Abstract
In 2020, the U.S. Department of Veterans Affairs (VA) expanded an initiative to distribute video-enabled tablets to Veterans with limited virtual care access. We examined patient characteristics associated with adoption and sustained use of video-based primary care among Veterans. We conducted a retrospective cohort study of Veterans who received VA-issued tablets between 3/11/2020-9/10/2020. We used generalized linear models to evaluate the sociodemographic and clinical factors associated with video-based primary care adoption (i.e., likelihood of having a primary care video visit) and sustained use (i.e., rate of video care) in the six months after a Veteran received a VA-issued tablet. Of the 36,077 Veterans who received a tablet, 69% had at least one video-based visit within six months, and 24% had a video-based visit in primary care. Veterans with a history of housing instability or a mental health condition, and those meeting VA enrollment criteria for low-income were significantly less likely to adopt video-based primary care. However, among Veterans who had a video visit in primary care (e.g., those with at least one video visit), older Veterans, and Veterans with a mental health condition had more sustained use (higher rate) than younger Veterans or those without a mental health condition. We found no differences in adoption of video-based primary care by rurality, age, race, ethnicity, or low/moderate disability and high disability priority groups compared to Veterans with no special enrollment category. VA’s tablet initiative has supported many Veterans with complex needs in accessing primary care by video. While Veterans with certain social and clinical challenges were less likely to have a video visit, those who adopted video telehealth generally had similar or higher rates of sustained use. These patterns suggest opportunities for tailored interventions that focus on needs specific to initial uptake vs. sustained use of video care.
Keywords: Veterans, Health care access, Video-based care, Tablets, Telemedicine
Introduction
Providing tablets to populations with digital health care access barriers may contribute to bridging the “digital divide” [1]. In 2016, the U.S. Department of Veterans Affairs (VA) implemented a program to distribute video-enabled tablets to Veterans with access barriers [2]. This initiative was rapidly expanded in 2020 with the onset of the Coronavirus (COVID-19) pandemic [2, 3]. Simultaneously, VA broadened available video-based services to include a wide range of clinical services so as to reduce risk of COVID-19 transmission [4-6].
VA’s distribution of tablets has been shown to have a positive effect on access, continuity of care, and outcomes for at-risk patients [6, 7]. However, while older, unhoused, and low-income Veterans receive tablets at similar proportions to those without these characteristics, Veterans with these characteristics have lower use of video care [8].
Past studies have focused on various aspects of the tablet program and overall care at VA [2, 5-7]. Given the essential role of primary care in maintaining health and rapid integration of video primary care across VA during the pandemic, we examined variation in adoption and sustained use of video-based primary care by sociodemographic and clinical characteristics. By assessing adoption and sustained use among populations vulnerable to the impacts of the digital divide but now empowered with a video and internet capable device, we offer insight into the equity of video care access within VA and inform interventions for those who need greater support. We hypothesize that even after the provision of an internet capable device, certain subgroups of Veterans may still experience barriers to video-based care at VA.
Materials and Methods
VA’s Tablet Initiative
Since 2016, VA has offered video-enabled tablets with data plans to Veterans with access barriers to VA health care who lack a suitable device and/or broadband or cellular internet service to engage in video-based care. Characteristics of Veterans who received tablets both prior to and during the COVID-19 pandemic have been previously described in detail [8]. Eligible Veterans who experience barriers such as transportation difficulties, social isolation, complex health issues, or caregiving responsibilities can be referred for tablets by a VA provider who places a consult in VA’s computerized patient record system. A social worker then reviews the consult, evaluates a Veteran’s need for a tablet and/or broadband access, and places an order to have a device shipped directly to the Veteran [2, 3]. Veterans may also receive support in applying for Lifeline or EveryoneOn, two programs that offer eligible Veterans low-cost internet services [9, 10].
