# Improving Access Through Targeted Delivery of Telemedicine

> **NIH VA IK2** · VETERANS AFFAIRS MED CTR SAN FRANCISCO · 2021 · —

## Abstract

Background: Improving access to care is a high priority within the VA. While improvements to access have
been made in recent years, gaps and inefficiencies still exist, particularly around missed clinic visits, or `no-
shows'. The VA reports that approximately 15-18% of scheduled outpatient primary care appointments are not
completed and that 9.2 million appointments were lost because of no-shows in FY2017. In preliminary work,
we demonstrated the importance of social risk factors on VA no-show rates. These findings suggest that a no-
show prediction model that incorporates patient-level factors could predict missed clinic rates and provide
clinical phenotypes (i.e. an aggregate description of a Veterns' social vulnerabilities) of Veterans at greatest
risk of no-showing. VA Video Connect (VVC) is a newly developed telemedicine application that provides video
conferencing services as a means to connect Veterans with their VA medical providers. With VVC, Veterans
can access their VA provider from any mobile or web-based device (e.g. smartphone, tablet, or computer) and
do not need to be located at a satelite clinic. Previous work supports the idea that VVC could be targeted to
those at elevated risk of no-showing clinic appointments. This CDA proposes a risk-based, targeted use of
VVC in patients with social vulnerabilities as a means of decreasing clinic no-shows.
Significance: This proposal aims to improve access to care by identifying, describing and engaging Veterans
who would most benefit from alternative methods of primary care, specifically VA Video Connect.
Innovation: This research has several innovative aspects to it. First, we will utilize machine-learning predictive
techniques to identify and describe Veterans who are at highest risk of no-showing based on their social risk.
This methodology has never been utilized in addressing no-shows. Second, we will actively engage Veterans
in a formative assessment of how to optimize the use of VVC as an alternative method to obtaining primary
care. Engaging Veterans throughout this proposal will ensure that Veterans' voices are properly integrated into
the final product. Finally, this proposal utilizes novel telemedicine technologies (i.e. VVC) as a means of
improving access for Veterans who are at high risk of missing clinic visits.
Specific Aims & Methodology: (1) Use regression tree analysis to phenotype Veterans based on their
estimated risk of no-showing clinic appointments. Hypothesis: Social risk factors are associated with no-
shows in the ambulatory VA population and certain phenotypes will have higher no-show rates compared to
others. (2) Use a sequential exploratory mixed methods design to engage phenotyped Veterans at high
risk for no-showing and assess Veteran suitability and capability of using VVC. Hypothesis: Certain
phenotypes of Veterans will be optimally served by VVC, while other phenotypes will require higher intensity
primary care programs or continued in-person care. (3) Pi...

## Key facts

- **NIH application ID:** 10178548
- **Project number:** 1IK2HX003139-01A2
- **Recipient organization:** VETERANS AFFAIRS MED CTR SAN FRANCISCO
- **Principal Investigator:** Charlie M Wray
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2021
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2021-02-01 → 2026-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10178548

## Citation

> US National Institutes of Health, RePORTER application 10178548, Improving Access Through Targeted Delivery of Telemedicine (1IK2HX003139-01A2). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10178548. Licensed CC0.

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