3–6 Telehealth usage is on the rise among patients across payer categories, including Medicare,⁷ Medicaid,⁸ the Department of Veterans Affairs (VA),⁹ and private health plans.¹⁰ Yet as recently as 2013, fewer than 1 percent of Medicaid and rural Medicare beneficiaries used telehealth services.^7,8 In contrast, 12 percent of VA beneficiaries received telehealth services in 2014,⁹ and over half of all Kaiser Permanente patient encounters are now provided through telehealth.¹¹

States have varying policies regarding parity of payment for in-person visits and telehealth services and different restrictions on where telehealth services can take place, who can provide them, and whether a medical professional (known as the telepresenter) is required to be with the patient.⁸ The American Telemedicine Association has been rating states since 2014 on thirteen telehealth coverage and reimbursement policies, including eleven related to Medicaid telehealth policies specifically. States that have the fewest restrictions on the types of providers, settings, or eligible technologies and have parity of coverage for in-person visits and telehealth get A or B ratings; those that have more restrictions or do not have parity laws get ratings of C or F. In recent years states have been updating their telehealth policies to support and expand the use of telehealth.¹² Since the initial report in 2014, ten states have enacted parity laws that require private insurance plans to cover services through telehealth to the same extent as those services are covered in person, bringing the number of states with parity laws to thirty-one. The number of states that received an overall favorable (A or B) coverage and reimbursement rating has also increased from twenty-nine to forty-three as of 2017.¹²

Several recent studies found that parity of coverage was associated with faster growth of telehealth use. Jonathan Neufeld and colleagues found that use of telemedicine in Medicare in Michigan grew following the adoption of telemedicine parity for commercial payers.¹³ Using commercial claims data, Jillian Harvey and colleagues also found that the states with parity laws saw significant increases in outpatient telehealth visits.¹⁰ The rate of telehealth visits among Medicare beneficiaries was higher in states with private parity laws than in states without such laws.^4,7 These studies also found that compared to rural Medicare beneficiaries who did not use telehealth, those who did were sicker and more likely to be younger than age sixty-five and to live in low-income communities.

Despite this growing body of research, evidence is still lacking on the prevalence of telehealth usage among the overall population and on whether state policies play a role in increasing that use after population characteristics are controlled for. Most prior studies are limited in that they focused on telehealth usage in one payer—Medicare¹³ or Medicaid⁸—or one health system—Kaiser Permanente¹¹ or the VA.⁹ When looking at the association of state policy and telehealth usage, most prior studies relied on descriptive analysis and did not fully control for population characteristics.

Understanding overall telehealth usage and its association with state policy and population characteristics simultaneously is important to allow policy makers to design better policies to boost telehealth usage and target populations most in need of telehealth services. Using four years of data from a nationally representative consumer survey that spans all payer types, this study fills an important gap by examining trends in telehealth usage over time across the US population and subgroups, as well as examining the role that state telehealth policies play in telehealth usage.

Study Data And Methods

Data And Study Population

This study used a nationally representative biannual survey of consumers commissioned by the Association of American Medical Colleges from June 2013 to December 2016. The online survey collected detailed information about respondents’ demographic characteristics (sex, age, race, and ethnicity), health status (limited activities because of physical or mental/emotional problems), insurance type, income, and rural location. It also asked if respondents had used telehealth in the past twelve months. Each survey wave included 2,000–3,500 respondents, with oversampling of rural, uninsured, Medicaid, black, Hispanic, and low-income populations in every other wave. To better represent the US adult population, data were adjusted with poststratification weights calculated by using the Current Population Survey.¹⁴ Data from a total of 22,294 respondents (adjusted number) were analyzed in the study.

Telehealth Use

Telehealth use was defined using eight binary measures based on questions (see online appendix exhibit A1)¹⁵ that asked if respondents had used telehealth in the past twelve months to make online appointments, view test results through a website, ask medical questions through email, and communicate with a provider in one of five ways (on the phone, via live video, using live text chat, via a mobile phone text message, and using a mobile app).