Data Extraction and Study Population
We identified and extracted patient (sociodemographic and clinical characteristics) and encounter-level data for Veterans shipped a VA-issued tablet between 3/11/2020-9/10/2020, after the World Health Organization’s designation of COVID-19 as a pandemic, using VA’s Corporate Data Warehouse, a repository for VA electronic health records [11, 12]. Of the 36,933 recipients meeting extraction criteria, we subsequently excluded Veterans living on island territories (N = 18), and missing zip code (needed for urban/rural classification; N = 519), VA priority enrollment group (N = 10), and VA Medical Center (VAMC) station designation (N = 212). We excluded those without VA outpatient care in the past year (N = 67) as at least one outpatient consult is required to determine tablet eligibility. Finally, we excluded Veterans who’s designated VAMC had fewer than ten Veterans (N persons = 30, N VAMC = 5) per VA data privacy recommendations. The final analytic cohort comprised 36,077 Veterans.
Outcome: Use of Video-Based Primary Care
Our primary outcomes were adoption and sustained use of outpatient video-based primary care within six months of tablet shipment. Six months was selected to capture acute health care needs as tablets are distributed based on a current need for VA health care. We identified video-based primary care outpatient encounters using VA’s Managerial Cost Accounting Stop Codes [5]. To reduce the likelihood of non-tablet-based video encounters, we excluded encounters that occurred within seven days after tablet shipment, as VA assists recipients with set-up within seven days after shipment [3].
Patient Sociodemographic and Clinical Characteristics
Race and ethnicity were recorded based on most frequently reported identification [13]. Missing data on race, ethnicity and marital status were treated as distinct categories. Veterans’ home addresses were classified into urban, rural, and highly rural designations based on zip code of their home address [14]. We used outpatient stop codes for housing instability service use and VA diagnosis codes to define history of housing instability [15]. We identified the primary VAMC (N = 134) for each Veteran where the patient was assigned a primary, mental health, specialty or rehabilitation, or other care team (in ranked order). We calculate the number of comorbid conditions using 28 chronic conditions and diagnoses (Appendix A). History of a mental health condition (e.g., depression, PTSD) were defined as previously described (Appendix B) [5, 16-19]. VA’s priority-based enrollment system enrolls Veterans into one of eight mutually exclusive groups based on service-connected disability rating, income, recent military service, and other factors. We generated four categories of priority status: low income, low/moderate disability, high disability, or no special enrollment (Appendix C) [13].
We assessed prior use of VA health care in the 365 days prior to and excluding the date of tablet shipment for all patients to account for any association between past and future use (Appendix D). To contextualize the usage of video-based care among tablet recipients beyond primary care, we also calculated the use of video-based mental health care and other care (rehabilitation, diagnostic/ancillary, and emergency care) as previously defined within the first 6 months of tablet receipt.
Statistical Analyses
We evaluated differences in Veteran sociodemographic and clinical characteristics by use of video-based primary care within six months of tablet receipt. Additionally, we evaluated the time between tablet shipment and a recipients’ first video visit and the total number of video encounters within six months. In a two-part modeling process, we assessed the likelihood of any video-based primary care among all tablet recipients by Veteran characteristics, using Poisson generalized linear models and report adjusted risk ratios (RR). Then, among Veterans with at least one video-based primary care visit, we calculated the adjusted incidence rate of video visits over six-months by Veteran characteristics, using a zero-truncated negative binomial model with a log link. In both models, we adjusted for patient demographics, clinical characteristics, VAMC, and previous use of VA health care. We conducted a sensitivity analysis using a year of follow-up (Appendix D) to allow sufficient time for slow adopters of video primary care. We report 95% confidence intervals and used robust standard errors.
We completed analyses using Stata 17 (StataCorp, LLC). This evaluation was completed as part of a VA Quality Enhancement Research Initiative and was designated as non-research quality improvement by VA’s Office of Rural Health.
