Abstract

Background: Low-value medical services are common and costly. Veterans often receive services that offer little or no clinical benefit while generating costs and unnecessary risks. Gaps in research have hindered effective policies to address low-value Veteran care. First, the causes of low-value service use are uncertain. For example, through the VA Community Care program (VACC), Veterans are treated by non-VA clinicians who face few incentives to avoid unnecessary tests and procedures. However, it is unclear whether VACC has increased Veterans’ risk of receiving low-value services. Our research has shown an association between greater use of VACC and increased rates of low-value care. Rigorous quasi-experimental research could confirm whether this association is causal, guiding appropriate policy responses. Second, policies addressing low-value care have been hindered by a lack of evidence on what constitutes low-value care and how to translate evidence into effective clinical decision-making. To address these research gaps, first, I will test whether VACC under Choice/MISSION has increased low-value care. Second, I will study strategies to address low-value care via evidence development and evidence translation. Significance/Impact: Addressing low-value health care use is of crucial importance to Veterans, aligning with multiple dimensions of HSR&D priority domains including priority research areas (health care value, quality and safety of health care), priority HSR methods (advancing HSR methods in areas that cut across conditions or care settings), and priority policy/legislative areas (MISSION Act). Innovation: This research applies innovative methods to novel research questions. The quantitative methods have wide potential applications across VA HSR, though they have been rarely applied in this setting. Specific Aims: This Career Development Award (CDA) would support the following research aims: Aim 1 Quantify the effect of VACC under Choice/MISSION on Veterans’ low-value service use and spending. Aim 2a Convene an expert panel to identify and prioritize “gray zone” services ideal for evidence development. Aim 2b Conduct focus groups to identify barriers and facilitators to translating new evidence on service value into high-value practices Methodology: Aim 1: Using 33 measures of low-value services applied to national clinical data, we will test the effect of outpatient VACC on low-value service use and spending. A regression discontinuity (RD) analysis will examine a natural experiment that arose because VACC eligibility can differ for otherwise similar Veterans who live slightly different distances from VA facilities. Machine learning covariate selection techniques will optimize statistical power. Aim 2a: Via an expert consensus building process, clinicians, researchers and Veterans will prioritize “gray zone” services, which have unclear value, for evidence development. Services will be prioritized based on incidence among Veterans, expected costs/harms, and analytical tractability for RD analysis in VA data. Aim 2b: We will conduct focus groups with clinical and health system leaders as well as Veterans; drawing on a conceptual model of health care value, we will identify barriers and facilitators to translating new evidence on low-value services into high-value practices. Complementary training aims in qualitative methods, machine learning, and learning health system competencies will support the research aims. Next Steps/Implementation: This work has the support of the VA Office of Analytics and Performance Integration and VA Office of Community Care, operational partners whose efforts to detect and address low- value care will be enhanced by this research. I will collaborate with the VA Office of Community Care to assess how Aim 1 results will inform their efforts to discourage low-value care in VACC. I will submit one IIR proposal evaluating VA efforts to employ utilization management strategies in VACC. I will submit a second IIR proposal to quantify the value of high-priority gray zone services identified in Aim 2.

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DRA: Mental, Cognitive and Behavioral Disorders, Substance Use Disorders, Health Systems

DRE: Technology Development and Assessment

Keywords: Career Development

MeSH Terms: None at this time.