Poster Paper: The Win-Win Tool: Making Clear the Impacts of Community Level Interventions to Support Evidence-Based Policies

Saturday, November 5, 2016
Columbia Ballroom (Washington Hilton)

*Names in bold indicate Presenter

Asya Spears1, Nathaniel Anderson2, Brian Cole2, Jonathan Fielding2, Jeremy Fuller2, Boyd Jackson2, Natalie Rhoads2, Sophie Snyder2, Steven Teutsch2 and Frederick Zimmerman2,3, (1)Pardee RAND Graduate School, (2)University of California, Los Angeles, (3)University of California, Los Angeles

What if county-level decision makers could estimate the health, education, and public safety impacts of spending their budget surplus on, for example, an intervention aimed at mental health? The Win-Win tool is designed to help answer these kinds of questions across a variety of interventions and geographic regions.  The goal of the Win-Win tool is to assist decision makers in determining the most cost effective ways to achieve particular health outcomes, using a cohort-based approach to estimate the impacts of the most promising interventions in the domains of interest. The impact of one intervention, a Nurse Home Visit program, is estimated by assuming eligible families are enrolled prior to the birth of a child, and tracking outcomes for these families over a 26 year period. Beginning at the zip code level, data are entered into the model, retaining the flexibility to be aggregated to service planning areas and other subregions of interest. Annual effects can be estimated in the domains of health, education, public safety, and returns to the funding agency. Results are presented via Tableau, allowing interaction and real-time querying of the model across a range of geographies and stakeholders. To showcase the visual accessibility of the findings, this poster presents impact estimates of three interventions – a Nurse Home Visit Program in Los Angeles, Universal Pre-K in San Diego, and School Based Obesity Programs in San Antonio.