# An eHealth intervention to increase depression treatment initiation and adherence among Veterans referred for mental health services

> **NIH VA IK2** · JAMES A. HALEY VA MEDICAL CENTER · 2021 · —

## Abstract

Background: Depression is the most prevalent mental health disorder in VHA and is strongly
associated with disability and suicide mortality, especially when untreated. Understanding the
profiles of patients that disengage from care will help develop support systems to improve care
utilization and outcomes. According to Levesque’s framework, relevant patient characteristics that
lead to care access map onto a process that incorporates identifying health care needs and desire
for care, healthcare seeking, reaching, and utilization, all leading to health care outcomes. Using this
framework, the proposed CDA takes a two-prong approach in response to underutilization of care
among those with depression by: developing risk predictive models through analytics methodology
and leveraging the role of mood and symptom self-monitoring as key components in depression
management. Significance/Impact: The knowledge developed through this CDA has long term
implications for OEF/OIF Veterans who are at highest risk for depression and suicide. Depression
has a significant impact on Veterans, providers, and the VA. It is a disorder that is linked to
substantial medical and economic burden in the VA. Depression is a risk factor for the development
and maintenance of medical and psychiatric conditions (i.e., PTSD, TBI). Despite persistent efforts
to increase care for depression, treatment guidelines are exclusively focused on those engaging in
care. Pre-treatment interventions have the potential to increase mental health care utilization and
reduce depression related burden on patients and the VA. Such interventions can minimize provider
burden by reducing no shows and by increasing adherence. Innovation: Research shows that the
VA has the potential to foster the development of tools to enhance mental health care for Veterans.
To fill gaps in the use of analytics and technology in enhancing care for mental health concerns, the
proposed work is innovative in two ways: 1) we propose the use of big data and analytics tools to
identify patient profiles associated with mental health treatment engagement and increased risk for
drop out of care; 2) develop a technology driven intervention to increase self-efficacy and active
engagement in mental health care. Specific Aims: RA1: Identify risk profiles (scores) associated
with depression treatment use. Test prediction models using VHA electronic health records (EHR).
Risk scores computed in Aim 1 will be used in selection of patients at risk and eligible for the
proposed intervention.TA1: Gain proficiency in methods and analysis of EHR/big data. RA2: Design
an eHealth intervention using technology driven self-monitoring. TA2: Develop skills and knowledge
about intervention development. RA3: Formatively evaluate and pilot the eHealth intervention. TA3:
Gain proficiency in formative evaluation. Methodology: RA1 will use a retrospective cohort design.
Leveraging the strengths of EHR data and analytics tools, we will investigate r...

## Key facts

- **NIH application ID:** 10064813
- **Project number:** 1IK2HX002899-01A2
- **Recipient organization:** JAMES A. HALEY VA MEDICAL CENTER
- **Principal Investigator:** Vanessa Panaite
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2021
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2021-04-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10064813

## Citation

> US National Institutes of Health, RePORTER application 10064813, An eHealth intervention to increase depression treatment initiation and adherence among Veterans referred for mental health services (1IK2HX002899-01A2). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10064813. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*