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. 2022 Dec;12(6):e133–e142. doi: 10.1212/CPJ.0000000000200078

Telemedicine Utilization Among Patients With Multiple Sclerosis in the US Veterans Health Administration, 2010–2020

Hoda S Abdel Magid 1,✉, Shan Jin 1, William J Culpepper 1, Lorene M Nelson 1, Mitchell Wallin 1
PMCID: PMC9757110  PMID: 36540144

Abstract

Background and Objectives

Telemedicine may help to bridge the specialty care access gap for patients with MS (PwMS) restricted by distance or disability. The objective of this study is to assess the frequency and longitudinal patterns of telemedicine utilization among PwMS and controls.

Methods

We conducted a population-based nested case-control study within the Veterans Health Administration (VHA) from January 1, 2010, to December 31, 2020. MS cases and controls were individually matched on sex, age, and Veterans Affair (VA) service region (Veterans Integrated Service Network). MS case and control participants sample sizes by year included 2010: 19,387/86,379; 2016: 19,752/88,535; and 2020: 16,451/78,315. Telemedicine encounter codes were used to identify telemedicine utilization among MS cases and controls in the VHA for 2010, 2016, and 2020. Telemedicine encounters were categorized according to mode (video, phone, and supplementary remote) and type of care provided.

Results

Patients in the VHA have had increasing utilization of telemedicine over the past decade. Among PwMS, mean telemedicine encounters increased steadily from 2010 to 2020 (5.6–10.5 encounters/patient, respectively). Across all years, MS cases were significantly more likely than controls to use telemedicine. The odds ratios (ORs) (95% confidence interval [CI]) of any telemedicine utilization comparing MS cases with controls in 2010, 2016, and 2020, respectively, were 1.5 (CI: 1.3–1.5), 1.9 (CI: 1.8–2.0), and 1.7 (CI: 1.6–1.8). Compared with non-Hispanic White veterans, non-Hispanic Black veterans were more likely to use telemedicine (adjusted OR = 1.5; [CI: 1.40–1.60]). The most common and least common modes of telemedicine among cases and controls were telephone and supplementary remote, respectively. Comparing 2010 with 2020, the largest increases in telemedicine utilization exhibited among MS cases were among primary care, specialty care, specialty neurology care, and other types of health care. States with the highest increases in telemedicine utilization were AL, CA, CO, FL, GA, KS, IL, NY, and SC. PwMS tended to live in counties with more adverse social determinants of health compared with controls.

Discussion

PwMS were significantly more likely to use telemedicine than their matched controls. There were significant increases in telemedicine utilization between 2010 and 2020. The VHA has a robust telemedicine system of care that has grown to supplement in person care more so than other US health care systems. Future work is needed to assess the determinants of telemedicine utilization.

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Multiple sclerosis (MS) is the most common progressive neurologic disease of young adults with a course that can produce disability in all major CNS domains.1 With 23 FDA-approved disease-modifying treatments (DMTs), the management has become more complex over the past 2 decades, requiring both specialty neurology and interdisciplinary care involving multiple health care providers.2

At least 31% of patients with MS (PwMS) do not have access to specialty care.3-5 Moreover, PwMS may face multiple interrelated barriers accessing specialty care that include transportation and cancelled referrals.6 Telemedicine, the practice of clinical care at a distance with the aid of technology, may be a potential bridge to close the specialty care access gap for PwMS restricted by distance or disability.7-10 Telemedicine has been an effective tool to maintain health care access when outpatient or inpatient care is disrupted, especially during natural disasters and most recently during the COVID-19 pandemic.6,11-13 There are several types of telemedicine services relevant for MS care including phone, video, and supplementary remote telemedicine. Phone and video formats allow providers and patients to communicate in real time. Supplementary remote telehealth utilization is the use of technologies to asynchronously acquire and store information to be forwarded for later evaluation by a specialist. In this study, we found that among MS cases and controls using telehealth, the least common mode was supplementary remote. This is probably because this mode requires the transfer of data for surveillance or procedural based tasks, and most telehealth encounters in our study involved simultaneous provider and patient interactions. Potential ways to increase adoption of store and forward technology for PwMS include increasing remote monitoring in the home (e.g., Fitbits), remote cognitive assessments, and data sharing with specialists and patients.7 The findings, however, were mixed about the rate and pattern of utilization of telemedicine by PwMS. To our knowledge, a comprehensive examination of telemedicine utilization among PwMS in the United States has not been conducted. To address this gap, we conducted a population-based evaluation of MS telemedicine utilization within the national VHA health care system and compared telemedicine use between PwMS and their matched controls. Our a priori central hypothesis was that PwMS would use telehealth care more frequently than their matched controls.

