Natural Experiment of Value-Based Incentives for Preventive Services

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DESCRIPTION (provided by applicant): Financial incentives can be powerful tools to influence health care behavior. The literature suggests that patients faced with high levels of cost-sharing have lower use of preventive services than patients with less cost-sharing, but there are few studies in children and only a limited number of studies in any population demonstrating that the elimination of cost-sharing increases use of prevention. This alignment of insurance benefit design with clinical goals, aka value-based insurance design (VBID), is a central feature of the recent Patient Protection and Affordable Care Act (ACA). The ACA requires that all health insurance plans eliminate cost-sharing for high value preventive services including those services recommended by the US Preventive Services Task Force (USPSTF) and the Centers for Disease Control and Prevention (CDC) as of 2011; the ACA, however, exempts existing employer-sponsored (i.e., group) insurance plans from these policies provided that the plans do not make major changes in their benefits or prices. Thus, individuals within these "grandfathered" plans continue to face the same cost-sharing for preventive care. We will exploit this natural experiment to examine how the elimination of cost-sharing for annual wellness visits and immunizations affects children and adolescents (age up to 21 years). Individuals enrolled in group health insurance plans without cost-sharing changes and tests not recommended by the USPSTF provide concurrent comparative information. Using data from the MarketScan Databases and from Kaiser Permanente, the project will examine the early clinical and economic effects of this ACA-mandated health insurance policy change on our outcomes: Aim 1) office visit rates; Aim 2) immunizations; and Aim 3) total medical spending. Our data contain detailed, comprehensive information on insurance benefits, individual characteristics, immunizations, clinical events, and medical spending. The study sample includes subjects with a range of baseline cost-sharing amounts and in the timing of cost-sharing changes. Our primary analyses will focus on within-person changes (fixed effects estimation), and will adjust for a rich set of demographic, clinical, and system characteristics. With several million person-years of data, we will have adequate power to detect even small changes in our outcomes.