Results
Our study population had a mean age of 64.4 years and had an average of 7.6 chronic conditions, 67% were white, and 24% had a history of housing instability (Table 1), representing a slightly older population with higher clinical needs than the average Veteran enrolled in VA health care [13]. While 69% of the 36,077 tablet recipients in our study population had at least one video visit within 6 months of tablet receipt, only 24% of recipients had a video visit in primary care (Fig. 1). Roughly 43% of primary care encounters for Veterans included in this study occurred in person. This can be compared to roughly 65% of primary care encounters that occurred in person amongst those who received tablets in the year prior to the pandemic. Among those who had a video-based primary care visit, most (70%) also had video visits for mental health care and other services, whereas fewer than 30% had video visits in primary care alone. Notably, a quarter of all Veterans who utilized video-based primary care had their first video visit within one month (four weeks) of tablet shipment (Fig. 2), averaging 1.7 visits in the first six months of tablet receipt. Use of video care ranged from 1 to 22 visits among users (Fig. 3). Yet, 95% had five or fewer encounters (i.e., less than one a month), and 67% had only one encounter.
Table 1.
Demographics and clinical characteristics of tablet recipients and use of video-based primary care within six months of tablet receipt
| Total | No Use of Video-break/>Based Primary Care | Any Use ofbreak/>Video-Basedbreak/>Primary Care | |
|---|---|---|---|
| Total | N (%) | N (%) | N (%) |
| 36,077 | 27,382 | 8,695 | |
| Age Group | |||
| 18–44 | 3,776 (10.5) | 3,083 (11.3) | 693 (8.0) |
| 45–64 | 12,816 (35.5) | 10,164 (37.1) | 2,652 (30.5) |
| 65+ | 19,485 (54.0) | 14,135 (51.6) | 5,350 (61.5) |
| Race | |||
| White | 24,183 (67.0) | 18,223 (66.6) | 5,960 (68.5) |
| Black/African American | 9,214 (25.5) | 7,098 (25.9) | 2,116 (24.3) |
| Asian | 235 (0.7) | 180 (0.7) | 55 (0.6) |
| American Indian/Alaska Native | 433 (1.2) | 355 (1.3) | 78 (0.9) |
| Native Hawaiian/Pacific Islander | 365 (1.0) | 279 (1.0) | 86 (1.0) |
| Unknown | 1,647 (4.6) | 1,247 (4.6) | 400 (4.6) |
| Ethnicity | |||
| Hispanic/Latino | 1,631 (4.5) | 1,198 (4.4) | 433 (5.0) |
| Not Hispanic/Latino | 33,374 (92.5) | 25,364 (92.6) | 8,010 (92.1) |
| Unknown | 1,072 (3.0) | 820 (3.0) | 252 (2.9) |
| Gender | |||
| Male | 32,048 (88.8) | 24,401 (89.1) | 7,647 (87.9) |
| Female | 4,029 (11.2) | 2,981 (10.9) | 1,048 (12.1) |
| Marital Status | |||
| Single (or divorced/widowed) | 21,056 (58.4) | 16,472 (60.2) | 4,584 (52.7) |
| Married | 14,702 (40.8) | 10,664 (38.9) | 4,038 (46.4) |
| Unknown | 319 (0.9) | 246 (0.9) | 73 (0.8) |
| Rurality | |||
| Urban | 24,488 (67.9) | 18,557 (67.8) | 5,931 (68.2) |
| Rural | 10,447 (29.0) | 7,890 (28.8) | 2,557 (29.4) |
| Highly Rural | 1,142 (3.2) | 935 (3.4) | 207 (2.4) |
| History of Housing Instability | |||
| No | 27,450 (76.1) | 20,273 (74.0) | 7,177 (82.5) |
| Yes | 8,627 (23.9) | 7,109 (26.0) | 1,518 (17.5) |
| Multimorbidity | |||
| 0–3 Conditions | 4,822 (13.4) | 3,947 (14.4) | 875 (10.1) |
| 4–6 Conditions | 10,827 (30.0) | 8,447 (30.8) | 2,380 (27.4) |
| 7–9 Conditions | 10,419 (28.9) | 7,804 (28.5) | 2,615 (30.1) |
| 10 + Conditions | 10,009 (27.7) | 7,184 (26.2) | 2,825 (32.5) |
| Mental Health Condition(s) | |||
| No | 9,154 (25.4) | 6,407 (23.4) | 2,747 (31.6) |
| Yes | 26,923 (74.6) | 20,975 (76.6) | 5,948 (68.4) |
| VA Priority Group | |||
| No Special Enrollment | 2,583 (7.2) | 1,896 (6.9) | 687 (7.9) |
| Low Income | 9,305 (25.8) | 7,315 (26.7) | 1,990 (22.9) |
| Low/Moderate Disability | 6,069 (16.8) | 4,651 (17.0) | 1,418 (16.3) |
| High Disability | 18,120 (50.2) | 13,520 (49.4) | 4,600 (52.9) |
Fig. 1.