Methods

Data Collection

We conducted a nested case-control study within the VHA population. The study population pool was all registered patients within the VHA's Corporate Data Warehouse (CDW) between January 1, 2010, and December 31, 2020.

Veteran Patient Characteristics

Age, sex, race, ethnicity, urban/rural status, geographic region, and zip code were retrieved from VHA's electronic health record database, the CDW. Race and ethnicity were defined by the standard Department of Defense and VHA classification system and self-reported. Race categories included non-Hispanic White, non-Hispanic Black, Asian, and American Indian/Alaskan Native. Ethnicity categories included self-reported Hispanic and non-Hispanic. Geographical region was determined by the VHA's Veterans Integrated Service Networks (VISNs) and primary VA Medical Center. There are 18 VISNs in the VHA, regional systems of care, in the United States.14 Urbanized areas were defined by the US Census Bureau.15 Rural areas were defined as areas having a population density less than or equal to 7 people per square mile; all other areas were defined as urban. Veteran's home zip code was used to geographically link publicly available area-based social determinants of health.

MS Case Ascertainment and Control Selection

MS cases were identified using a validated algorithm for patients in administrative health claims data sets between 2010 and 2020.17 The validated algorithm required MS cases to have ≥3 MS-related claims from any combination of an inpatient diagnosis, outpatient diagnosis for MS (ICD9 or ICD10), or DMT claim within a 1-year period. For VHA, patients who had a MS military service-connected designation also met the algorithm case definition. Algorithm-identified MS cases were included in VHA's National Multiple Sclerosis Database.16 We identified up to 5 healthy controls for each MS case and matched on age- (within 1 year), sex-, and VISN. We required that controls had never had an MS ICD encounter within VHA or never used MS DMTs.

Telemedicine Utilization

Telemedicine clinic stop codes and Current Procedural Terminology (CPT) codes were used to identify telemedicine utilization in the VHA for 2010, 2016, and 2020. Several thousand telemedicine encounters were identified over the 10-year period, and the mean outpatient and telemedicine encounters have previously been cited.17 We selected 2010, 2016, and 2020 as our primary years of analysis to cover the beginning, middle, and end of the 10-year period and the first year of the pandemic. Encounters were classified into the type of care and method of care delivery among the following mutually exclusive groups: primary care, mental health care, specialty care, rehabilitation care, emergency/urgent care, diagnostic/ancillary care, specialty neurology, or other. The methods of telemedicine delivery were categorized as video, phone, or supplementary remote. A detailed data dictionary and codes for all telemedicine utilization variables used in this study and their corresponding encounter types, SAS code, primary and secondary stop codes, CPT code, and CPT modifier code are described in eTable 1 and eTable 2 in the Supplement (http://links.lww.com/CPJ/A378). In addition, eTable 3 (http://links.lww.com/CPJ/A378) in the Supplement presents the mean telemedicine utilization in the number of visits per year by primary and secondary stop codes, CPT code, and CPT modifier code. Clinical care and use of telemedicine for PwMS in VHA are guided by the national VA MS Center of Excellence (MSCoE) leadership.18

County-Level Social Determinants of Health

Veterans home zip code was used to geographically link 18 publicly available area-based sociodemographic measures as proxies of Veterans' county-level social determinants of health (SDH), spanning from 2012 to 2018. A detailed table describing each county-level SDH, source, and original variable name from the source are provided in eTable 4 (http://links.lww.com/CPJ/A378). We focused on covariates addressing measures of poverty, education, health insurance, crowded housing, broadband access, income inequality, historic unemployment rates, and county composition of non-native and non-Hispanic White residents. These covariates have been previously identified as being critical for health equity among veterans, the general population, and for telemedicine.6,18-23

