Disparities in Telehealth Offer and Use among U.S. Adults: 2022 Health Information National Trends Survey

Abstract

Objective:

Understanding the sources of telehealth disparities can inform efforts to ensure equity. This study examines disparities in telehealth offer and use to understand the role of health care providers in increasing telehealth access.

Methods:

This cross-sectional analysis of the 2022 Health Information National Trends Survey (n = 5,295) used survey-weighted proportions to characterize telehealth use and multivariable logistic regressions to test associations of sociodemographic and social determinants with (1) telehealth offer and (2) use among those offered the option.

Results:

Among U.S. adults, 57% were offered telehealth, 80% of whom used it. Technology difficulties and privacy concerns were barriers for 15%−20% of U.S. adults. Compared to telehealth users, most nonusers preferred in-person care (25% versus 84%). Age, education, geographic location, and broadband internet access were related to telehealth offer, whereas no significant disparities emerged in telehealth use.

Conclusions:

Telehealth use is widespread, but structural and provider-level engagement are needed to achieve equity.

Introduction

Telehealth use expanded as the health care system adapted to remote health care during the COVID-19 pandemic. As COVID-19 shifts to an endemic stage, telehealth remains in use at higher rates than prepandemic,¹ indicating an enduring shift toward virtual care. Research has identified barriers to effective patient-provider communication via telehealth, including technological difficulties and privacy concerns.^2,3 However, several studies have documented high levels of patient satisfaction with telehealth, with some data suggesting patients are more satisfied with telehealth than in-person visits.^4,5 Past research has also found that people who use telehealth tend to be younger, more highly educated, wealthier, of White race, and reside in urban areas.^6

–9 In addition, social determinants of health, including lack of reliable transportation and high-speed internet access, can shape whether telehealth is an available or desirable option for patients.^9
–11 As telehealth becomes more embedded in health care delivery, it is important to establish a baseline understanding of current telehealth use, barriers, and disparities to better guide and evaluate progress toward equitable access and benefit.

It is unclear whether disparities in patients’ telehealth use are driven by patient-level factors, such as patient preference, or by health system and provider-level factors that limit telehealth access for some patients. For example, clinicians in larger metropolitan areas are more likely to use telehealth than their rural counterparts.¹² Furthermore, some providers may fail to offer telehealth to patients who they believe will not use or benefit from it.¹³ Efforts to leverage telehealth to promote health care access and equity must be sensitive to sources of disparities in telehealth use at the patient level (e.g., digital literacy or individual preferences) and the health system and provider levels (e.g., capacity or willingness to offer telehealth services).

Health care providers’ offer and encouragement of health care options are key to patients’ decisions to use them.^14
–16 For example, a recent study found that racial disparities in patient portal use were largely driven by disparities in who was offered a portal by their health care provider.¹⁴ We hypothesize that sociodemographic factors and social determinants will similarly be more strongly associated with patients’ access to telehealth care as facilitated by their health care providers than with their decisions to use it when given the option. Using a nationally representative survey of United States adults, this study describes reports of telehealth offer, use, and barriers. Furthermore, it explores the associations of sociodemographic factors and social determinants of health with reported telehealth offer and use.

Methods

DATA AND SAMPLE

Data are from the National Cancer Institute’s Health Information National Trends Survey (HINTS) 6, a nationally representative survey of civilian, non-institutionalized adults living in the United States. The survey is not restricted to adults with a cancer history. Data were collected from March 7 through November 8, 2022, via mailed and web-based survey with a weighted overall response rate of 28.1% (n = 6,252). HINTS data are deidentified and thus exempt from review by the National Institutes of Health Office of Human Subjects Research Protections. HINTS 6 methodology details are available elsewhere.¹⁷ U.S. adults who did not receive any medical care in the past 12 months (n = 605) and those missing data on telehealth use (n = 206) or offer (n = 146) were excluded, resulting in an analytic sample of 5,295.

Measures

OUTCOME VARIABLES

All respondents were asked whether, in the past 12 months, they received telehealth care (defined as, “telephone or video appointment with a doctor or health professional”). Those who did not use telehealth were asked whether they had been offered the option for a telehealth visit (response options: yes/no; those who reported having a telehealth visit were coded as having received a telehealth offer).