Use of video-based care across VA clinical specialties in the first six months of tablet receipt among 36,077 Veterans
Fig. 2.
Time in weeks between tablet shipment and first primary care video visit for tablet recipients. 1 represents 8,695 Veterans who received tablets between 3/11/2020–9/10/2020 and had at least one video vis
Fig. 3.
Total primary care video visits in first six months of tablet receipt among entire cohort and among Veterans with at least one video visit
Use of any video-based primary care amongst tablet recipients differed substantially between sociodemographic groups. Video-based primary care users were older, with an average age of 67.3 years (vs. 63.5 years) and had more chronic conditions (8.1 vs. 7.4 conditions) compared to non-users. Despite those with a history of housing instability comprising 24% of the cohort, they comprised only 18% of video primary care users. Conversely, only 68% of primary care utilizers identified as having a mental health condition compared to 75% in the overall cohort. The proportion of primary care utilizers by race, ethnicity and rurality and priority groups mirrored the overall cohort demographics closely.
Adoption of Video Care: Likelihood of any Video Care Use
In adjusted models, housing instability, low-income, and history of mental health condition were associated with decreased likelihoods of adopting video-based primary care (Table 2). Veterans with a history of housing instability and Veterans assigned to low-income VA Priority Groups had 10% (CI: 0.84,0.96) and 9% (CI: 0.83,0.99) reduced likelihoods of using video-based primary care compared to stably housed Veterans and Veterans with no special enrollment, respectively.
Table 2.
Adjusted incidence risk ratios and adjusted rate ratios with 95% confidence intervals for VA video-based primary care use within 6 months of tablet receipt
| Risk Ratiobreak/>Primary Carebreak/>N = 36,077 | Risk Ratiobreak/>Primary Carebreak/>N = 8,695 | |||
|---|---|---|---|---|
| Age Group | ||||
| 18–44 | 1.00 | -- | 1.00 | -- |
| 45–64 | 0.97 | (0.89,1.06) | 1.05 | (1.00,1.10) |
| 65+ | 0.95 | (0.87,1.04) | 1.14 | (1.08,1.20) |
| Race | ||||
| White | 1.00 | -- | 1.00 | -- |
| Black/African American | 0.99 | (0.94,1.05) | 0.95 | (0.92,0.99) |
| Asian | 0.98 | (0.75,1.28) | 1.05 | (0.91,1.22) |
| American Indian/Alaska | 0.89 | (0.71,1.11) | 1.07 | (0.92,1.24) |
| Native | ||||
| Native Hawaiian/Pacific Islander | 0.92 | (0.75,1.15) | 0.97 | (0.86,1.10) |
| Unknown | 1.03 | (0.91,1.15) | 0.99 | (0.92,1.06) |
| Ethnicity | ||||
| Not Hispanic/Latino | 1.00 | -- | 1.00 | -- |
| Hispanic/Latino | 1.06 | (0.95,1.17) | 1.00 | (0.93,1.07) |
| Unknown | 0.91 | (0.79,1.04) | 1.08 | (0.98,1.19) |
| Gender | ||||
| Male | 1.00 | -- | 1.00 | -- |
| Female | 1.18 | (1.11,1.27) | 1.03 | (0.96,1.07) |
| Rurality | ||||
| Urban | 1.00 | -- | 1.00 | -- |
| Rural | 1.03 | (0.98,1.09) | 0.98 | (0.95,1.02) |
| Highly Rural | 0.91 | (0.79,1.05) | 1.06 | (0.95,1.18) |
| History of Housing Instability | ||||
