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April 2023; 13 (2) Research ArticleOpen Access

Inequities in Telemedicine Use Among Patients With Stroke and Cerebrovascular Diseases

A Tricenter Cross-sectional Study

Imama A. Naqvi, Audrey S. Cohen, Youngran Kim, Jennifer Harris, Mary Carter Denny, Kevin Strobino, Nathan Bicher, Ryan A. Leite, Dylan Sadowsky, Comfort Adegboye, Nnedinma Okpala, Munachi Okpala, Sean I. Savitz, Randolph S. Marshall, Anjail Sharrief
First published March 14, 2023, DOI: https://doi.org/10.1212/CPJ.0000000000200148
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Abstract

Background and Objectives In response to the COVID-19 pandemic, outpatient stroke care delivery was rapidly transformed to outpatient evaluation through video (VTM) and telephone (TPH) telemedicine (TM) visits around the world. We sought to evaluate the sociodemographic differences in outpatient TM use among stroke patients.

Methods We conducted a retrospective chart review of outpatients evaluated at 3 tertiary stroke centers in the early period of the pandemic, 3/16/2020 through 7/31/2020. We compared the use of TM by patient characteristics including age, sex, race/ethnicity, insurance status, stroke type, patient type, and site. The association between TM use and patient characteristics was measured using the relative risk (RR) from a modified Poisson regression, and site-specific effects were controlled using a multilevel analysis.

Results A total of 2,024 visits were included from UTHealth (n = 878), MedStar Health (n = 269), and Columbia (n = 877). The median age was 64 [IQR 52–74] years, and 53% were female. Approximately half of the patients had private insurance, 36% had Medicare, and 15% had Medicaid. Two-thirds of the visits were established patients. TM accounted for 90% of total visits, and the use of TM over office visits was primarily associated with site, not patient characteristics. TM utilization was associated with Asian and other/unknown race. Among TM users, older age, Black race, Hispanic ethnicity, and Medicaid insurance were associated with lower VTM use. Black (aRR 0.88, 95% CI 0.86–0.91, p < 0.001) and Hispanic patients (aRR 0.92, 95% CI 0.87–0.98, p = 0.005) had approximately 10% lower VTM use, while Asian patients (aRR 0.98, 95% CI 0.89–1.07, p = 0.59) had similar VTM use compared with White patients. Patients with Medicaid were less likely to use VTM compared with those with private insurance (aRR 0.86, 95% CI 0.81–0.91, p < 0.001).

Discussion In our diverse cohort across 3 centers, we found differences in TM visit type by race and insurance early during the COVID-19 pandemic. These findings suggest disparities in VTM access across different stroke populations. As VTM remains an integral part of outpatient neurology practice, steps to ensure equitable access are essential.

The coronavirus disease (COVID-19) pandemic resulted in an unprecedented expansion in telehealth infrastructure.1,2 Telehealth covers a range of technologies, including telephone and live video as well as e-mail and text messaging.3 Telemedicine (TM) refers specifically to remote clinical services.4 Incentivized by Centers for Medicare and Medicaid Services, with changes in reimbursement policies during the COVID-19 pandemic, telemedicine use considerably expanded in traditional practices during the pandemic.5

Implementation of telemedicine for acute stroke care has improved access to thrombolysis and thrombectomy for stroke treatment by making stroke clinical expertise readily available despite geographic constraints.6 There remain extensive gaps in care for secondary stroke prevention, stroke recovery, and poststroke complication management, especially for socially high-risk groups.7 Telemedicine can offer many potential solutions for barriers to poststroke care. Patients surviving stroke may have limited access to outpatient care related to social factors including insurance status, access to transportation, income, and social support. Stroke-related disabilities such as impaired mobility and cognitive impairments create further impediments to traveling for office visits. These challenges are amplified in underserved racial and ethnic groups.

Structural inequities and social contexts give rise to disparities in health care access and utilization. For stroke care, this manifests as inequitable prevention and treatment leading to adverse health outcomes.8 Evidence suggests that 700 000 more US deaths would have been avoided by equalizing mortality rates between White individuals and Black individuals than would have been saved by medical advances between 1991 and 2000.9 These findings should motivate further investigation into differences in health care delivery involving marginalized and minoritized groups.

