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2023 HSR&D/QUERI National Conference Abstract

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1154 — Factors Associated with Veteran Self-Reported Use of Digital Health-Related Devices

Lead/Presenter: Stephanie Robinson,  COIN - Bedford/Boston
All Authors: Robinson SA (Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System), Zocchi M (Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System) Shimada SL (Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System) Etingen B (Center of Innovation for Complex Chronic Healthcare, VA Hines Healthcare System) McMahon N (Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System) Cutrona S (Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System) Smith B (Center of Innovation for Complex Chronic Healthcare, VA Hines Healthcare System) Hogan TP (Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System)

Objectives:
Digital health-related devices, technologies designed to gather, track, monitor, and sometimes share data about health-related behaviors or symptoms, can support the prevention or management of chronic conditions. However, bolstering their adoption remains a challenge. This analysis examined Veteran perceptions of digital health-related device use and identified factors associated with their use.

Methods:
We analyzed data collected in 2021 from a national sample of Veterans as part of a longitudinal quality improvement initiative. Surveys asked about perceptions and use of specific digital health-related devices. Devices were categorized into: 1) lifestyle monitoring (i.e., Fitbit/smartwatch/pedometer), and 2) self-management (e.g., digital blood pressure monitor) devices. Combined with clinical data, we modeled two multiple logistic regressions to assess factors associated with: 1) lifestyle monitoring device use, and 2) self-management device use. We present adjusted odds ratios (AORs) and 95% confidence interval (CI) estimates for the predictors.

Results:
Of the 1,358 Veterans invited to complete the survey, 858 responded (63% response rate). The current analysis includes n = 846 Veterans with complete data on model covariates. Most respondents (87%) were current or past users of > = 1 device. Respondents with a chronic disease were more likely to use a self-management device (Ps = .00), but not a lifestyle monitoring device. Most (67%) reported their VA care team recommended device use and 65% were provided a device by VA. To make behavioral changes (50%) and track health over time (49%) were the most frequently reported uses of the device-collected health data. Those > = 65 years were 42% less likely to use a lifestyle monitoring device (AOR = 0.58, 95% CI [0.41, 0.83]), but 65% more likely to use a self-management device (AOR = 1.65, 95% CI [1.08, 2.52]). Ownership or easy access to a smartphone was associated with 160% and 97% greater likelihood of using a lifestyle monitoring (AOR = 2.60, 95% CI [1.43, 4.73]) and self-management device (AOR = 1.97, 95% CI [1.13, 3.44]), respectively. Worse health, as measured via the Hierarchical Condition Category score, was associated with a 63% greater likelihood of using a self-management device (AOR = 1.63, 95% CI [1.30, 2.05]); health was not associated with use of lifestyle monitoring devices.

Implications:
Age, technology access, and health influence digital health-related device use, and these relationships vary based on device function. The majority of device users reported VA involvement, such as the provision of devices and care team encouragement to use the devices. Respondents reported using the devices to take an active role in health management and behavior change. These findings suggest that providing Veterans with digital health-related devices and the technology needed to use them (e.g., smartphones), and supporting communication between Veterans and their care teams about device use, may be important factors to facilitate adoption.

Impacts:
Existing work has mostly focused on intent to use or general device adoption. This analysis extends this previous work by examining actual use, and variation in use, based on device functionality. This work can inform the design of future initiatives to support Veteran adoption of digital health-related devices.