Willingness To Use A Video Call

Since 2015 survey respondents have been asked if they would be willing to discuss health issues (lab test results, follow-up after starting a new medication, depression, dizziness, fever, or cough) with a provider using a video call (adjusted $n=10,839$). We created a binary variable indicating respondents’ willingness to use a video call for one or more of the listed health issues.

Population Characteristics

We chose the following characteristics based on evidence from the literature:^4,7,8,10,13 sex, age (ages 18–24, 25–44, 45–64, and 65 or older), race (Native American, Asian, black, Pacific Islander, white, other, and multiple), ethnicity (Hispanic and non-Hispanic), patients’ self-reports of being “limited in any way in any activities because of physical problems” or “mental or emotional problems,” insurance type (private; Medicare [younger than age 65]; Medicare [age 65 or older]; Medicaid; Medicare and Medicaid; TRICARE, VA, Indian Health Service, or through a parent; and no insurance), income (less than $25,000, $25,000–$49,999, $50,000–$74,999, $75,000–$99,999, and $100,000 or more), and rural location.

State Telehealth Policies

To obtain state telehealth policies, we used annual reports by the American Telemedicine Association that capture the complex policy landscape of the fifty states and the District of Columbia on thirteen indicators related to coverage and reimbursement policies¹² (see appendix exhibit A2).¹⁵ State telehealth policy was converted to a binary variable indicating whether or not a state received a high rating on its overall coverage and reimbursement policies (A or B versus C or F).

Analysis

This study used a repeated cross-sectional time series design with a state fixed effects specification. We first conducted a trend analysis to examine overall telehealth utilization during 2013–16 by eight different modalities. We then examined whether telehealth use varied by population characteristics and state telehealth policies. In doing so, we focused on live video communication, the most predominantly reimbursed telehealth modality.¹⁶ Chi-square tests were run to examine whether the rates of live video communication differed by population subgroups and state telehealth policies. In addition, we compared the rate of actual live video usage to that of willingness to use a video call among population subgroups. Multivariate logistic regression models were constructed to examine the associations between the use of live video communication and both state telehealth policy and population characteristics. We also examined whether living in a state with less restrictive telehealth policies was related to a higher rate of live video communication (specifically among underserved populations) by including interaction terms of state telehealth polices with race, ethnicity, insurance type, income, and rural location. We included wave dummies to control for changes in telehealth usage over time and state dummies to capture any unobserved time-invariant factors within states.

In the sensitivity analyses, we modeled the thirteen individual indicators separately to test whether our use of the composite score was masking the impact of the individual policies. We also used the presence of parity laws instead of the American Telemedicine Association’s grading scores to compare our results to those of relevant prior studies.

This study was ruled exempt by George Washington University’s Institutional Review Board.

Limitations

This study had several key limitations. First, we may have overestimated the rates of telehealth use because the survey was conducted online and could have excluded people with limited internet access.

Second, although our analytic sample was adjusted to be representative of the US adult population, Medicaid and uninsured subgroups were slightly underrepresented, and rural populations were overrepresented (see appendix exhibit A3).¹⁵

Third, the sample included only adults who indicated that they or a physician believed that they needed medical care at least once in the past twelve months. This study should therefore not be extrapolated to children using telehealth or adults using telehealth for their dependents.

Fourth, our estimates could suffer from self-reported bias because the data were retrospective.

Lastly, the cross-sectional nature of this study limited our ability to determine a causal pathway between telehealth use and state policies. However, analysis using state fixed effects specification substantially minimizes potential biases related to existing differences within states.

Study Results

Trends In Telehealth Use Over Time

In the period 2013–16 rates of telehealth use increased, with the fastest growth reported in the use of live video communication (exhibit 1). The rate of live video communication rose from 6.6 percent in June 2013 to 21.6 percent in December 2016 (an average growth rate of 228.1 percent), while the rate of phone communication dropped from 58.6 percent to 47.6 percent (an average growth rate of −18.8 percent).