Disparities in telemedicine delivery for stroke services including in outpatient stroke practice are understudied,10 and difference in the type of TM care provided (video or telephonic) has been less known. Video TM (VTM) visits more closely simulate office visits and offer potential advantages over telephonic (TPH) visits. Particularly for stroke, unlike telephone visits, video visits allow for assessment of stroke-related deficits through remote physical and neurologic examinations, facilitate interactions with caregivers (outpatient care), and allow for visualization of the home environment.11 Understanding patient characteristics in relation to telemedicine visits among stroke survivors may help identify barriers and facilitators of telemedicine implementation into routine stroke practice during and after the pandemic. In this study, we sought to evaluate relationships between sociodemographic characteristics and access to telemedicine (video vs telephonic) for outpatient care among patients presenting to stroke clinics associated with 3 different comprehensive stroke centers across the United States during the early time of the pandemic.

Methods

Standard Protocol Approvals, Registrations, and Patient Consents

The study protocol was reviewed and approved for waiver by the Institutional Review Boards across the 3 programs. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

Study Participants

We performed a retrospective review of outpatient clinic data from 3 urban teaching hospital outpatient Stroke Clinic Programs. Our review included 1 clinic in Houston, TX (UTHealth); 2 clinics in Washington D.C. area (MedStar Health); and 2 clinics in New York City (Columbia). These centers have come together to create the Collaboration to Improve Outcomes, Preventive care, and Care Transitions after Stroke (CONnECT) consortium dedicated to multicenter health services research in postacute stroke care. This study included visits as they were conducted, in person or through TM (VTM or TPH) at participating sites at the beginning of the pandemic, from March 16, 2020, through July 31, 2020. All patients were offered TM video visits at each site by default at the start of the pandemic in March 2020 and could opt in for telephone visits if video visits were not possible. Patients could also opt-in for in-person visits with approval of the provider if they were not felt to be at high risk for serious complications of COVID-19 based on age or medical comorbidities. Bilingual staff were available at all sites. Interpreters or language line services were available for visits. Researchers abstracted patient demographic variables including age and insurance status at the time of visit, race, ethnicity, and sex from the electronic medical record (EMR) system. In case of unknown or missing code abstraction, individual charts were reviewed to identify self-reported data. Stroke type was determined as ischemic, hemorrhagic, transient ischemic attack (TIA), or other cerebrovascular diseases (that is aneurysm or radiographic small vessel disease). The 3 sites individually collected data for their outpatient clinics, and then, the data were pooled for analysis.

Outcomes and Exposure

The study outcomes included the use and type of TM, and the primary exposure was social and demographic characteristics. We determined whether the use of TM and type of TM differed by race/ethnicity and explored factors associated with TM use and type of TM including age, sex, insurance status, stroke type, and site. Visits were categorized as in-person office visit or TM. TM was further specified as video telemedicine (VTM) and telephone (TPH). Race and ethnicity were self-reported and categorized as non-Hispanic White (“White”), non-Hispanic Black (“Black”), Hispanic, non-Hispanic Asian (“Asian”), and Others/Unknown includes these additional groups that were not represented in sufficient numbers to inform analysis. The use of any TM and use of VTM among TM users were compared across race/ethnicity using White as a reference.

Statistical Analysis

Descriptive statistics for differences in baseline characteristics and outcome measures were assessed across race/ethnicity using the chi-square tests for categorical variables and Wilcoxon rank-sum tests for numeric variables. The data were presented as well by site to examine differences in characteristics of patients and TM use across sites. The association between telemedicine type and race/ethnicity was measured using the relative risk (RR) from a modified Poisson regression model adjusting for age, sex, insurance type, stroke type, and patient type (new or established).12 To account for site-specific effect and correlations among visits within the site, we conducted a multilevel analysis by allowing a random effect for residual components at each site level. We also performed subgroup analysis by site as a sensitivity analysis to assess whether the effect of race remained consistent. Significance levels were set at p < 0.05 for 2-tailed tests, and all analyses were performed using STATA 16.0 (StataCorp, College Station, TX).

Data Availability

Anonymized data not published within this article will be made available on reasonable request from the corresponding author.

