Disparities in Telehealth Care in Multiple Sclerosis

Abstract

Background and Objectives

The COVID-19 pandemic has dramatically increased telehealth use. We assessed access to and use of telehealth care, including videoconferencing and usability of videoconferencing, among persons with multiple sclerosis (MS).

Methods

In Fall 2020, we surveyed participants in the North American Research Committee on Multiple Sclerosis Registry. Participants reported availability and receipt of MS care or education through telehealth. Participants who completed ≥1 live videoconferencing visit completed the Telehealth Usability Questionnaire (TUQ). We tested factors associated with access to and receipt of telehealth care using logistic regression. We tested factors associated with TUQ scores using quantile regression.

Results

Of the 8,434 participants to whom the survey was distributed, 6,043 responded (71.6%); 5,403 were eligible for analysis. Of the respondents, 4,337 (80.6%) were women, and they had a mean (SD) age of 63.2 (10.0) years. Overall, 2,889 (53.5%) reported access to MS care via telehealth, and 2,110 (39.1%) reported receipt of MS care via telehealth including 1,523 (28%) via videoconference. Among participants who reported telehealth was available, older age was associated with decreased odds of having a telehealth video visit; higher income and being physically active were associated with increased odds. Older age and moderate to very severe visual symptoms were associated with lower perceived usability of telehealth.

Discussion

Older age, lower socioeconomic status, and disease-related impairments are associated with less access to and use of telehealth services in people with MS. Barriers to telehealth should be addressed to avoid aggravating health care disparities when using digital medicine.

Telehealth can be classified as live video conferencing, asynchronous video (store and forward), remote patient monitoring, and mobile health.¹ Previously, we found that people with multiple sclerosis (MS) commonly use mobile health apps,² but older individuals and those of lower socioeconomic status were less likely to use them.

Health communication continues to evolve, and the COVID-19 pandemic has dramatically increased telehealth use over a short time.³ In a South American study of clinicians with expertise in demyelinating disorders, fewer than one-fifth reported telehealth experience prepandemic, whereas nearly four-fifths reported use during the pandemic.⁴ In Norway, most hospital-based neurologists reported increased use of telephone and video consultations early in the pandemic; however, telehealth was considered less satisfactory for care of MS than for headaches or epilepsy.⁵

Although telehealth could improve access to care, it could also aggravate disparities due to the need for a reliable electronic device and internet access, and due to neurologic impairments. A review of telemedicine in MS management noted that patients with cognitive and visual impairments had challenges using telemedicine.¹ Evaluations of telehealth access and experience from the perspective of the person with MS have been limited, relying on small samples of higher socioeconomic status and relatively focused assessments of satisfaction.⁶

We assessed current access to, and use of, telehealth care including the use of videoconferencing and usability of videoconferencing. We hypothesized that individuals of lower socioeconomic status would have lower access to and use of telehealth care and that greater disability with respect to vision, cognition, and hand function would be associated with lower usability of videoconferencing.

Methods

Study Population

The source population was participants in the North American Research Committee on Multiple Sclerosis (NARCOMS) registry, a self-report registry for persons with MS.⁷ NARCOMS participants complete questionnaires online or by mail at enrollment. At enrollment, participants report sociodemographic and clinical information, which is updated semiannually thereafter. For this study, we used information from the enrollment and fall 2020 questionnaires.

Standard Protocol Approvals, Registrations, and Patient Consents

Participants permit use of their deidentified information for research. At the time of the fall 2020 survey, the NARCOMS registry was approved by the Institutional Review Board of Washington University at St. Louis.

Participant Characteristics

We used birthdate, sex, race, ethnicity, and education level reported at enrollment. Race and ethnicity were categorized as White or non-White given the small number of participants in the latter category. Consistent with prior work,² we categorized the education level as high school/General Educational Development Test and postsecondary (associate's degree, bachelor's degree, postgraduate education, and technical degree).

