# Implementing and Evaluating Computer-Based Interventions for Mental Health

> **NIH VA IK2** · VA CONNECTICUT HEALTHCARE SYSTEM · 2020 · —

## Abstract

Background. Computer-based interventions (CBIs) provide a potentially effective platform for increasing
Veteran access to evidence-based treatment for disorders common in primary care such as depression,
anxiety, and insomnia. Because of their advantages, Congress mandated that VA implement CBIs via the
Veterans' Mental Health and Other Care Improvements Act of 2008.3 However, efforts to evaluate strategies
for CBI implementation in VA primary care have been limited. The Supported-CBI Implementation Strategy
was developed to implement a range of mental health CBIs in primary care and consists of four components:
(1) a clinical intermediary for patient support, (2) provider/staff facilitation and education, (3) patient education,
and (4) stepped-care for those requiring additional treatment. A recent pilot study at VACT demonstrated the
feasibility of a CBI for insomnia in VA outpatient care when implemented via Supported-CBI.
Objectives. The focus of this work will be on using CBIs as intervention platforms and not a specific program
or disorder. However, the RESTORETM program for the treatment of insomnia, will be used for testing. There
are three objectives: (1) adapt Supported-CBI to current VA primary care organizations, (2) test the
effectiveness of Supported-CBI and the clinical outcomes of RESTORETM in VACT primary care, and (3)
explore the development of informatics-based processes to track the diffusion of CBI use throughout VA.
Hypotheses.
1. Supported-CBI can be modified for use in VA primary care by identifying barriers/facilitators revealed by
 national and local primary care providers and administrators.
2. Supported-CBI, relative to a control implementation strategy, will demonstrate superior rates of (a) CBI
 engagement by patients, (b) provider adoption through referral to the CBI, and (c) patient completion of the
 CBI, as well as (d) improved patient insomnia outcomes.
3. VA organizations/providers who are early- and non-adopters of CBI use can be identified from VA medical
 record documentation. Once identified, interviews will validate informatics findings, identify additional
 barriers/facilitators, and reveal sites interested in a multi-site trial of Supported-CBI.
Methods. Barriers/facilitators to Supported-CBI implementation will be identified through the qualitative
analysis of semi-structured interviews and focus groups with VA-wide primary care leadership and members of
local VACT primary care teams. The preliminary effectiveness of Supported-CBI and clinical outcomes of
RESTORETM (compared to a low-intensity [control] strategy) will be evaluated in a hybrid type 3
implementation-effectiveness trial. Summative and process-level implementation outcomes as well as clinical
insomnia outcomes will be evaluated over a six-month period and the sustainment of implementation over an
additional year. The diffusion of CBI use across VA will be evaluated using information retrieval from a national
dataset of VA clinical notes to ...

## Key facts

- **NIH application ID:** 10208955
- **Project number:** 5IK2HX001772-04
- **Recipient organization:** VA CONNECTICUT HEALTHCARE SYSTEM
- **Principal Investigator:** ERIC HERMES
- **Activity code:** IK2 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2016-07-01 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10208955

## Citation

> US National Institutes of Health, RePORTER application 10208955, Implementing and Evaluating Computer-Based Interventions for Mental Health (5IK2HX001772-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10208955. Licensed CC0.

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