Results

Patient Characteristics

A total of 2,024 visits were included from UTHealth (n = 878), MedStar Health (n = 269), and Columbia (n = 877). The racial/ethnic breakdown was as follows: White 45%, Black 27%, Hispanic 15%, Asian 4%, and other/unknown 9%. The median age was 64 [IQR 52–74] years, and 53% were female (Table 1). White patients were older and more likely to be men compared with other racial/ethnic groups (Table 1). Almost half the patients had private insurance, 36% had Medicare, 15% had Medicaid, and 2% were uninsured. Asian patients were most likely to have private insurance followed by White patients. Higher proportions of Black and Hispanic patients had Medicare or Medicaid insurance at 50% and 58%, respectively, and Hispanic patients had a higher percentage of uninsured visits. Most of the visits were for ischemic stroke (61%), and the percentage of ischemic stroke was highest among Black patients (70%) (Table 1). Between sites, race/ethnicity was significantly different, such as high percentage of Black patients (48%) at MedStar Health and 20% of visits at Columbia patients for Hispanic patients (eTable 1, links.lww.com/CPJ/A406).

View this table:
Table 1

Patient Characteristics by Race/Ethnicity

Factors Associated With Telemedicine Use

TM accounted for 89.6% of all visits, and there were no significant differences in the use of TM over office visits across race/ethnicity and other patient characteristics, apart from the 45–54 and 55–64-year-old age groups who were more likely to have an office visit (Table 2). We observed significant differences in the use of TM across program sites. Almost all visits at Columbia were conducted through TM (98.9%), whereas 80.3% and 89.6% were through TM at UTHealth and MedStar Health, respectively. From multivariable analysis, we found that Asian (aRR 1.03 (95% CI 1.01–1.04), p < 0.001) and other/unknown races (aRR 1.02 (95% CI 1.01–1.03), p < 0.001) had slightly higher use of TM compared with White patients.

View this table:
Table 2

Factors Associated With Telemedicine Use

Factors Associated With Type of Telemedicine

Among TM users, VTM accounted for 84.8% and VTM over TPH was associated with several factors (Table 3). Older age was associated with decreased use of VTM, and patients 75 years or older were 14% less likely to use VTM compared with younger age group (aRR 0.86 [95% CI 0.80–0.92], p < 0.001). Female patients were less likely to use VTM, but after adjusting other factors, the difference was not statistically significant. White patients had higher VTM use (89.2%) compared with Black (76.3%) and Hispanic (81.2%), and differences remained after adjusting for other factors (aRR 0.88, 95% CI 0.86–0.91, p < 0.001, and aRR 0.92, 95% CI 0.87–0.98, p = 0.005, respectively, for Black and Hispanic patients compared with White patients). Asian patients had similar VTM use (88.5%) compared with White patients (aRR 0.98, 95% CI 0.89–1.07, p = 0.59). In a subgroup analysis by site as a sensitivity analysis, we found similar trends across race/ethnicity (lower VTM use among Black and Hispanic patients and similar VTM use among Asian compared with White patients), although not all reached to statistically significant levels (eTable 2). Patients with Medicaid were less likely to use VTM compared with those with private insurance (aRR 0.86, 95% CI 0.81–0.91, p < 0.001). New patients were slightly more likely to use VTM, but this was not statistically significant after adjusting for other factors. Compared with ischemic stroke, hemorrhagic stroke or TIA had no different use of VTM but other cerebrovascular diseases had a slightly higher VTM use (aRR 1.06 [95% CI, 1.02–1.11], p = 0.003).

View this table:
Table 3

Factors Associated With Video Use Among Telemedicine Users

Discussion

The COVID-19 pandemic forced rapid changes in outpatient services, requiring a shift from in-person appointments to telehealth visits. As a result, telemedicine has become an alternative health care delivery model to provide outpatient service remotely while maintaining physical distance from their providers.13 In the outpatient setting, video-based interactions have been associated with greater satisfaction and enhanced communication compared with telephone encounters with patients.14 Several advantages to video-based outpatient visits identified by patients include convenience and decreased cost. However, patients do have concerns around privacy and the physician's ability to virtually perform physical examinations.15 Stroke patients may be particularly well-suited for outpatient video visits as neurologic assessments including NIHSS (NIH Stroke Scale) can be conducted through video interaction.16 Telemedicine implemented in rural areas has been successful in improved outreach and uptake for chronic neurologic care.17 In addition, many stroke patients have physical and cognitive impairments that make transportation to in-person visits costly and inconvenient and may result in higher no-show rates for in-person visits.