| No | 1.00 | -- | 1.00 | -- |
| Yes | 0.90 | (0.84,0.96) | 1.00 | (0.95,1.05) |
| Multimorbidity | ||||
| 0–3 Conditions | 1.00 | -- | 1.00 | -- |
| 4–6 Conditions | 1.09 | (1.00,1.18) | 1.03 | (0.98,1.08) |
| 7–9 Conditions | 1.14 | (1.05,1.25) | 1.02 | (0.96,1.07) |
| 10 + Conditions | 1.20 | (1.09,1.32) | 1.03 | (0.97,1.10) |
| Mental Health Condition(s) | ||||
| No | 1.00 | -- | 1.00 | -- |
| Yes | 0.92 | (0.87,0.99) | 1.06 | (1.01,1.11) |
| VA Priority Group | ||||
| No Special Enrollment | 1.00 | -- | 1.00 | -- |
| Low Income | 0.91 | (0.83,0.99) | 1.01 | (0.95,1.08) |
| Low/Moderate Disability | 0.97 | (0.87,1.07) | 0.99 | (0.93,1.06) |
| High Disability | 1.01 | (0.93,1.10) | 1.03 | (0.97,1.09) |
Female Veterans had an 18% (CI: 1.11,1.27) higher likelihood of video-based primary care use compared to male Veterans. A higher number of comorbidities/chronic conditions was associated with a greater likelihood of video-based primary care use with a 9% (CI: 1.00,1.18) increased likelihood among those with 4–6 conditions and a 20% (CI: 1.09,1.32) increased likelihood among those with 10 + chronic conditions compared to those with 0–3 chronic conditions. There were no differences in the likelihood of video care by rurality, age, race, ethnicity, or among Veterans belonging to low/moderate disability and high disability priority groups compared to Veterans with no special enrollment group.
Sustained Video Care: Rate of Video Care Use
Sustained use of video-based primary care varied across several demographics. Despite lower likelihood of video care adoption, those with any mental health condition had a 6% (CI: 1.01,1.11) higher rate of use compared to Veterans with no mental health conditions. While Veterans in low-income groups or those with a history of housing instability had lower likelihoods of having any video care, there were no differences in their rate of video care use among video care users compared to Veterans enrolled without special considerations and Veterans without a history of housing instability respectively.
While Veterans who were female, low-income, or with higher numbers of comorbidities had higher likelihoods of having any video care, there were no differences in their rates of video care for their respective comparators. Black/African American Veterans were the only race group to have a significantly decreased rate of use: 5% (CI: 0.92, 0.99) lower when compared to video use rates among White Veterans.
There were no differences in the likelihood of video care use by age, yet, older Veterans had higher rates of video care once engaged compared to younger Veterans. Specifically, Veterans older than 45 and those older than 65 years of age had a 5% (CI: 1.00, 1.10) and 14% (CI: 1.08, 1.20) higher rate of video-based primary care use compared to Veterans younger than 45 years, respectively.
Similar to likelihood of adoption, the rates of sustained use were not significantly different across all other racial groups, ethnicity, rurality, history of housing instability, and VA priority group.