Statistical Analysis

We calculated the mean (standard deviation) of telemedicine utilization for all encounters (outpatient and inpatient) and telemedicine encounters among cases and controls for 2010, 2016, and 2020. We classified telemedicine utilization if they had any video, phone, or supplementary remote telemedicine encounters during the year. Trends in the number of encounters overall, by type of care, and by care delivery method were described graphically. In addition, we created maps of the mean level of telemedicine utilization using veterans' home zip code. Zip codes were geocoded to census tract using ArcGIS 10.5.1(Esri, West Redlands, CA 92373 USA) and OpenStreetMap (OSM, Open Database License). For all maps, the sample size was restricted to veterans with a valid address that could be mapped (mapping rate = 95%). State-level maps were produced using Stata's maptile/spmap mapping packages.24 To examine the association of patient characteristics and telemedicine utilization, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) using conditional logistic regression with strata defied by the 1:5 case-control–matched sets to predict any telemedicine utilization during each year. Key demographic covariates were adjusted through matching (sex, age, and VISN) and conditional logistic regression, which controlled for race/ethnicity, rural/urban status, and county-level percentage of households without broadband and percentage of households without a computer in 2018 (for 2020 models). All statistical analyses and graphical output were conducted in Stata SE 16.1 (StataCorp, College Station, TX).

Standard Protocol Approvals, Registrations, and Patient Consents

This study was approved by the institutional review boards of the University of Maryland/Baltimore VA Medical Center and Stanford University (HP-43983).

Data Availability

Owing to the U.S. Department of Veterans Affairs (VAs) regulations and our ethics agreement, the analytic data sets used for this study are not permitted to leave the VA firewall without a Data Use Agreement. This limitation is consistent with other studies based on VA data. However, VA data are made freely available to researchers with an approved VA study protocol.

Results

The final study population consisted of 19,387 cases and 86,379 controls in 2010; 19,752 cases and 88,535 controls in 2016; and 16,451 cases and 78,315 controls in 2020. The demographic characteristics of cases and controls across all years analyzed are presented in eTable 5 in the Supplement (http://links.lww.com/CPJ/A378). Overall, there were no significant differences between cases and controls by the matching factors age, sex, and VISN (p < 0.05).

Table 1 presents the mean and SD of telemedicine encounters per year among cases and controls in 2010, 2016, and 2020. Among cases, the mean total telemedicine encounters increased steadily from 2010 (mean 5.6 encounters per patient) to 2016 (mean 7.2) to 2020 (mean 10.5). Phone and supplementary encounters among cases more than doubled from 2010 (mean 3.7) to 2020 (mean 7.5) and 2010 (mean 0.4) to 2020 (mean 1.3), respectively. Video encounters, on the other hand, remained steady with means of 1.5 encounters per MS case in 2010 and 1.7 in 2020 but exhibited a decrease in 2016 (0.4). Trends among controls were similar with the mean total telemedicine encounters also increasingly steadily from 2010 (3.3 encounters per patient) to 2016 (4.1) to 2020 (6.4). eTable 6 (http://links.lww.com/CPJ/A378) shows the mean telemedicine encounters per year among cases and controls stratified by demographic characteristics across the 3 study years. Of note, across every year, among both cases and controls, non-Hispanic Black veterans had more telemedicine care than non-Hispanic White veterans.

Table 1.

Mean Telemedicine Utilization per Year Among Multiple Sclerosis Cases and Controls in the US Department of Veterans Affairs: 2010, 2016, and 2020a

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Coding for telemedicine shifted over the past decade as displayed in eTable 3 (http://links.lww.com/CPJ/A378). Among MS cases in 2020, telemedicine utilization defined by primary or secondary clinical stop codes was highest (9.5 encounters/year) and lowest for telemedicine utilization defined by CPT modifier only (0.8). However, a similar relationship was observed for 2016. In 2010, telemedicine utilization as defined by CPT or CPT modifier codes was highest among cases. Approximately 65.8%, 71.8%, and 78.2% of MS cases who had at least one visit per year in the 2010, 2016, and 2020 study cohorts used any telemedicine care (Table 2). Among controls, approximately 47.1%, 54.2%, and 63.8% of controls who had at least one visit per year in the 2010, 2016, and 2020 study cohorts used any telemedicine care. Across all years, MS cases were significantly more likely than controls to have any telemedicine utilization. The ORs (95% CI) of any telemedicine utilization comparing MS cases to controls in 2010, 2016, and 2020, respectively, were 1.47 (1.31–1.54), 1.88 (1.79–1.98), and 1.70 (1.63–1.77).

Table 2.