SOURCE Authors’ analysis of data from the Consumer Survey of Health Care Access of the Association of American Medical Colleges. NOTES “Communicating” means communicating with a provider. Examples of live video are Skype and FaceTime.

Characteristics Of Study Population

The study population was majority white (67 percent; adjusted $n=14,928$) and non-Hispanic (84.5 percent; adjusted $n=18,841$) (exhibit 2). Just over 40 percent (adjusted $n=9,709$) of respondents reported that they were “limited in any way in activities because of physical problems,” while about 20 percent (adjusted $n=4,726$) reported being “limited in any way in any activities because of mental or emotional problems.” Insurance type varied, with the largest segment of respondents (41.6 percent; adjusted $n=9,268$) having private insurance. About 15 percent (adjusted $n=3,473$) were Medicaid beneficiaries, and about 5 percent (adjusted $n=1,157$) reported having no insurance coverage. Nearly 20 percent (adjusted $n=4,367$) lived in rural areas.

Over the four-year study period 2,801 of 22,294 respondents (on average, 12.6 percent) reported that they talked with a health provider by live video (exhibit 2). Compared to the respondents who did not use live video communication, those who did tended to be male (68.2 percent versus 46.2 percent) and younger than age sixty-five (98.9 percent versus 76.1 percent) and have private insurance (51.5 percent versus 40.2 percent) and incomes greater than $75,000 (60.9 percent versus 30.8 percent) (exhibit 2). Similarly, respondents who used live video communication tended to be nonwhites (47.1 percent versus 30.1 percent) (data not shown) and Hispanics (23.5 percent versus 13.8 percent) and to have physical problems (54.9 percent versus 41.8 percent) and mental or emotional problems (48.2 percent versus 17.0 percent) that limited activity (exhibit 2). And respondents who used such communication tended to live in states with less restrictive telehealth policies (74.2 percent versus 65.3 percent) and not to live in rural areas (8.3 percent versus 21.6 percent).

Population Subgroups’ Willingness To Discuss Health Issues In A Video Call

In the period 2015–16 we found that the rate of willingness to discuss health issues during a video call was much higher than the actual use of live video (61.7 percent versus 17.6 percent) across all population groups (exhibit 3). Almost half of Medicare beneficiaries age sixty-five or older expressed willingness to use a video call, while only 1 percent had done so. Likewise, only 7 percent of the rural population used live video communication, but more than half expressed willingness to do so.

Likelihood Of Using Live Video Communication

We used three logistic regression models of the likelihood of using live video communication. Model 1 included only population characteristics and determined which of those characteristics were associated with that likelihood. Age was one of the biggest predictors of using live video communication, with younger populations being more likely to use it. Compared to those age 65 or older, the odds of using live video communication were 11.830 times for those ages 18–24, 16.240 times for those ages 25–44, and 3.685 times for those ages 45–64 (exhibit 4). The likelihood of using live video communication was also higher for nonwhite and Hispanic populations (data not shown). Respondents who had physical problems and mental or emotional problems that limited activities were more likely to use live video communication, compared to those who did not (odds ratios: 1.499 and 2.393, respectively) (exhibit 4). The odds of using live video communication were higher for Medicare beneficiaries younger than sixty-five (OR: 1.891), compared to people who had private insurance. An income analysis revealed that the odds of using live video communication were higher for people with higher incomes. In contrast, the odds of using live video communication were 0.346 times for Medicare beneficiaries age sixty-five or older and 0.656 times for people with Medicaid, compared to those with private insurance. Respondents in rural areas were also less likely to use live video communication (OR: 0.778), compared to urban or suburban respondents.