Telehealth users were asked whether they chose telehealth for any of five listed reasons: because it was recommended or required by the health care provider, because it was more convenient, to avoid possible infection, for advice about whether in-person care was needed, and to include family or other caregivers (response options: yes/no) and which type of appointment they used telehealth for most recently.

Barriers to telehealth care included preference for in-person visits, technology difficulties, and privacy concerns and were assessed among telehealth users and nonusers who were offered a visit. Barriers were coded among telehealth users who agreed or strongly agreed that they had experienced technical problems, were concerned about privacy, or who disagreed or strongly disagreed that the care they received was as good as an in-person visit. Barriers were coded among nonusers who reported that they chose not to participate because they preferred an in-person appointment, were concerned about privacy, or thought the technology would be difficult to use.

INDEPENDENT VARIABLES

Sociodemographic characteristics and social determinants associated with disparities in telehealth use were the key independent variables of interest. These included age, race and ethnicity, highest level of education, comfort with current income, urban/rural residence, lack of reliable transportation, and broadband internet access. Multivariable models controlled for additional factors associated with health care access, quality, and engagement, including sex, U.S. Census region, frequency of nonemergency medical visits, diagnosis with a chronic health condition (i.e., cancer, diabetes, heart disease, high blood pressure, lung disease), or depression, and lack of insurance.

ANALYTIC METHODS

Analyses were conducted using Stata SE 18.0 (College Station, TX). Sample weights provided nationally representative estimates with 50 jackknife replicate weights for accurate standard errors. Weighted proportions described rates of telehealth use and offer, reasons, and barriers. Weighted bivariate and multivariable logistic regression models tested unadjusted and adjusted associations of sociodemographic factors with (1) telehealth offer and (2) telehealth use among those offered. Missingness among covariates ranged from 0% to 9.0% and was highest for race and ethnicity (9.0%), sexual orientation (6.9%), and perceived income (5.8%). Models used list-wise deletion.

Results

DESCRIPTION OF TELEHEALTH USE

Over half (57%) of U.S. adults reported that they were offered a telehealth option for their medical care in the past year, and nearly half (46%), or 80% of those offered the option, used telehealth. The most frequently endorsed reasons for choosing a telehealth visit were that it was recommended or required by a provider (73%) and that it was more convenient (66%; Fig. 1). Reasons for the most recent telehealth appointments included annual visits (18%), minor illnesses (30%), chronic conditions (21%), and mental health (16%; Fig. 2). Telehealth care barriers are shown in Fig.3. Technology and privacy barriers were similar among users and nonusers, with about 20% reporting technology difficulties and slightly fewer reporting privacy concerns. Among nonusers offered a telehealth option, most (84%) preferred an in-person appointment, whereas only 25% of telehealth users suggested a preference for in-person care by reporting that the care they received was not as good as an in-person visit.

Fig. 1.

Weighted percent of telehealth users selecting each of five reasons for choosing to use telehealth. Bars represent standard errors.

Fig. 2.

Weighted percent of telehealth users' primary reasons for their most recent telehealth visit. Bars represent standard errors.

Fig. 3.

Prevalence of barriers to telehealth care among telehealth users and nonusers who received a telehealth offer. Bars represent standard errors.

ASSOCIATIONS OF SOCIODEMOGRAPHIC AND HEALTH-RELATED CHARACTERISTICS WITH TELEHEALTH OFFER AND USE

As highlighted in Table 1, in a multivariable logistic regression model predicting whether individuals were offered a telehealth option in the past year, the odds of receiving a telehealth offer were higher among adults with a college or graduate degree (versus ≤ high school: aOR = 1.48, 95% CI = 1.14–1.92, p = 0.004) and with broadband access (aOR = 1.33, 95% CI = 1.03–1.71, p = 0.03). The odds of telehealth offer were lower among older adults (≥65 years versus 18–49 years: aOR = 0.59, 95% CI = 0.43–0.82, p = 0.003) and those living in rural micropolitan areas (vs. large metro areas: aOR = 0.60, 95% CI 0.37–0.98, p = 0.04). In the model predicting telehealth use, no sociodemographic or social determinants factors were related to telehealth use among those offered. Results of bivariate logistic regression models are presented in Supplementary Table S1 and did not meaningfully differ from the results of multivariable models.

Table 1.

