Abstract

Background: This CDA will provide me, Megan E. Vanneman, PhD, MPH, with the training and experience to become an independent health services researcher who applies decision science and informatics to improve Veterans’ access to and engagement in high-quality care. To help achieve this goal, I will work with my mentors, consultants, and operational partners to develop and evaluate an information and decision support tool to improve VA leaders’ understanding and decision-making about VA enrollment and reliance (proportion of care received at VA) on primary and mental health care. Significance/Impact: This research will have a positive impact on VA leaders, Veterans interested in enrolling in VA health care, and Veterans needing primary and mental health care, by increasing understanding of how access, quality, enrollment, and reliance can be optimized to better meet Veterans’ needs. As the VA moves from a more closed, integrated healthcare system to providing care through networks that include community partners, VA leaders need to better understand enrollment, reliance, access, and quality at their local facilities and VISNs, particularly for “foundational services,” such as primary and mental health care. The CDA strongly aligns with top VA priorities – increasing choice for Veterans, modernizing the VA system, using VA resources more efficiently, and improving timeliness of services. Innovation: While we know that about 50% of Veterans enroll in VA and that about 50% of care for these enrollees is provided in the VA, we have little understanding of what drives these decisions for recently separated Servicemembers – those who participated in conflicts in Iraq and Afghanistan. Preliminary studies show that there is wide variation in VA facility enrollment rates, but we do not have data on variation in VA facility reliance rates. Furthermore, we do not understand what drives these differences. Although there is some understanding of individual (e.g., age) and community-level (e.g., non-VA provider supply) factors that influence VA enrollment and utilization, we lack understanding of facility factors that can be modified to appropriately connect Veterans to VA and needed services thereafter. Specific Aims: The research plan has three primary goals: 1) Learn what information and resources VA facility and VISN leaders need to better understand and manage enrollment rates and reliance rates for primary and mental health care; 2) Derive insights on facility factors by evaluating relationships among enrollment rates, reliance rates, access to care, and quality of care for primary and mental health care; and 3) Develop or modify existing information tool(s) to assist facility and VISN leaders to manage enrollment and reliance rates for primary and mental health care. Methodology: This CDA seeks to fill the gap in understanding on enrollment and reliance for primary and mental health care through a mixed-methods approach by: producing descriptive data on facility enrollment and reliance rates (Aim 1.1); qualitatively studying Veterans’ insights on their decisions regarding enrollment and reliance in interviews involving VA enrollees and non-enrollees (Aim 1.2); interviewing VA leaders about their information needs regarding enrollment and reliance (Aim 1.3); using hierarchical modeling to understand what modifiable facility factors on access and quality are associated with enrollment and reliance rates (Aim 2); and developing, testing, and implementing a tool to assist VA leaders to improve enrollment and reliance rates (Aim 3). Next Steps/Implementation: Study results will help VA healthcare leadership target changes that they can make to manage enrollment and retention of Veterans in the VA healthcare system and deliver needed foundational services. Results will also inform my future work on information and resource allocation tools to support Veterans’ and leaders’ decision making.

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DRA: Health Systems Science

DRE: Technology Development and Assessment, TRL - Applied/Translational

Keywords: Career Development, Organizational Structure

MeSH Terms: None at this time.