From the fall 2020 questionnaire, we obtained annual household income, zip code, disability status, symptom severity, current employment status (full time/part time and not employed), health insurance status (yes/no), comorbidities, current smoking status (yes/no), alcohol intake (never, monthly or less, 2–4 times/month, 2–3 times/week, and ≥4 times/week), and any physical activity. Participants reported annual household income as ≤$50,000, $50,001–$100,000, >$100,000, and “I do not wish to answer.” Using zip codes, we classified participants into rural-urban commuting area codes, which classify census tracts based on urbanization, population density, and daily commuting.⁸ These were aggregated as urban focused, large rural city/town focused, small rural town focused, and isolated small rural town focused. Disability status was reported using the single-item Patient Determined Disease Steps (PDDS), which has response options ranging from 0 (normal) to 8 (bedridden); it correlates highly with the Expanded Disability Status Scale score.⁹ The PDDS was categorized as mild (0–1), moderate (2–4), and severe (5–8).¹⁰ Participants reported symptom severity using SymptoMScreen, which includes 1 item for each of walking/mobility, hand function/dexterity, spasticity/stiffness, bodily pain, sensory symptoms, bladder control, fatigue, vision, dizziness, cognitive function, depression, and anxiety domains.^11,12 Each item is scored from 0 (not affected at all) to 6 (total limitation). Participants reported whether a doctor had diagnosed them with comorbidities including anxiety disorder, depression, autoimmune thyroid disease, diabetes, hypertension, hyperlipidemia, heart disease, chronic lung disease, irritable bowel syndrome, psoriasis, fibromyalgia, seizure disorder, migraine, sleep apnea, stroke, and cancer. We summarized comorbidities as a count (0, 1, 2, and ≥3). Alcohol intake was dichotomized as yes/no.

Telehealth

The survey provided a definition of telehealth: “Telehealth is the use of technology (e.g., cell phones, Internet, video conferencing) to deliver health care, health information or health education at a distance. Some common examples of telehealth include remote monitoring, two-way interaction between a patient and health provider, communicating health history information to a specialist for evaluation or targeted text messaging that promotes healthy behavior.” Participants were asked about availability of MS care or education with their provider through telehealth (yes/no) and whether MS care or education had been provided through telehealth (yes/no/unsure). We did not define the type of provider (i.e., physician).

Participants who indicated that care had been provided through telehealth were asked whether they had had ≥1 live videoconferencing visit and to name the system used. Participants completed the Telehealth Usability Questionnaire (TUQ) with respect to their most recent video conferencing visit with their MS care provider.¹³ The TUQ was developed to assess usability across the various types of telehealth systems and is the most frequently used questionnaire for evaluating telemedicine services.¹⁴ The usability factors (number of items) included usefulness (3), ease of use and learnability (3 items), interface quality (4), interaction quality (4), reliability (3), and satisfaction and willingness to use the system for future interactions (4). Item responses ranged from strongly disagree (1) to strongly agree (5). The responses to the items on each subscale are summed; maximum scores for each subscale ranged from 15 to 20.

In the spring 2017, we had asked participants about electronic exchange of health information using questions from the Health Information National Trends Cycle 4 survey. In the present survey, we repeated 1 question, specifically, “How interested are you in exchanging the following types of medical information with a health care provider electronically?” and listed the following types of medical information: appointment reminders, general health tips, medication reminders, laboratory/test results, diagnostic information (e.g., medical illnesses or diseases), vital signs (e.g., heart rate and blood pressure), lifestyle behaviors (e.g., physical activity and food intake), symptoms (e.g., nausea and pain), and digital images/videos (e.g., photographs of skin lesions). Responses used a Likert-type response format with responses of not at all, a little, somewhat, and very.

Analysis

For this analysis, we selected participants residing in the United States who had complete information regarding sex and age and responded to the question as to whether they had used telehealth. We summarized participant characteristics, responses about interest in electronic exchange of medical information, and scores for the TUQ subscales using descriptive statistics including mean (SD), median (interquartile range), and frequency (percent).