Our study reports important differences in access to telemedicine for outpatient stroke care across 3 large urban centers at the start of the pandemic. We found that 90% of all outpatient visits during the study period were conducted by telemedicine. Time to implementation, site practices in types of visits offered, and barriers in transition to telehealth during the pandemic likely contributed to differences in utilization among sites. We found higher utilization of telemedicine at Columbia in New York, where the first COVID-19 wave began. Although infrastructure was in place at this site, only up to 0.5% neurology outpatient visits were conducted through video telehealth in the months of the year leading up to the pandemic. Implementation for all sites may have been facilitated by preexisting acute stroke telemedicine or outpatient research infrastructure. Rapid changes to reimbursement policies for telemedicine, led by Centers for Medicare & Medicaid Services, supported this expansion.5 Inevitably, as the pandemic spread across the country and telemedicine became a routine part of outpatient practice, institutions across the country developed outpatient infrastructure for telemedicine and we believe our data support the need for continued growth of this infrastructure fostered by federal and state legislation.

However, with any new health care delivery model, it is important to establish that care is equitable, especially among clinically higher risk groups. In this study, we found patients in groups at higher risk for poor outcomes after stroke, including those of older age, Black or Hispanic race/ethnicity, and those with Medicaid, had lower VTM use. Race and ethnicity distribution were significantly different among sites in our study, but this finding did not affect our results overall as demonstrated in the sensitivity analysis by site with consistently lower use of video telemedicine among Black and Hispanic patients. Disparities by race and ethnicity are important to examine to drive improved access to care and health outcomes.9,18,19 Projected increases in stroke prevalence vary by racial and ethnic category, with the largest rises expected in men and women of Hispanic ethnicity and Black race.20 Stroke incidence and recurrence also vary by race.21,22 Black and Hispanic patients have higher risk of stroke than non-Hispanic White patients.23,-,26 Factors that contribute to health inequities include structural factors including access to education, income, wealth, and structural racism and everyday discrimination which may translate to lower health literacy, lower access to care, poor medication adherence and result in suboptimal control of risk factors, and adverse stroke outcomes.27 Where health disparities in stroke already exist, it is important to examine outpatient telemedicine practice for indications of these inequities at the onset of these services with the pandemic.

There are several potential barriers to video telemedicine use in patients with stroke and cerebrovascular diseases. Video visits in the outpatient setting require access and ready use of technology by patients and/or caregivers. Older adults and groups with poorer health literacy and limited English proficiency are most likely to have limited digital literacy and access.28 We found lower utilization of video telemedicine among older individuals perhaps because they may not be comfortable with telemedicine because of lack of experience or access. However, since the COVID-19 pandemic began, a recent survey among 2000 adults aged 50–80 years suggests fewer concerns about trying telemedicine among older adults especially among those with prior telemedicine visits.29 We also found lower TM utilization among those with Medicaid, which has been shown in previous studies in other populations.30 Among the general US population, the proportion of Black households who have access to computers (desktop/laptop, smartphone, or tablet) and internet connectivity is uniformly and disproportionately lower, compared with White households.31 However, Pew Research Center32 data suggest that in 2021, internet use did not differ significantly by race (93% White, 95% Hispanic, and 91% Black respondents). Furthermore, among stroke patients and their caregivers, internet access has been reported as comparable with the general population.33 However, persons residing in poorer, often non-White areas have been reported to suffer from greatly reduced internet speeds compared with their more affluent peers although they pay the same nominal fees for internet services.34 These considerable gaps in effective connectivity may play a role in disparities in telemedicine adoption. As we consider the various barriers to improved access, evidence suggests that by providing more options for care, access can be improved.35,36 Our results highlight opportunities for equitable utilization of telemedicine among patients with stroke and cerebrovascular disease.