Model 2 added state telehealth policies to assess the association between those policies and the use of live video communication. The study did not demonstrate a significant association between the policies and use of live video communication across all population groups. After we controlled for population characteristics, we found that the odds of using live video communication were 1.338 times higher among respondents in states with less restrictive policies than among those in states with more restrictive policies, although this difference was not significant. The estimates on population characteristics in model 2 were very similar to those in model 1.

Lastly, model 3 added interaction terms between state telehealth policies and selected population characteristics (race, ethnicity, insurance type, income, and rural location) to further examine whether living in a state with less restrictive telehealth policies was associated with higher rates of live video communication among population subgroups—in particular, underserved populations. None of the interaction terms was significant, thus providing little evidence that state telehealth policies were particularly associated with higher use of live video communication among underserved populations. We report full regression results in appendix exhibit A4.¹⁵

Sensitivity Analyses

We conducted multiple sensitivity analyses to test whether our use of the composite rating of overall coverage and reimbursement policies was masking the impact of individual policies. We had hypothesized that less restrictive Medicaid telehealth policies would increase this population’s use of telehealth. At the same time, it is also possible that parity laws would increase telehealth availability for Medicaid beneficiaries, by helping make it possible to generate enough patient volume to support investments in telehealth. We modeled the individual indicators separately on the likelihood of live video usage by beneficiaries. However, we did not find any significant direct effects of Medicaid-specific policies on their targeted population or any significant spillover effects of private or state employee health plan parity laws (see appendix exhibit A5).¹⁵

We conducted a robustness check using the presence of parity laws, consistent with relevant prior studies.^4,10,13 While we did find a small positive bivariate association between the presence of parity laws and the use of live video communication, this relationship went away after we controlled for population characteristics (see appendix exhibit A6).¹⁵

Discussion

Telehealth use increased dramatically during 2013–16, with new modalities such as live video, live chat, texting, and mobile apps gaining traction across all population groups. Consumers used live video communication (the focus of our study) three times more often in 2016 than in 2013. This rapid growth is consistent with the results of other studies,^7–9,11 but we found that usage varied significantly by population characteristics. Age, health status, insurance type, income, and rural location were among the biggest predictors.

We found that the use of live video communication was most likely among people for whom it might be more difficult to take time off from work, as evidenced by high use among working-age and higher-income populations; and those who might have more difficulty leaving the home because of physical and mental limitations, including Medicare beneficiaries younger than age sixty-five (who presumably had substantial disabilities)—which is consistent with prior studies.^4,7 However, though telehealth is widely viewed as being a key strategy for increasing access to care for underserved populations, it was used less by Medicaid beneficiaries and low-income and rural populations, compared to the rest of the study population.

One explanation for why live video use remains low for underserved populations may relate to lack of availability. A 2016 consumer survey conducted by the American Telemedicine Association found that the most frequently cited barrier to using telehealth is that providers do not offer telehealth services.¹⁷ Indeed, only 38 percent of community health centers, which collectively are a major service provider for underserved populations, offer telehealth.¹⁸ Some of the centers are using retired and semiretired volunteers as a successful strategy for increasing access to telehealth in rural areas. However, many centers do not have a high enough patient volume to support investing in telehealth, and the restrictions around telehealth use at the centers, combined with confusion over which patients or services are covered, discourage that use. The Centers for Medicare and Medicaid Services (CMS) recently released proposed rules for 2019 to promote access to virtual care no matter where people live.¹⁹ Given that many private insurers and state Medicaid programs follow Medicare, the proposed rules in support of advancing virtual care could make it more affordable for community health centers to offer telehealth services.

State policies surrounding telehealth are becoming less restrictive. One would expect that when there are fewer restrictions, providers have less uncertainty about whether a telehealth visit will be reimbursed for a particular patient or service, making it less risky to offer telehealth services. However, we did not find any significant association between less restrictive state telehealth policies and increased use of live video communication once we controlled for population characteristics. These findings remained unchanged when we examined the impact of telehealth policies on specific populations, including Medicaid beneficiaries—the population most directly affected by the majority of state telehealth policies.