Results of Multivariable Logistic Regression Models Testing Associations of Covariables with Telehealth Offer Among U.S. Adults Who Received Health Care in the Past Year and Telehealth Use Among U.S. Adults Who Were Offered a Telehealth Option, HINTS 6, 2022

	OFFERED TELEHEALTH (n = 4,572)				USED TELEHEALTH (n = 2,670)
	ODDS RATIO	95% CI		P-VALUE	ODDS RATIO	95% CI		P-VALUE
	ODDS RATIO	LOWER	UPPER	P-VALUE	ODDS RATIO	LOWER	UPPER	P-VALUE
Age (ref: 18–49 years)
50–64	0.68	0.50	0.92	0.02	1.11	0.68	1.80	0.67
65+	0.59	0.43	0.82	0.003	0.95	0.55	1.65	0.86
Race and Ethnicity (ref: non-Hispanic White)
Non-Hispanic Black/African American	0.95	0.69	1.31	0.75	0.77	0.46	1.31	0.34
Hispanic	1.40	0.98	1.99	0.07	1.08	0.69	1.70	0.74
Non-Hispanic Asian	1.03	0.53	1.99	0.94	0.76	0.14	4.30	0.76
Other Race/Ethnicity	1.23	0.67	2.27	0.49	1.02	0.51	2.01	0.96
Education (ref: High school degree or lower)
Some College	1.14	0.88	1.48	0.31	0.93	0.52	1.66	0.80
College degree or higher	1.48	1.14	1.92	0.004	1.06	0.61	1.85	0.84
Feelings about current income (ref: living comfortably)
Getting by on present income	1.13	0.91	1.41	0.27	0.95	0.66	1.35	0.76
Finding it difficult/very difficult on present	1.16	0.86	1.58	0.33	0.69	0.39	1.20	0.18
Location (ref: large metro)
Large fringe metro	0.93	0.70	1.22	0.59	1.20	0.76	1.88	0.43
Medium metro	0.90	0.66	1.22	0.49	0.85	0.52	1.39	0.52
Small metro	0.79	0.47	1.34	0.38	0.92	0.39	2.17	0.85
Rural-Micropolitan	0.60	0.37	0.98	0.04	1.02	0.61	1.69	0.94
Rural-Noncore	1.09	0.69	1.71	0.72	1.17	0.55	2.50	0.68
Broadband internet Access (ref: no)	1.33	1.03	1.71	0.03	1.26	0.77	2.06	0.35
Lack of reliable transportation (ref: no)	1.15	0.73	1.81	0.54	0.99	0.49	1.97	0.97
Female Sex (ref: Male)	1.18	0.92	1.50	0.19	1.74	1.20	2.52	0.004
Census Region (ref: Northeast)
Midwest	0.61	0.42	0.89	0.01	0.71	0.42	1.20	0.20
South	0.75	0.55	1.04	0.09	1.34	0.83	2.17	0.23
West	1.52	1.06	2.19	0.02	1.26	0.74	2.13	0.39
Nonemergency provider visits (ref: 2 or less)
3–4	1.51	1.17	1.95	0.002	1.52	1.01	2.29	0.05
5 or more	2.02	1.50	2.71	<0.001	2.23	1.46	3.41	<0.001
Chronic Health Conditions (ref: none)
1	1.33	0.97	1.81	0.07	0.93	0.53	1.61	0.78
2 or more	1.59	1.14	2.23	0.008	1.21	0.67	2.15	0.52
Depression (ref: no)	2.13	1.56	2.92	0.000	1.87	1.21	2.90	0.006
Insured (ref: no)	2.42	1.35	4.34	0.004	1.05	0.57	1.94	0.87

Discussion

In this U.S. population-based sample, almost three of every five adults who had a need for medical care in the past year reported that they were offered telehealth and almost half reported that they used telehealth, suggesting rates remain elevated in post-pandemic care. This provides additional information and context to data from the National Health Interview Survey, which estimated 37% of U.S. adults used telehealth in 2021.¹⁸ We found several sociodemographic factors and social determinants associated with telehealth offer, which subsequently impacts the ability to access telehealth care. In contrast, fewer factors were associated with telehealth use among those who had access through being offered a telehealth option. Findings suggest that lack of telehealth being offered is an important, distinct barrier from use and highlight the important role of health care providers in facilitating telehealth access for their patients.

