Abstract

Background: Beyond the distribution of video-enabled tablets to overcome access barriers to telemedicine, Veterans need training to improve their digital skills. We hypothesize that by offering an in-person digital literacy intervention among hospitalized Veterans, we can improve (1) digital skills and (2) use of MyHealtheVet, [MHV] and VA Video Connect [VVC] to improve post-hospitalization access and care. Significance: In the post-pandemic environment, telemedicine continues to expand. Patients, especially those who are most vulnerable and require the most care, need effective training opportunities to improve digital literacy as an important step to fully participate in virtual care. This digital training intervention is significant as it is designed to address this challenge among a high-cost, high-risk population (hospitalized Veterans) who require close follow-up care after discharge. Moreover, this feasibility study of a bedside digital literacy intervention will identify implementation strategies that could be expanded into clinical workflows across a variety of settings and populations to improve virtual access. Innovation & Impact: While the Veterans Health Administration (VA) provides telephone-based orientation services for VA-issued tablets in the outpatient setting, no program explores the opportunity to use hospitalization to provide hands-on digital education. If effective, this pilot study will contribute to our understanding of how to best engage Veterans in and provide digital literacy training to improve MHV and VVC use. Findings from this effort will inform a larger pragmatic trial and offer insights that can be extended into other clinical scenarios where digital training could be embedded. Specific Aims: The aims of this study are: Aim 1: Engage 50 hospitalized Veterans to determine Veteran's access to the internet, digital literacy needs, and preferences for using VA virtual care and 20 inpatient providers to aid in optimizing an inpatient intervention to improve digital engagement; Aim 2: Conduct a three- arm randomized pilot study of an inpatient digital literacy intervention among 75 hospitalized Veterans to assess whether digital literacy and downstream use of MHV and VVC post-discharge improve across study arm; and Aim 3: Examine acceptability, feasibility, and satisfaction of the digital literacy intervention. Methodology: This study will first perform a Needs Assessment among 50 hospitalized Veterans and interview 20 providers to optimize the intervention to avoid interfering with clinical processes. Second, we will assess the effectiveness of a pilot intervention with (1) “high-intensity” personalized bedside training, (2) “low- intensity” written education materials, or a (3) no digital training control arms. Third, we will obtain feedback and assess barriers and facilitators among Veterans who received the high- and low-intensity inpatient digital training using a semi-structured telephone interview 30-days post-discharge. We will focus on two outcomes: (1) changes in digital literacy as measured by the Mobile Device Proficiency Questionnaire-16 at 30-days post- hospitalization, and (2) engagement with MHV and VVC at 30-, 90- and 120-days post-discharge. We will also assess secondary outcomes of 30-, 90- and 120-days post-discharge primary care, subspecialty care, and mental health visits, no-show rates, use of the emergency department and hospitalization rates during the same time periods using electronic health records data from the VA's Corporate Data Warehouse. Next Steps/Implementation: The findings from this proposal will act as pilot data for a VA Merit application to perform a larger, pragmatic, cluster randomized trial assessing the impact of an inpatient digital literacy service on subsequent digital use (MHV and/or VVC) and post-hospitalization utilization (e.g., primary, subspecialty care, and mental health visits, no-show rates, emergency department use, and hospital readmission).

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DRA: Other Conditions

DRE: TRL - Applied/Translational, Data Science

Keywords: None at this time.

MeSH Terms: None at this time.