Sensitivity Analysis
Models examining adjusted likelihoods of any video-based primary care use within one year of tablet receipt largely mirrored the six-month model. Veterans who used video-based primary care averaged 1.7 video visits within six months and 2.4 video visits within the first year after tablet receipt (i.e., average of 1.2 visits per six months), indicating a decrease in utilization over time (Fig. 3). Sensitivity analyses for adjusted rate ratios for video-based primary care had minimal differences between the 1-year and 6-month models. In a final sensitivity analysis, where we calculated rate ratios over a year amongst those who used video-based primary care within the first six month of tablet receipt, also had no notable deviations from results seen in our primary model.
Discussion
In this evaluation of VA’s tablet distribution program, we identified several notable patterns when examining use of video-based primary care by sociodemographic characteristics among tablet recipients. The observed differential patterns for adoption vs. sustained use of video-based care can inform policies and targeted interventions to promote meaningful engagement with virtual care.
Despite the pervasive digital divide among older adults, we did not observe significant differences in likelihood of video-based primary care use among tablet recipients. This differs from previous analyses that examined utilization of multiple clinical services, suggesting differential patterns across primary vs. mental health care [8]. Notably, we found that older Veterans had higher rates of primary care video use compared with younger Veterans, contrasting with a previous national evaluation of VA video-based care among tablet recipients and non-recipients [20]. Barriers faced by older adults in accessing telehealth have been well-documented, including a recent non-VA study that found tailored education on device usage and the utility of telehealth was of strategic importance in encouraging adoption of video-based care, especially among older adults [21]. VA’s success in achieving equivalent adoption of video-based primary care across all age groups suggests that the approach used by VA, which included device distribution coupled with education and technical support provided by the Connected Devices Program, is a promising strategy to improve telehealth access [22].
Similarly, while rurality is strongly associated with lower adoption and sustained use of video telehealth, including in primary care, [23, 24], we found no significant differences in likelihood or rate of video-based primary care use across rurality categories. While access to broadband internet in rural areas has increased overtime, many rural communities still face barriers to internet access. Our finding suggests that distribution of tablets in conjunction with locally-tailored data plans and access to low-cost internet services may be an effective in increasing access [23, 24]. Future evaluations should examine the relative merits (e.g., access benefits, costs) of the individual components of VA’s initiative (e.g., device distribution, referral to the federal Lifeline, Affordable Connectivity Program,) to determine the potential value of expanding these programs to a broader population [9, 10].
Although our findings suggest that tablet distribution might narrow digital divides for older adults and rural Veterans, we observed persistent disparities in adoption of video-based primary care for other groups. For example, Veterans with a history of housing instability were 10% less likely to utilize video-based primary care compared to Veterans without a history of housing instability, which may reflect barriers such as lack of private space and reliable charging stations. However, among those with at least one video-based primary care visit, we did not see differential rates of use [25]. This suggests that disparities relate more to adoption than sustained use. In addition, our findings differ from analyses of video-based mental health care, that have previously demonstrated that Veterans with a history of housing instability were more likely to have a video-based mental health care visit compared to stably housed Veterans [20]. Future research should therefore explore barriers specific to adoption to ensure that Veterans with housing instability derive optimal benefits from tablets and other interventions that support virtual care access [15].
We also found that 45% of tablet recipients had a video-based mental health visit, while only 11% had both a mental health and primary care video visit. Furthermore, having a mental health condition was associated with reduced likelihood of video-based primary care use. This pattern has been observed in other national analyses of VA video-based care and may be reflective of primary care’s less rapid video telehealth implementation compared to mental health care [5]. Mental health providers may be more likely to request a tablet and may have been better poised to provide and support appointments via video than primary care providers[26]. However, it may also reflect barriers to general primary care access for individuals with mental health conditions [27-29]. Veterans who were in a VA priority group due to low-income also had decreased likelihood of video-based primary care use, a finding that might reflect unique barriers to accessing video primary care beyond those resolved by tablet possession, such as barriers to stable electricity access, privacy for visits, or less-established relationships with primary care providers [30, 31]. The similar rates of video care use among Veterans with mental health conditions and those with low-income suggests the barriers to adoption are surmountable and do not impact sustained video care in the same way.