We conducted multivariable logistic regression analyses to test factors associated with (1) access to MS care or education via telehealth; (2) receipt of any MS care or education via telehealth in general; and (3) receipt of telehealth via videoconference. For each model, we included these covariates: age (continuous), sex (women as reference), race (White as reference), income (<$50,000 as reference), education (high school/general educational development test as reference vs postsecondary), health insurance status (no as reference), employment status (unemployed as reference), number of comorbidities (0 as reference), smoking (no as reference), any physical activity (no as reference), any alcohol intake (no as reference), and severity of symptoms related to cognition, hand function, vision, and mobility (mild as reference). Model assumptions were assessed using standard methods. Model fit was assessed using the Hosmer-Lemeshow goodness-of-fit statistic, and we report model c-statistics.

We tested factors associated with the TUQ score using quantile regression as this regression model does not require distributional assumptions. The median (50th quantile) was the primary analysis while secondary analyses modeled the 20th and 80th quantiles. We report a pseudo-R² as a measure of model goodness of fit.¹⁵ The covariates were the same as in the logistic regression analyses with 1 exception. The number of persons without health insurance was so small that this impeded model convergence at the 20th and 50th quantiles so it was removed as a covariate. Statistical analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC).

Data Availability

The data sets generated and analyzed during this study are held by the NARCOMS registry (narcoms.org).

Results

Participants

The survey was distributed to 8,434 participants, of whom 6,043 (71.6%) completed it. Compared with responders, nonresponders were more likely to be non-White and to have less education and a greater disability (eTable 1, links.lww.com/CPJ/A332). Of the responders, 5,403 (89.4%) met the inclusion criteria. Most participants were White, women, and had a postsecondary education. Two-thirds of participants had moderate or severe disability as assessed using the PDDS (Table 1).

Table 1.

Clinical and Demographic Characteristics of Study Participants (n = 5,403)^a

Exchange of Medical Information

Interest in exchanging health information electronically with a health care provider varied by type of health information queried (eFigure 1, links.lww.com/CPJ/A332). Nearly 80% of participants reported that they were somewhat or very likely to be interested in exchanging test results electronically. Interest in receiving appointment reminders (73.0% somewhat/very likely) and diagnostic information (70.2%) was also high. Fewer than half of participants were somewhat or very likely to be interested in receiving electronic exchanges regarding general health tips, lifestyle behaviors, or medication reminders.

Access and Use of Telehealth

The characteristics of the participants who indicated that they had access to telehealth (n = 2,889, 53.5%), had received telehealth (n = 2,110, 39.1%), or accessed telehealth by videoconference (n = 1,523, 28.2%) are shown in Table 2. Most participants in the access to telehealth group were White women with a postsecondary education; two-thirds of participants had moderate or severe disability.

Table 2.

Characteristics of Participants Who Responded Affirmatively to Each Telehealth Question (N = Affirmative Response/Total Responses)

On logistic regression analysis, several characteristics were associated with participants reporting that MS care or education was available through telehealth (Table 3). Compared with having a high school education, having a postsecondary education was associated with increased odds of telehealth being available. Similarly, vs an annual income <$50,000, higher incomes were associated with increased odds of telehealth availability. Having more comorbidities vs no comorbidities, having moderate to severe mobility symptoms compared with mild symptoms, and being physically active were also associated with increased odds of access to telehealth. Older age was associated with reduced odds of being informed about telehealth availability.

Table 3.

Logistic Regression: Factors Associated With Access to and Use of Telehealth

Among participants who indicated that telehealth was available, demographic characteristics associated with receipt of MS care or education via telehealth shared similarities with those for being informed about telehealth availability (Table 3). Older age was associated with reduced odds of receipt of MS care via telehealth, whereas higher income and being physically active were associated with increased odds. However, comorbidity was not associated with receipt of care via telehealth. Specific symptoms (vision, cognition, mobility, and hand) were also not associated with receipt of care via telehealth.

Among participants who indicated that telehealth was available, older age was associated with decreased odds of care via videoconference, whereas higher incomes (vs an annual income <$50,000) were associated with increased odds. Compared with mild vision symptoms, moderate to very severe symptoms were associated with decreased odds of receiving care via videoconference.