Frequency of Any Telemedicine Utilization Use and Multivariate Adjusted Odds Ratios Stratified by Case-Control Status and Demographic Characteristics in the US Department of Veterans Affairs: 2010, 2016, and 2020a,b

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Multivariate adjusted models in addition showed differences in telemedicine utilization by demographic characteristics (Table 2). Non-Hispanic Black veterans were more likely to use telemedicine care in the VHA than non-Hispanic White veterans. For example, in 2020, non-Hispanic Black veterans had 1.5 times higher odds of using any telemedicine care in the VHA than non-Hispanic White veterans (95% CI: 1.40–1.60). On the other hand, Asian-Pacific Islanders veterans were less likely than non-Hispanic White veterans to use any telemedicine, although these results were statistically significant only for 2016. The results were not statistically significant (p < 0.05) for ethnicity or rural/urban status across all models.

Trends in the mean number of telemedicine visits per year overall and stratified by care type are presented in Figures 1 and 2, respectively. In 2010, 2016, and 2020, the highest telemedicine utilization among cases and controls was conducted over the telephone and the lowest telemedicine utilization was conducted in supplementary remote format (Figure 1). Comparing 2010 with 2020, the largest increases in telemedicine utilization exhibited among MS cases were among primary care (0.2–2.8 episodes per year), specialty care (1.1–2.5), specialty neurology care (0.08–0.4), and mental health care (1.2–1.5). Of note, telemedicine-based mental health care increased among MS cases from 1.3 encounters/patient in 2010 to 1.5 in 2020. On the other hand, mental health care among controls increased from 1.2 in 2010 to 1.5 encounters per patient in 2020 (Figure 2).

Figure 1. Trends in Mean Telemedicine Utilization (Mean Number of Annual Visits) Among Multiple Sclerosis Cases and Controls in the US Department of Veterans Affairs: 2010, 2016, and 2020.

Figure 1

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Figure 2. Trends in Mean Telemedicine Utilization (Number of Visits) Among Multiple Sclerosis Cases and Controls in the US Department of Veterans Affairs: 2010, 2016, and 2020, Stratified by Care Subtype.

Figure 2

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Figure 3 presents choropleth maps of state-level spatial patterning of the mean number of telemedicine utilization visits per year among cases and controls in 2010, 2016, and 2020. We observed a significant increase in telemedicine encounters among PwMS with time (p < 0.001), but the temporal trend was relatively stable for controls. Among both cases and controls, states with highest telemedicine increases from 2010 to 2020 include California, Colorado, Kansas, Illinois, New York, South Carolina, Florida, Georgia, and Alabama. Of note, in 2020, among controls, states with the highest telemedicine utilization (means of 10.3–13.4 encounters per year) were Utah, Kansas, West Virginia, Connecticut, and Massachusetts. In contrast, among MS cases, the highest telemedicine utilization observed (means of 14.7–31.9 encounters per year) were in Illinois, Florida, South Carolina, New York, New Hampshire, Connecticut, and Massachusetts.

Figure 3. Spatial Patterning of the Number of Telemedicine Utilization Encounters by State Among Multiple Sclerosis Cases and Controls in the US Veterans Health Administration: 2010, 2016, and 2020.

Figure 3

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The mean for each county-level social determinant of health among cases and controls for 2010, 2016, and 2020 are provided in eTable 7 (http://links.lww.com/CPJ/A378). On average, across all years examined, MS cases tended to live in counties with more adverse social determinants of health than controls. For example, in 2020, we observed that compared with controls, PwMS lived in counties with more households without a computer, lower median income, higher crowded housing, and higher percentage of residents receiving food stamps, percentage of 65 + residents living alone or living in a multigenerational house, and higher percentage of persons in deep poverty. Overall, the trends in mean county-level social determinants of health among MS cases and controls remained steady from 2010 to 2016 to 2020.

