Veterans at high-risk for hospitalization, including those with complex care needs, represent a large population of VHA patients who often do not receive evidence-based primary care practices that would help them avoid the hospital and improve their health. The high-RIsk VETerans (RIVET) Program will implement evidence-based practices that can support VHA Primary Care teams to deliver more comprehensive and patient-centered care, better strategies to manage medications, and avoid unnecessary hospitalizations. The RIVET Program is designed to find the most effective approaches to increasing use of evidence-based practices for high-risk Veterans in primary care, provide rapid data feedback to VHA on high-risk patient care, build capacity for the implementation of evidence-based practices, and train future leaders in high-risk Veteran care.
The top 5% of Veterans at the highest risk for hospitalizations account for almost 50% of VHA healthcare costs, have significant multimorbidity, and are also at high risk for poor health outcomes. In the VHA, most (88%) high-risk patients are managed by general primary care teams (i.e., Patient-Aligned Care Teams; PACTs). Few PACTs, however, have implemented evidence-based practices (EBPs) known to address the most common issues among high-risk Veterans. Some evidence indicates that usual implementation strategies, such as dissemination of toolkits and training are not effective for improving uptake of EBPs. The most effective implementation strategies to achieve evidence-based care for high-risk patients, however, are unknown. The overall impact goal of the high-RIsk VETerans (RIVET) QUERI Program is to improve VHA primary care capacity to provide comprehensive, evidence-based care for complex, high-risk Veterans. The investigators will test 2 implementation strategies to evaluate their impact on the uptake of two separate EBPs. These EPBs are 1) Comprehensive Assessment and Care Planning (CACP), and 2) Phone-Based Health Coaching for Medication Adherence (HCMA). CACP is based on the Comprehensive Geriatric Assessment and guides teams in systematically addressing patients' cognitive, functional, and social needs through a comprehensive care plan. HCMA addresses common challenges to medication adherence using a patient-centered approach through virtual encounters. Both comprehensive assessments and health coaching have demonstrated efficacy in randomized, controlled trials and have been implemented by two of the national partners in geriatrics and Whole Health teams. However, both EBPs have had low uptake in primary care. Implementing these practices in primary care has the potential to improve quality of care for the large majority of high-risk Veterans. The investigators will conduct a mixed methods type 3 hybrid effectiveness-implementation design to test the effectiveness of EBQI-IC and EBQI-LC versus usual care (national tool dissemination and training efforts) in at least 16 sites in multiple VISNs using a Concurrent Stepped Wedge design (Aim 2). The primary outcome is proportion of eligible high-risk patients that receive each EBP. The investigators will use the Practical, Robust Implementation and Sustainability Model (PRISM) framework to compare and evaluate Reach, Effectiveness, Adoption, Implementation, and costs. The investigators will then assess the Maintenance/sustainment and spread of both EBPs in primary care across all sites after the active 18-month implementation period (Aim 3).
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
17
Individual (ongoing) consultation (IC), often described as coaching or supervision, is endorsed by implementation experts as an effective implementation strategy
A Learning Collaborative is a systematic approach to process improvement based on the Institute for Healthcare Improvement Breakthrough Series Collaborative model. During the Collaborative, organizations will test and implement system changes and measure their impact. They will share their experiences to accelerate learning and broader implementation of best practices.
VA Greater Los Angeles Healthcare System, Sepulveda, CA
Sepulveda, California, United States
VA Pittsburgh Healthcare System University Drive Division, Pittsburgh, PA
Pittsburgh, Pennsylvania, United States
VA Puget Sound Health Care System Seattle Division, Seattle, WA
Seattle, Washington, United States
Change in the proportion of team-assigned primary care patients in the upper 90th percentile of acute hospitalization risk (identified via VA CAN score) who received the Evidence Based Practice (EBP)
This primary outcome aims to measure reach of the evidence practices to implement the EBP.
Time frame: 18
Number of PACT encounters from social worker, pharmacist, nurse and integrated mental health
This secondary outcome will measure the impact of EBPs on the proximal care process.
Time frame: 18 months
Number of encounters from PACT pharmacist, social worker, nurse and integrated mental health
This secondary outcome will measure the impact of EBPs on the proximal care process.
Time frame: 18 months
Comprehensiveness of Care questions from the RIVET Patient Survey- consisting of three items, which was sourced from the SHEP
This secondary outcome will measure patient impact due to EBPs.
Time frame: 18 months
Self-Management Support questions from the RIVET Patient Survey- sourced from the SHEP, which is two items in the survey.
This secondary outcome will measure patient impacts due to EBPs .
Time frame: 18 months
PACT provider perceived support for high-risk patient care questions from the RIVET Clinician Survey- three survey items assessing confidences, skills and strain/satisfaction with caring for high-risk patients
This secondary outcome will measure patient impacts of EBP#1 (CACP).
Time frame: 18 months
Providers Discuss Medication Decisions (Patient Survey)
This secondary outcome will measure patient impacts of due to EBPs.
Time frame: 18 months
Self-Management Support (Patient Survey)
This secondary outcome will measure patient impacts of due to EBPs.
Time frame: 18 months
Total number of ambulatory care-sensitive and acute hospitalizations
This secondary outcome will measure clinical quality due to EBPs.
Time frame: 18 months
Total number of ambulatory care-sensitive and and emergency department visits
This secondary outcome will measure clinical quality due to EBPs.
Time frame: 18 months
Patient self-reported medication adherence This survey is a 3-item scale developed and validated in Veteran populations
This survey is a 3-item scale developed and validated in Veteran populations.
Time frame: At the beginning and end of 18-month implementation period
Adherence to chronic medications (diabetes, hypertension, hyperlipidemia, mental health) (VA Pharmacy Data)
This secondary outcome will measure clinical quality outcome of EBP#2(HCMA). Medications will be calculated via VA pharmacy fill data using Proportion of Days Covered (PDC).
Time frame: The 18-month implementation period
Adoption of Evidence Based Practice (EBP)
Proportion of staff trained on EBPs.
Time frame: 30-months
HEDIS measures for diabetes, hypertension, hyperlipidemia management
This secondary outcome will measure clinical quality outcome due to EBPs.
Time frame: The 18-month implementation period
Fidelity
The fidelity assessment tool draws from data collected from key stakeholder interviews , implementation facilitation logs , administrative documents, and weekly time diaries. The team will apply criteria to rate sites as high-, medium-, or low-fidelity on the EBQI elements.
Time frame: 18 months
EBP Fidelity
A composite EBP fidelity measure for each EBP will be assessed by percent of items completed.
Time frame: 18 months
Implementation costs
Implementation Core staff time spent in various implementation activities
Time frame: 18 months
Facility adopting cost
Cost calculated from time incurred by facilities adopting the EBPs
Time frame: 18 months
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