Usability of Telehealth

Among those using videoconferencing, usability was high based on the TUQ (Table 4). At the 50th quantile, factors associated with lower perceived telehealth usability included older age and moderate to very severe vision symptoms vs mild vision symptoms (Table 5). Participants with household incomes of $50,000-$100,000 reported higher telehealth usability as vs incomes <$50,000. Findings were similar at the 20th and 80th quantiles of usability. At the 20th quantile, residence in an isolated small rural town was associated with higher perceived telehealth usability. Of the 690 responses regarding the videoconference system used, the dominant response (n = 340, 49.3%) was Zoom, followed by Doxy.me (n = 44, 6.4%) and Facetime (n = 40, 5.8%).

Table 4.

Responses to the Telehealth Usability Questionnaire (n = 1,523)

Table 5.

Quantile Regression: Factors Associated With Telehealth Usability (n = 5,403)

Discussion

In this large cross-sectional study, we examined access to and use of telehealth care among >5,000 participants with MS approximately 6 months into the COVID-19 pandemic. We focused on video visits because they facilitate an examination and are commonly required for payer billing so are more often requested by providers. Slightly over 5 in 10 participants reported access to telehealth, and 4 in 10 had received telehealth care. This is similar to a prior smaller survey that reported that one-third of respondents had had a telehealth visit because of the pandemic.¹⁶ Higher socioeconomic status, more comorbidities, being physically active, and moderate–very severe mobility symptoms were associated with increased odds of being advised of telehealth availability, whereas older age was associated with decreased odds; region of residence was not associated with telehealth use. Among participants who were advised telehealth was available, age, income, and physical activity were associated with receipt of telehealth care. Older age, lower annual income, and moderate–very serve vision symptoms were associated with decreased odds of care via videoconference.

A high proportion of participants were willing to exchange some information electronically with a health care provider.² In 2017, 84% of NARCOMS participants reported that they had exchanged medical information with a health professional, and nearly half had used a mobile health app. At that time, the willingness of NARCOMS participants to exchange information electronically was 77.5% for laboratory results, 69% for diagnostic tests, and 71.3% for appointment reminders, indicating that little change has occurred in these attitudes over 3 years. In a Canadian study, over 80% of participants with MS reported a high likelihood of using telehealth services such as for appointment scheduling, obtaining prescription renewals, and discussions regarding symptoms.¹⁷

Our findings regarding disparities in access to and use of telehealth with respect to age and socioeconomic status are consistent with findings in other populations. A survey conducted at an MS Center in Italy found that only higher levels of education and income were associated with interest in telemedicine, but not characteristics of MS such as mobility.¹⁸ These findings are similar to those in the general population. Of 148,402 patients attending primary care or specialty ambulatory care visits, only 54.4% completed a telehealth visit, of which 45.6% were video visits.¹⁹ Older patients and those of Asian, vs White, race had fewer completed visits. Comorbidity and higher income were associated with more completed visits. Older patients, women, and those with lower income were less likely to have video visits. Within a New England health system, patients who were older or lived in areas with lower income, less education, and less broadband availability were less likely to participate in video visits.²⁰

Older persons demonstrate less internet use, slower uptake of technology, and lower digital health technology use.²¹ They are more likely to express concerns about privacy, hearing, and eyesight.²¹ Individuals with lower income levels are less likely to have computers, more likely to access the internet on cell phones, and may have cell phone plans with limited data.²² In an urban primary care practice, one-third of individuals only had a phone to access video appointments, and 14% did not have any devices with a capability for a video appointment.²³ Limitations on the amount of phone data also posed challenges.

Older age and moderate to severe vision symptoms were associated with lower perceived usability of telehealth. Living in an isolated rural town was associated with higher perceived usability of telehealth for those in the lowest quantile of usability assessed. A review of 28 studies regarding the use of telehealth for MS care found that patients with cognitive and visual impairments had challenges using telemedicine,¹ but people with MS were satisfied with telemedicine for general MS care and for rehabilitation and cognitive assessments. A study of 36 participants with MS compared satisfaction with in-person and virtual follow-up visits via Zoom.⁶ Although the likelihood of recommending in-person and telemedicine visits in the future was similar, participants who lived closer to the clinic were less likely to indicate that they would return for another telemedicine visit.

