# Sustaining STAR-VA:  Partnered Evaluation of Veteran, Implementation and Facility Factors Contributing to Positive Sustained Outcomes to Inform Ongoing Program Implementation

> **NIH VA I50** · VA WESTERN NEW YORK HEALTHCARE SYSTEM · 2020 · —

## Abstract

STAR-VA, a Veteran-centered, interdisciplinary, behavioral approach for managing behavioral symptoms
of dementia (BSD) among Veterans Health Administration Community Living Center (CLC) residents, has been
implemented in 66 trained CLC sites between 2013 and 2016. Collaborative evaluation is necessary to
demonstrate the longitudinal impact of STAR-VA on CLC Veteran and site level outcomes, and determine
factors associated with sustained implementation and positive outcomes, in order to support program
sustainability and expansion. This project intends to identify a quality indicator for monitoring behavior change
among CLC residents with dementia, determine Veteran, intervention, and facility/site factors that predict
sustained positive behavioral and systemic outcomes, and identify facilitators and barriers to sustained STAR-
VA implementation. Project outcomes will inform development and recommendations for an implementation
and evaluation strategy for an outcome-driven, tailored intervention to support CLC teams in sustaining
STAR-VA. Specific aims are to:
1. Develop and validate a quality indicator for monitoring the prevalence of BSD, using Minimum Data Set 3.0
 behavior measures, validated by STAR-VA outcome measures;
2. Evaluate the longitudinal impact of STAR-VA by comparing site and resident outcomes at trained and
 untrained CLCs in years 2013-2016 on BSD, psychotropic use, and, for sites, staff injuries, and identify
 high and low performing CLC sites.
3. Explain variations in the sustained implementation of STAR-VA using qualitative methods with a
 purposeful sample of trained CLC sites, examine what Knowledge Reservoir (KR) domains are present in
 CLC sites and the impact of these KRs and additional factors on sustainment.
 Objective #1: Create a BSD quality indicator from mandatory Resident Assessment Instrument Minimum
Data Set (MDS) 3.0 behavior variables, validated by STAR-VA outcome measures of behavior, depression and
anxiety collected for 280 Veterans enrolled in STAR-VA between 2013 and 2016. STAR-VA participating
Veterans have a dementia diagnosis and display repeated behaviors that are distressing to the resident or
others, not directly related to delirium, other acute illness, psychotic symptoms, or recent brain injury. Objective
#2: Evaluate the impact of STAR-VA by comparing trained and untrained CLC sites and residents in years
2013-2016 on selected outcomes, and identify resident, implementation, and facility factors associated with
BSD. Resident level outcomes will include rates of BSD and psychotropic use in CLC residents using MDS 3.0
behavior quality indicator and Psychotropic Drug Safety Initiative (PDSI) data. CLC site level outcomes will be
based on: a) Overall rates of BSD in the CLC (using MDS 3.0 behavior quality indicator and Workplace
Behavioral Risk Assessment disruptive behavior reporting system), b) Antipsychotic and antianxiety medication
use from PDSI program data, and c) Nursing staff injuries, using ...

## Key facts

- **NIH application ID:** 10021439
- **Project number:** 5I50HX002383-02
- **Recipient organization:** VA WESTERN NEW YORK HEALTHCARE SYSTEM
- **Principal Investigator:** Kimberly J. Curyto
- **Activity code:** I50 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2020
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2018-01-01 → 2019-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10021439

## Citation

> US National Institutes of Health, RePORTER application 10021439, Sustaining STAR-VA:  Partnered Evaluation of Veteran, Implementation and Facility Factors Contributing to Positive Sustained Outcomes to Inform Ongoing Program Implementation (5I50HX002383-02). Retrieved via AI Analytics 2026-07-28 from https://api.ai-analytics.org/grant/nih/10021439. Licensed CC0.

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