People reported multiple reasons for choosing telehealth, identifying its flexibility in care delivery. For example, adults in poorer health may value telehealth to avoid infection, whereas adults lacking access to paid leave may appreciate the convenience telehealth affords.¹⁹ Importantly, the most commonly reported reason for using telehealth was health care providers’ recommending or requiring it, bolstering evidence of the importance of health care providers’ encouragement for telehealth use. Results also highlight that individuals use telehealth for varied appointment types. Future research should continue to examine the benefits and costs of telehealth across different appointment types. For example, telehealth may increase engagement with chronic disease management for people who might otherwise forego necessary care. Yet, telehealth could also reduce the uptake of preventive care, such as vaccinations delivered via in-person appointments. Understanding these tradeoffs will be critical to maximizing the benefits of telehealth while minimizing potential harms.

Importantly, most people who used telehealth believed that the care they received was as good as in-person care, suggesting that preference for in-person care is unlikely to be a barrier among telehealth users. However, those who chose not to use telehealth when it was offered to them largely did so based on a preference for in-person visits, suggesting a benefit for complementary telehealth and in-person options. We also found that approximately one in every five U.S. adults reported technological difficulties and concerns about the privacy of personal health information as barriers to telehealth use. Though these rates may be lower than earlier in the pandemic,³ continued efforts to improve ease of use and transparency are needed to minimize these barriers to telehealth use and benefit.

Sociodemographic factors associated with telehealth varied across models predicting its offer and use. Sociodemographic characteristics associated with telehealth offer were similar to the results of a study testing sociodemographic characteristics associated with telehealth use among all HINTS 6 respondents.⁹ However, these factors were not related to telehealth use when the model included only those who were offered a telehealth care option. Specifically, older adults, those without a college-level education, and those lacking broadband access had lower likelihoods of being offered a telehealth option for their care, but they were no less likely to use telehealth once offered the option. It is possible that providers’ expectations of who will want to use telehealth bias their offers or that providers serving these populations have lower capacity to offer telehealth care options.¹³ Previous research found that race and ethnicity and lack of reliable transportation were related to telehealth use, but these were not related to either telehealth offer or use in the current study. This may be in part due to this analytic sample excluding people with no health care appointments in the past year. Relationships of other covariates with telehealth offer and use largely replicated prior findings that women²⁰ and individuals with more health care needs or more frequent interactions with the health care system were more likely to receive a telehealth offer and to use it when offered.⁹

The current study is limited in its reliance on self-reported data, which may have introduced measurement error due to inaccurate recall of telehealth offer or other key study variables. The available HINTS items also limit the ability to identify the sources of disparities in telehealth offer and use. For example, sociodemographic disparities in telehealth offer may reflect different health care needs in populations that require in-person visits or other unknown patient, provider, or structural factors. Research is needed to understand these factors and resultant interventions designed to broaden telehealth access and usability for all U.S. adults.

Conclusions

Telehealth access and use remained high following its growth during the COVID-19 pandemic. High rates of telehealth use among those offered and widespread agreement with health care providers’ recommendations as a reason for using telehealth affirm the importance of providers supporting telehealth use. When examining disparities in telehealth use, failure to account for its offer may have the unintended consequences of implying that disparities in telehealth use are due to individual preference or capacity. This may, in turn, lead to a reliance on interventions targeting the individual, rather than consideration of additional provider- and structural-level solutions. We found that most disparities in telehealth use may be influenced by differences in who received the offer of telehealth, suggesting a need for interventions at the structural and provider levels to ensure telehealth access and benefits are widely and equitably distributed.

Footnotes

Authors’ Contributions

N.S.E.: Conceptualization, Methodology, Analysis, and Writing—original draft. R.E.J.: Conceptualization, Methodology, Writing-Review & Editing. R.C.V.: Conceptualization, Methodology, Writing-Review & Editing.

Disclaimer

The opinions expressed by the authors are their own, and this material should not be interpreted as representing the official viewpoint of the U.S. Department of Health and Human Services, the National Institutes of Health, or the National Cancer Institute.

Disclosure Statement

The authors report no conflicts of interest.

Funding Information

No funding was received for this article.

Supplementary Material

Supplementary Table S1

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Supplementary Material

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