Discussion

In this population-based nested case-control study, we observed that PwMS were significantly more likely to use telemedicine than matched controls and that there was significant variation in telemedicine utilization among PwMS in the VHA between 2010 and 2020. We found the number of telemedicine encounters among PwMS increased over time but was relatively stable for controls. From 2010 to 2020, telemedicine care among MS cases and controls was highest for non-Hispanic Blacks and lowest for American Indians/Alaskan Natives and varied by care type and geographic region. The highest and lowest telemedicine utilization modes were phone and supplementary remote formats, respectively. Supplementary remote telehealth utilization is the use of technologies to asynchronously acquire and store information to be forwarded for later evaluation by a specialist. In this study, we found that among the cases and controls using telehealth, the least common mode of telehealth used was supplementary remote. This is probably because this mode requires the least amount of procedural based tasks and that most telehealth utilization involves the provider and the patient simultaneously. Potential ways to increase adoption of this technology for PwMS include increasing remote monitoring in the home, cognitive assessments, and data sharing with specialists and patients.7 We also found increases in telemedicine utilization among MS cases for primary care, specialty care, specialty neurology care, and other types of health care. Increases in telemedicine for neurology patients may be because of increased access and implementation of the technology required for neurology telemedicine. Examples include increases in remote neurologic assessment implementation, telestroke capacity, and hospitals' rapid deployment of virtual encounters for neurology and its subspecialities.7,13,25 Moreover, coding of telehealth utilization has been increasingly used throughout the country since the COVID-19 pandemic, including at the VA health care system which demonstrated significant expansions of telehealth between 2020-2022.26

Despite being more likely to use telemedicine services and having more telemedicine encounters per year, PwMS tended to live in counties with more adverse social determinants of health than controls, including counties with fewer computers and broadband connections per household, deep poverty, and higher crowded housing. Moreover, we observed that PwMS were significantly more likely to use telemedicine than their matched controls even after controlling for area-level social determinants of health. One potential explanation for the finding that PwMS had higher rates of telemedicine utilization but also lower likelihood of living in a county with fewer computers and broadband connections per household is that PwMS are using multiple types of telehealth including phone telehealth requiring no internet connection. This is consistent with previous studies examining telehealth in the VA, including a study conducted between March 11, 2020, and June 6, 2020, demonstrating that older, homeless, and rural veterans were less likely to have video visits.11

Our findings showing increased telemedicine utilization over time and reaching significant peaks during the COVID-19 pandemic in PwMS are consistent with studies in other health care systems including the Centers for Medicare & Medicaid Services (CMS),27 OptumLabs Data Warehouse,28 and Kaiser Permanente.29 For example, in a study of Kaiser Permanente Southern California members from January 5, 2020, to October 31, 2020, Hispanic and low-income patients had the largest percentage increase in telemedicine use.29 In this study, we also observed state variability in telemedicine utilization, which may be related to differences in telemedicine access and policies within the VHA. In most private and nonintegrated government programs in the United States, there are state-to-state variation in telemedicine policies and geographic variation in outpatient care.29 In addition, our findings for telemedicine utilization and modality are aligned with previous studies noting substantial increases in overall telemedicine utilization at the onset of the COVID-19 pandemic.26 For example, telephone was the main modality of patient choice in a study comparing telehealth services at the VA Medical Center, Greater Los Angeles, across 3 clinicals 12 months before and 12 months after the onset of the COVID-19 pandemic. Although there were increases in video telemedicine, phone encounters remained the primary modality as patients described a heavy reliance on telephone as the main modality during the early months of the pandemic. Similar to the VA health care system, a group at Kaiser Permanente Northern California found the majority of telemedicine visits in primary care clinics scheduled during the first 7 months of the pandemic were telephone encounters (60.6%) compared with 39.4% of encounters conducted by televideo.30 Both studies noted that many patients, particularly those older than 65 years, preferred to use telephone as a remote communication platform. Important barriers to televideo visits included the multiple steps required to initiate a video conference, limited internet connectivity, and limited mobile portal access.26,30,31

Previous studies have examined general and specific chronic disease telehealth utilization at the VA. For example, in a study of telehealth utilization among veterans aged 65 years or younger with type 2 diabetes, investigators found no association between the shift from in-person to virtual visits during the COVID-19 pandemic and observed no association with hemoglobin A1c level or short-term type 2 diabetes-related outcomes.32 In another study, researchers compared the utilization of virtual health care before and during the COVID-19 pandemic for patients with inflammatory bowel disease (IBD) and found that the e-visits and e-messaging for care delivery increased during the COVID-19 pandemic and that expanded telemedicine options for patients with IBD eliminated previously identified racial and age disparities in virtual medical care.33

