Abstract

Background: Chronic pain is prevalent among Veterans and has myriad negative consequences. Despite recommendations and high interest among Veterans, multimodal non-pharmacological modalities (M-NPM) for chronic pain are underused in VA in part due to access barriers. The MISSION Act expanded VA community care (VACC) in 2018 to address access issues, and studies show VACC may help to address gaps in access to VA facility care. However, expansion has also been accompanied by mixed effects on quality and costs of care and increased unsafe opioid prescribing. This variation in VACC outcomes is in part the result of policy implementation issues. Whether policies such as the MISSION Act achieve their intended goals depends both on their design and implementation, including activities undertaken to meet policy goals after they are enacted. There is an urgent need to identify successful VACC implementation approaches specific to chronic pain care. Significance: In keeping with the goals of VA and the MISSION Act, VACC should enhance Veterans’ access to high-quality care but not result in unsustainable spending. Such optimal implementation of VACC has not yet been realized, and identifying ingredients for success is a focus of this research. We aim to identify elements for improving VACC implementation pertaining to chronic pain care, which has the potential to positively impact Veterans with chronic pain and support VA leaders’ need to better manage VACC access, quality, and costs. Innovation and Impact: The proposed research blends health economics and policy evaluation methods with implementation science; leverages the knowledge and experiences of VA operations and clinical leaders at VA facilities that have been more successful with VACC implementation specific to chronic pain care; and focuses on participatory decision-making with Veterans, caregivers, and VA staff to design an implementation guide. Specific Aims: Aim 1. Examine associations between VACC use and indicators of sub/optimal health care use among Veterans with chronic pain, overall and by VA medical center. Aim 2. Quantify associations between VACC use and indicators of sub/optimal health care costs among Veterans with chronic pain, overall and by VA medical center. Aim 3. Identify successful approaches and develop an implementation guide for improving VACC implementation pertaining to chronic pain care through use of implementation mapping and participatory decision-making methods with VA staff, Veterans, and caregivers. Methodology: This study uses a sequential explanatory design. In Aims 1 and 2, regression discontinuity (RD) studies will examine associations between VACC use and indicators of sub/optimal health care use and costs among Veterans with chronic pain. Aim 1 health care use indicators include receipt of M-NPM (optimal) and concurrent prescriptions of opioids and benzodiazepines (fewer is optimal). Aim 2 indicators include costs of ED visits and hospital stays (less is optimal). Results will be used to quantify high, mixed, and low performance for each VA medical center on VACC implementation specific to chronic pain care. In Aim 3, implementation mapping with VA clinical and operations staff at high performing facilities will uncover effective approaches for VACC implementation pertaining to chronic pain care. Participatory decision-making methods with VA staff and Veterans will prioritize approaches, and high-priority approaches will be included in an implementation guide. Next Steps/Implementation: Project data will support the work of operations partners and inform two VA Investigator Initiated Research proposals (IIRs). The first IIR (Year 3) will be a mixed-methods study comparing care integration, experiences, and outcomes of Veterans with chronic pain who use VA-delivered care through in-person and telehealth venues and those who use VA-delivered and non-VA care. IIR #2 (Year 5) will test the utility of the implementation guide for improving the delivery of chronic pain care across VA and VACC settings.

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DRA: Health Systems Science

DRE: Treatment - Implementation, TRL - Applied/Translational, Data Science

Keywords: None at this time.

MeSH Terms: None at this time.