Our study has limitations. Our response rate was 71%, but exceeded the typical response rate of 60% for medical surveys.²⁴ Responders differed from nonresponders with respect to race, ethnicity, education, and disability levels. NARCOMS participants enroll voluntarily, the number of participants reporting non-White race and ethnicity was small, and most participants were older women; therefore, our findings may not generalize well to individuals who self-identify as non-White, are younger, or with differing levels of education or income and higher levels of disability. Future studies should seek to assess these underrepresented groups. We did not define MS care provider, and experiences may have differed depending on the provider type. Where participants reported that they were not offered telehealth services, we do not know whether this is because the service was not available, not offered, or whether participants did not accurately recall being offered the service. We do not know when participants completed the usability questionnaire relative to having their telehealth visits, and lengthy delays could cause recall bias. We did not specifically query barriers to telehealth use, including video visits. We assessed usability of telehealth from the patient perspective, but did not assess usability of telehealth from the provider perspective or the effectiveness of the telehealth visit with respect to medical care. We conducted this survey early in the COVID-19 pandemic, and access to telemedicine and its usability will evolve. Future studies should reassess these issues in the postpandemic era. We focused on characteristics of participants who used telehealth services, but did not address whether telehealth use was medically appropriate or the outcomes of telehealth use. Future studies should address positive and negative outcomes related to telehealth use at the individual and health system levels, whether outcomes vary according to sociodemographic and clinical characteristics, and how this was affected by ongoing in-person visits, if any. Nonetheless, this study had several strengths including the large sample size and consideration of sociodemographic factors, clinical characteristics, and health behaviors.

Use of telehealth increased during the COVID-19 pandemic. Although telehealth has the advantages of convenience, reduced travel costs, and less missed time from work, it could worsen health care disparities. Our findings highlight this problem within a large MS population and suggest that health care systems, including its providers, need address barriers to telehealth for people with MS who are older, of lower socioeconomic status, and with physical and cognitive limitations.

Appendix. Authors

Study Funding

NARCOMS is a project of the Consortium of Multiple Sclerosis Centers (CMSC). NARCOMS is funded in part by the CMSC and the Foundation of the CMSC. The study was also supported in part by the Waugh Family Chair in Multiple Sclerosis and Research Manitoba Chair (to RAM).

Disclosure

R.A. Marrie: receives research funding from the CIHR, MS Society of Canada, MS Scientific Research Foundation, National MS Society, Crohns and Colitis Canada, the US Department of Defense, and the CMSC and is supported by the Waugh Family Chair in Multiple Sclerosis. L. Kosowan: nothing to disclose. G. Cutter: data/safety monitoring committees for AMO, BioLineRx, BrainStorm Cell Therapeutics, Galmed, Horizon, Hisun, Merck, Merck/Pfizer, OPKO Biologics, Neurim, Novartis, Orphazyme, Sanofi, Reata, Receptos/Celgene, Teva, NHLBI (Protocol Review Committee), and NICHD (OPRU oversight committee), and consulting/advisory boards for Biogen, Click Therapeutics, Genzyme, Genentech, GW, Klein Buendel, MedImmune, MedDay, Novartis, Osmotica, Perception Neuroscience, Recursion, Roche, Somahlution, and TG Therapeutics. R. Fox: consulting fees from AB Science, Actelion, Biogen, Celgene, EMD Serono, Genentech, Immunic, Novartis, Sanofi, and TG Therapeutics; advisory committees for Actelion, Biogen, Immunic, Novartis, and Sanofi; and research grant funding from Novartis. A. Salter: journal editor/member of editorial advisory board for Circulation: Cardiovascular Imaging. Full disclosure form information provided by the authors is available with the full text of this article at Neurology.org/cp.