Other findings suggest that Veterans who are more engaged in VA health care, (e.g., women and those with multiple chronic conditions) tend to have higher utilization rates of video-based primary care. These patterns may reflect patient preferences (in the case of women [32]) and/or increased virtual care needs due to risks posed by COVID-19, among multimorbid Veterans [33, 34]. It was concerning, however, that we found lower sustained use of video-based primary care among Black Veterans (although no differences among racial and ethnic groups when it came to adoption), yet, previous analyses of VA’s tablet initiative have not shown racial disparities [5, 8, 20]. This finding therefore warrants further exploration to determine whether there are factors related to identifying and scheduling patients for video-based visits that may be leading to racial disparities.
This study has limitations. The evaluation could not determine if video visits took place on VA-issued tablets. While Veterans only qualify for a VA-issued tablet if they do not have a video-enabled device with a suitable data plan, it is still feasible for a person to have a video visit on another device. The dataset also did not capture whether a video visit was completed as planned or converted into a phone visit, as sometimes happens if a patient or clinician has a poor connection or technical difficulties. Future research should investigate the prevalence of these issues and their impact on sustained use of video visits. Additionally, analyses do not account for Veteran preferences for in-person care or health issues that are ill-suited for video-based care, and analyses were unable to account for COVID-19-specific care, which might have influenced patterns of primary care utilization during the period of study. Evaluations focusing on these issues will inform targeted strategies that support clinically appropriate video visits for interested Veterans.
In conclusion, this study suggests that VA’s tablet program has successfully encouraged video primary care adoption among older and more rural Veterans. Although adoption of video-based primary care was lower for Veterans with mental health conditions or a history of housing instability, among those who had at least one video visit, rates of use were similar. Future studies should focus on potential contributors to disparities in video care adoption within primary care, including patient and clinician perspectives on the value and effectiveness of video-based primary care. Improved targeting of Veterans and/or efforts to facilitate early tablet use may improve adoption and sustained use of video-based primary care and will be essential to optimizing the cost-effectiveness of this initiative.
Supplementary Material
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s10916-024-02035-5.
Acknowledgements
The authors thank Camila Chaudhary, VA Office of Connected Care, VA Office of Rural Health, the Virtual Access QUERI team, and Stanford School of Medicine Department of Health Policy for their help in supporting this evaluation.
Funding
Funding was also provided by the U.S. Department of Veterans Affairs (VA) Office of Rural Health. Visit www.ruralhealth.va.gov to learn more. This work was also supported by a VA Quality Enhancement Research Initiative (QUERI) PEI 18–205. Dr. Ferguson was directly supported by a VA QUERI Initiative to Advance Diversity in Implementation Leadership (ADIL) Supplement to the QUERI PEI-18-205.
Footnotes
Conflict of interest The authors have no competing interests to declare that are relevant to the content of this article.
Disclaimer Views expressed are those of the authors and the contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.
Ethical Approval This evaluation was completed as part of a VA Quality Enhancement Research Initiative and was designated as non-research quality improvement by VA’s Office of Rural Health.
Data Sharing Statement
Due to US Department of Veterans Affairs (VA) regulations and our ethics agreements, the analytic data sets used for this study are not permitted to leave VA’s 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. For more information, please visit https://www.virec.research.va.gov or contact VA’s Information Resource Center at VIReC@va.gov.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Due to US Department of Veterans Affairs (VA) regulations and our ethics agreements, the analytic data sets used for this study are not permitted to leave VA’s 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. For more information, please visit https://www.virec.research.va.gov or contact VA’s Information Resource Center at VIReC@va.gov.