Objectives To describe the shift from in-person to virtual care within Veterans Affairs (VA) during the early phase of the COVID-19 pandemic, and to identify at-risk patient populations who require greater resources to overcome access barriers to virtual care. Materials and Methods Outpatient encounters (N = 42,916,349) were categorized by care type (e.g. primary, mental health, etc.) and delivery method (e.g., in-person, video). For 5,400,878 Veterans, we used Generalized Linear models to identify patient sociodemographic and clinical characteristics associated with: 1) use of virtual (phone or video) care versus no virtual care and 2) use of video care versus no video care; between 3/11/2020 and 6/6/2020. Results By June, 58% of VA care was provided virtually compared to only 14% prior. Patients with lower income, higher disability, and more chronic conditions were more likely to receive virtual care during the pandemic. Yet, Veterans aged 45-64 and 65+ were less likely to use video care compared to those aged 18-44 (aRR 0.80 [95%CI 0.79, 0.82] and 0.50 [0.48, 0.52], respectively). Rural and homeless Veterans were 12% and 11% less likely to use video care compared to urban (0.88 [0.86, 0.90]) and non-homeless Veterans (0.89 [0.86, 0.92]). Discussion Veterans with high clinical or social need had higher likelihood of virtual service use early in the COVID-19 pandemic, however, older, homeless, and rural Veterans were less likely to have video visits, raising concerns for access barriers. Conclusions and Relevance While virtual care may expand access, access barriers must be addressed to avoid exacerbating disparities.

Background Video telehealth technology has the potential to enhance access for patients with clinical, social, and geographic barriers to care. We evaluated the implementation of a US Department of Veterans Affairs (VA) initiative to distribute tablets to high-need Veterans with access barriers. Methods In this mixed methods implementation study, we examined tablet adoption (ie, facility-level tablet distribution rates and patient-level tablet utilization rates) and reach (ie, sociodemographic and clinical characteristics of tablet recipients) between 5/1/16 and 9/30/17. Concurrently, we surveyed 68 facility telehealth coordinators to determine the most common implementation barriers and facilitators, and then conducted interviews with telehealth coordinators and regional leadership to identify strategies that facilitated tablet distribution and use. Results 86 VA facilities spanning all 18 geographic regions, distributed tablets to 6 745 patients. Recipients had an average age of 56 years, 53% lived in rural areas, 75% had a diagnosed mental illness, and they had a mean (SD) of 5 (3) chronic conditions. Approximately 4 in 5 tablet recipients used the tablet during the evaluation period. In multivariate logistic regression, tablet recipients were more likely to use their tablets if they were older and had fewer chronic conditions. Implementation barriers included insufficient training, staffing shortages, and provider disinterest (described as barriers by 59%, 55%, and 33% of respondents, respectively). Site readiness assessments, local champions, licensure modifications, and use of mandates and incentives were identified as strategies that may influence widespread implementation of home-based video telehealth. Conclusion VA’s initiative to distribute video telehealth tablets to high-need patients appears to have successfully reached individuals with social and clinical access barriers. Implementation strategies that address staffing constraints and provider engagement may enhance the impact of such efforts.

Background Video-based health care can help address access gaps for patients and is rapidly being offered by health care organizations. However, patients who lack access to technology may be left behind in these initiatives. In 2016, the US Department of Veterans Affairs (VA) began distributing video-enabled tablets to provide video visits to veterans with health care access barriers. Objective This study aimed to evaluate veterans’ experiences with VA-issued tablets and identify patient characteristics associated with preferences for video visits vs in-person care. Methods A baseline survey was sent to the tablet recipients, and a follow-up survey was sent to the respondents 3 to 6 months later. Multivariate logistic regression was used to identify patient characteristics associated with preferences for care, and we examined qualitative themes around care preferences using standard content analysis methods for coding the data collected in the open-ended questions. Results Patient-reported access barriers centered around transportation and health-related challenges, outside commitments, and feeling uncomfortable or uneasy at the VA. Satisfaction with the tablet program was high, and in the follow-up survey, approximately two-thirds of tablet recipients preferred care via a tablet (194/604, 32.1%) or expressed that video-based and in-person care were “about the same” (216/604, 35.7%), whereas one-third (192/604, 31.7%) indicated a preference for in-person care. Patients were significantly more likely to report a preference for video visits (vs a preference for in-person visits or rating them “about the same”) if they felt uncomfortable in a VA setting, reported a collaborative communication style with their doctor, had a substance use disorder diagnosis, or lived in a place with better broadband coverage. Patients were less likely to report a preference for video visits if they had more chronic conditions. Qualitative analyses identified four themes related to preferences for video-based care: perceived improvements in access to care, perceived differential quality of care, feasibility of obtaining necessary care, and technology-related challenges. Conclusions Many recipients of VA-issued tablets report that video care is equivalent to or preferred to in-person care. Results may inform efforts to identify good candidates for virtual care and interventions to support individuals who experience technical challenges.

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This paper describes methods of determining costs for economic evaluations of healthcare and considers how cost determination is being affected by recent developments in healthcare. The literature was reviewed to identify the strengths and weaknesses of the four principal methods of cost determination: micro-costing, activity-based costing, charge-based costing, and gross costing. A scoping review was conducted to identify key trends in healthcare delivery and to identify costing issues associated with these changes. Existing guidelines provide information on how to implement various costing methods. Bottom-up costing is needed when accuracy is paramount, but top-down approaches are often the only feasible approach. We describe six healthcare trends that have important implications for costing methodology: (1) reform in payment mechanisms; (2) care delivery in less restrictive settings; (3) the growth of telehealth interventions; (4) the proliferation of new technology; (5) patient privacy concerns; and (6) growing efforts to implement guidelines. Some costs are difficult to measure and have been overlooked. These include physician services for inpatients, facility costs for outpatient services, the cost of developing treatment innovations, patient and caregiver costs, and the indirect costs of organizational interventions. Standardized methods are needed to determine social welfare and productivity costs. In the future, cost determination will be facilitated by technological advances but hindered by the shift to capitated payment, to the provision of care in less restrictive settings, and by heightened concern for medical record privacy.

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With increasing pressure on retirement-aged individuals to provide informal care while remaining in the workforce , it is important to understand the impact of informal care demands on individuals' retirement decisions. This paper explores whether different intensities of informal caregiving can lead to retirement for women in the United States. Using the National Longitudinal Survey of Mature Women, we control for time-invariant heterogeneity and for time-varying sources of bias with a two-stage least squares model with fixed effects. We find that there is no significant effect on retirement for all informal caregivers, but there are important incremental effects of caregiving intensity. Women who provide at least 20 hours of informal care per week are 3 percentage points more likely to retire relative to other women. We also find that when unobserved heterogeneity is controlled for with fixed effects, we cannot reject exogeneity. These findings suggest that policies encouraging both informal care and later retirement may not be feasible without allowances for flexible scheduling or other supports for working caregivers.

Health care systems frequently have to decide whether to implement interventions designed to reduce gaps in the quality of care. A lack of information on the cost of these interventions is often cited as a barrier to implementation. In this article, we describe methods for estimating the cost of implementing a complex intervention. We review methods related to the direct measurement of labor, supplies and space, information technology, and research costs. We also discuss several issues that affect cost estimates in implementation studies, including factor prices, fidelity, efficiency and scale of production, distribution, and sunk costs. We examine case studies for stroke and depression, where evidence-based treatments exist and yet gaps in the quality of care remain. Understanding the costs for implementing strategies to reduce these gaps and measuring them consistently will better inform decision makers about an intervention’s likely effect on their budget and the expected costs to implement new interventions.