Policy Implications

Given our finding that many more respondents expressed willingness to use live video communication than actually used it, including members of underserved populations, it will be important to identify strategies for increasing access to care through telehealth.

Making telehealth easy to use is important but might not be enough to make providers or health systems invest the time, energy, and money needed to begin offering the service or expand its use. Policies that incentivize providers and health systems to use telehealth could be an important way to increase access to care for underserved populations. For example, offering financial incentives for providers to adopt telehealth may lead to increased usage, as payment incentives led to the increased adoption and use of electronic health records and patient-centered medical home status in safety-net clinics.^20,21

Health systems can incentivize providers to adopt telehealth through financial means as well as organizational culture shifts. For example, Kaiser Permanente Medical Group provided all of its 9,000 physicians with a complimentary iPhone and data plan to support telehealth use and counts telehealth visits the same as in-person visits when it rewards providers for meeting new consult targets. All of the providers have participated in some video visits.²²

Removing consumer barriers—particularly financial ones—to using telehealth may also be effective for low-income populations. This could include waiving copayments for telehealth visits, similar to waivers available to veterans,²³ or implementing waivers to purchase needed equipment such as smartphones (as well as data plans or internet access) to support telehealth visits, similar to the way CMS recently revised Medicare Advantage regulations to pay for Lyft or Uber rides for patients who had difficulty getting to appointments.²⁴

Even when telehealth service is available, consumers might not know how, when, and where to use it.²⁵ Enhancing consumer education in underserved communities could help increase telehealth use in underserved populations. This could be particularly helpful for increasing access to behavioral health, since all states offer some form of Medicaid coverage and reimbursement for behavioral health services provided by telehealth, with fifteen states having no restrictions or additional conditions of payment.¹²

Other efforts to increase the use of telehealth focus on funding telehealth infrastructure and providing technical assistance to support telehealth implementation in rural and underserved communities. Several states are using State Innovation Model funding to provide technical assistance and training to providers interested in offering telehealth. Arkansas is expanding its telehealth programs to include offering training and certification to rural mental health clinics, helping them address patient privacy challenges, establish secure network connectivity, and ensure eligibility for Medicaid reimbursement for telehealth visits.²⁶

As of 2015 the Health Resources and Services Administration had invested $10 million in telehealth network grants, along with $4.5 million in a national network of telehealth resource centers.²⁷ It also supports the use of telehealth by many of its health center grantees, to ensure that populations in rural and underserved areas have access to needed care.²⁷ States and foundations are also supporting telehealth growth by providing technical assistance, funding telehealth pilots at clinical sites, and building up telecommunications systems in the community.^28–30

However, it is important to note that even rural and underserved populations with enough access to technology have relatively low use of telehealth, compared to other populations. An area for future research would be to seek more insights into the role that federal, state, and local investments in telehealth resources play in increasing the use of telehealth by underserved populations.

Last but not least, federal and state efforts to move to value-based care and prioritize addressing social determinants of health often include telehealth as an important strategy for increasing access to care and enhancing the coordination of care for high-cost patients.^31–33 Demonstrating the role that telehealth can play in achieving the Triple Aim of improving quality and health outcomes while lowering the cost of care could prove to be a powerful incentive for increased uptake.

Conclusion

The use of telehealth increased dramatically in the period 2013–16 across all population groups. While we found evidence that populations with limited mobility (such as Medicare beneficiaries younger than age sixty-five and people with self-reported physical or mental health concerns that limit their activities) were among the highest users, key underserved populations (including Medicaid, low-income, and rural populations) had significantly lower use of telehealth. This study suggests that state efforts alone to remove barriers to using telehealth might not be sufficient for increasing use, and new incentives for both providers and consumers to adopt and use telehealth may be needed.

ACKNOWLEDGMENTS

This project was supported by the Health Resources and Services Administration of the Department of Health and Human Services through the Health Workforce Research Centers Program (Cooperative Agreement No. U81HP26493).

NOTES

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