As the world continues to adapt to successive waves of the pandemic, telemedicine remains an active component of outpatient stroke care for all 3 centers. Policies to expand services among stroke survivors should be informed by the factors that can affect access to this relatively new health care delivery model. Understanding barriers to telemedicine access and utilization can advance services and increase options for care. Furthermore, as these systems evolve to enhance data security and patient privacy, with sustained technical support and ease of use, acceptability of these networks can continue to grow.

Our study has several limitations inherent in its retrospective design. Although every attempt was made to verify race/ethnicity as self-reported in EMR documentation, this may not be as reliable as prospective data collection. For instance, data captured in the records to conduct this study may only characterize patients' sex as a biological attribute or might not adequately disambiguate sex from gender as a socially constructed identity. Therefore, persons who are transgender or gender nonbinary may have been inadvertently excluded or poorly categorized in this analysis. For that reason, we report sex disparities and use terms “male and female” in this report. To our best knowledge, the information in electronic records was self-reported. There was potential for misclassification of video vs phone visits, as in when a visit was scheduled as video but completed as telephone. In this instance, we verified scheduled visits with chart notes and reported these as they were conducted. Although interpreters or language line services were available at all sites, language barriers may have still contributed to observe disparities and this should be explored further in future studies. We only examined disparities early during the pandemic, and it is possible that access has changed with increased familiarity and availability of services. It may be difficult to make meaningful statements about long-term disparities. However, as persistent racial, ethnic, and socioeconomic disparities in digital literacy, access to internet services, and patient portal use have been demonstrated throughout the pandemic, it would be expected that disparities in telemedicine use and access would persist. Furthermore, these findings highlight how disparities emerge when a new approach to care delivery and new medical technologies are implemented and the importance of evaluating the impact of new models of care on existing disparities. Additional investigation into factors of TM visit adherence including posthospitalization follow-up adherence is warranted to understand the utility of telemedicine as a vehicle of transitional care delivery. We also did not examine other associations such as the level of disability or cognitive impairment or willingness of patients to allow for video encounters. Furthermore, we did not examine the complex relationships of social determinants of health (such as physical environment, social support, and economic stability) and TM access. Despite these limitations, our findings remain robust as we included data from 3 different comprehensive stroke center–associated clinics across the country serving diverse populations. Public health efforts to address the causes of these disparities in telemedicine-delivered outpatient care are urgently needed as the pandemic continues.

In our diverse cohort, we found substantial differences in TM visit type by race and insurance, with overall higher utilization among established patients. These findings suggest disparities in VTM access among patients at risk for poor outcomes after stroke. As VTM becomes more integral to outpatient practice, steps to ensure equitable access are essential, and we need further studies now given that the pandemic continues to interrupt health services across the globe. We urge the health care and research communities to formally assess the barriers to adoption of this new health care delivery model and develop patient-centered solutions to improve health equity for patients with stroke and cerebrovascular diseases.

Study Funding

This publication was supported by the National Center for Advancing Translational Sciences, NIH, through Grant No. KL2TR001874 and American Heart Association Grant No. 923718. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the AHA.

Disclosure

I.A. Naqvi is currently supported by National Center for Advancing Translational Sciences, NIH, through Grant No. KL2TR001874 and American Heart Association Grant No. 923718. M.C.Denny is a member of the Abbott speakers bureau and receives grant funding support from National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) and MedStar Health Research Institute; however, none of these are related to this work. A.Z. Sharrief is a consultant for Abbott and receives grant funding from the National Institute of Minority Health and Health Disparities (NIMHD). The other authors report no relevant disclosures. Full disclosure form information provided by the authors is available with the full text of this article at Neurology.org/cp.

TAKE-HOME POINTS

  • →During the early period of the pandemic, telemedicine use accounted for 90% of all outpatient stroke clinic visits.

  • →Inequities were noted among Black and Hispanic patients and those with Medicaid insurance with lower video telemedicine use.

  • →Time to implementation, site practices in types of visits offered, and barriers in transition to telehealth during the pandemic contributed to differences in utilization among sites.

Appendix Authors

Table

Footnotes

  • Funding information and disclosures are provided at the end of the article. Full disclosure form information provided by the authors is available with the full text of this article at Neurology.org/cp.

  • Submitted and externally peer reviewed. The handling editor was Associate Editor Belinda A. Savage-Edwards, MD, FAAN.

  • Received March 14, 2022.
  • Accepted January 26, 2023.

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

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