Our study in the VHA system contrasts with other recent reports in other health systems. In a study using survey data from the North American Research Committee on Multiple Sclerosis Registry, researchers used a questionnaire to evaluate access to and use of telehealth care including videoconferencing and usability of videoconferencing among PwMS.34 Overall, 2,889 (53.5%) reported access to MS care via telehealth and 2110 (39.1%) reported receipt of MS care via telehealth including 1,523 (28%) via videoconference. Study findings revealed older age, lower socioeconomic status, and disease-related impairments are associated with less access to and use of telehealth services in PwMS.34 A cohort from a large academic health system in Pennsylvania was recently assessed for inequities in telemedicine use for both primary and specialty care during the COVID-19 pandemic, with study findings showing only 54% completed a telehealth visit of any kind.35 Moreover, in a cross-sectional study using data from a large, integrated health system in Boston, Massachusetts, non-Hispanic Black individuals, Hispanics, and patients in lower income categories with less broadband availability were overall less likely to use telemedicine services during the pandemic.36

Strengths of this study include its large size and national scope. All eligible patients within the VHA were included over 3 different annual time points. Because of this, we had the ability to assess major demographic groups and geography. In addition to being the largest integrated health care system in the United States, the VHA is one of the earliest adopters of telemedicine.37 Reimbursement for telemedicine is similar to face-to-face visits and integrated into VHA policies. In addition, the ability to cross state lines with video telehealth is permitted in the federal health care system as opposed to most state-based health care systems.

There are some potential limitations of this study. First, military veterans are a unique segment of the population and have demographic diversity but may not be fully representative of PwMS in the United States. Second, although we examined telemedicine utilization, we did not examine the quality of care and individual-level access to telemedicine services in the VHA. Third, because VHA provides comprehensive health care to enrolled veterans, PwMS in our study population may have better access to care than the general population. Notably, our sample of PwMS had lower overall SDH than controls residing in higher poverty regions with less access to internet. Therefore, these results may not be generalizable to populations in less integrated health care settings.

Findings from this study can be applied to other health care systems by promoting conversations and implementing policies to optimize telemedicine services between patients and providers in health care systems; further investigation of the financial reimbursement issues by health insurance companies post-COVID-19 pandemic that can help cover the cost of effective telemedicine strategies that will benefit PwMS, their families, and providers; and further studies on how telemedicine can best be accessed (e.g., improvement of high speed internet access in rural regions of the US) and technically supported (e.g., real time information technology support for patients and providers) in the clinical setting to ensure it is being delivered across the life span of a patient with a chronic disease.

We observed that PwMS were significantly more likely to use telemedicine than their matched controls and that telemedicine utilization varied by individual race/ethnicity over time, by care type, and by geographic region. The geographic variation in telemedicine utilization we observed may be related to the availability of MS specialty care providers in those states with high telemedicine utilization and relatively low availability of MS care providers in those states with low telemedicine utilization.

The VHA has a robust telemedicine system of care that has grown to supplement in-person care more so than other US health care systems. The VHA is far ahead of private health insurance system in telemedicine delivery of care to PwMS. More details regarding how telemedicine is being delivered in the type of service and geographic location of patients should be assessed in other integrated health care systems in the United States. Future work is also needed to assess the reasons for variation in telemedicine utilization from PwMS, controls, and health care providers.

TAKE-HOME POINTS

  • → This study evaluated longitudinal patterns of telemedicine utilization among patients with multiple sclerosis (MS) and their matched controls.

  • → Patients with MS were significantly more likely to use telemedicine than their matched controls.

  • → There were increases in telemedicine utilization for mental health care for both MS cases and controls between 2010 and 2020.

  • → Non-Hispanic Blacks were significantly more likely to use telemedicine than non-Hispanic Whites in the VA health care system.

Appendix. Authors

Appendix.

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Study Funding

This project is funded by a grant from the National Multiple Sclerosis Society (HC-1610-25978) with support from the US Department of Veterans Affairs Multiple Sclerosis Center of Excellence.

Disclosure

L.M. Nelson receives grants from the NIH, National MS Society, and Centers for Disease Control. Dr. Nelson receives compensation for serving as a consultant to Acumen, Inc. M.T. Wallin receives grants from the National MS Society and the Department of Veterans Affairs. 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.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Owing to the U.S. Department of Veterans Affairs (VAs) regulations and our ethics agreement, the analytic data sets used for this study are not permitted to leave the VA firewall without a Data Use Agreement. This limitation is consistent with other studies based on VA data. However, VA data are made freely available to researchers with an approved VA study protocol.

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