NYU Wagner Universal Pre-K & Neighborhood Gentrification Kacie - PowerPoint PPT Presentation

Policies for Action at NYU Wagner Universal Pre-K & Neighborhood Gentrification Kacie Dragan June 26, 2017 Academy Health Annual Research Meeting

New York State Medicaid Claims • 6-7 million patients/year • 200-300 million claims/year • Also available: social, welfare, and demographic data Furman Center for NYU Health Evaluation and NYC Government Real Estate and Analytics Lab (HEAL) Agencies Urban Policy NYU Wagner’s Policies for Action Hub PI: Dr. Sherry Glied, Dean of NYU Wagner NYU Faculty (social Rudin Center for policy, health Transportation economics, etc.) Center for Urban Institute for Science and Education and Progress Social Policy

T oday’s policies Tomorrow’s policies Examples of projects Evaluating the effect of Producing evidence for today’s policies tomorrow’s policies • Universal Pre-K Evaluation • Housing and gentrification • Cross-sector collaboration: • Cross-sector collaboration: • Education sector researchers / • Furman Center for Real Estate and Urban Policy policy-makers • NYU CUSP machine learning experts • Early childhood health experts • NYC Housing Authority • ENT clinician • Early childhood health experts

T oday’s policies Tomorrow’s policies Universal Pre-K evaluation • Relevant non-health policy: • UPK phased in over two years (2014-2015 and 2015-2016) for children born 4 calendar years prior • Design: • Difference-in-Regression Discontinuity design (“DRD”) • Total n across all comparisons: 715K • Results: • Increased the probability of diagnoses of asthma or vision problems, treatment for hearing or vision problems, or screening during the prekindergarten year. • UPK accelerated the timing of diagnoses of vision problems. • No increases in injuries, infectious diseases, or overall utilization. • These effects are not offset by lower screening rates in the kindergarten year

T oday’s policies Tomorrow’s policies Universal Pre-K evaluation (cont.) • Dissemination: • Urban Institute website & event • Chalkbeat interview • Meetings with NYC policymakers • Reception: • NBER • Under peer-review • Faculty interest • Next steps: • Follow-up study into seasonal flu pattern / epidemic curve • Deeper diver into hearing problem detection among Medicaid children through other policies

Today’s policies Tomorrow’s policies Gentrification & housing • Relevant non-health policies: • Rent regulation, public housing, real estate and land use regulation • Study designs: • Longitudinal and time series analyses (gentrification) • Machine learning classification algorithm (housing quality) • Natural experiments of interventions (housing quality) • Total n: 239,804 children born between 2006 and 2008

Today’s policies Tomorrow’s policies Gentrification & housing • Relevant non-health policies: • Rent regulation, public housing, real estate and land use regulation • Study designs: • Longitudinal and time series analyses (gentrification) • Machine learning classification algorithm (housing quality) • Natural experiments of interventions (housing quality) • Total n: 239,804 children born between 2006 and 2008

Today’s policies Tomorrow’s policies Gentrification & housing (cont.) • (Preliminary) Results: • Children born into gentrifying neighborhoods do not look very different from those born into persistently poor areas. • Children born into persistently high income neighborhoods generally appear to have more favorable health outcomes. • Differences between the groups appear to taper off toward the end of the period.

Today’s policies Tomorrow’s policies Gentrification & housing (cont.) Trend 1. Medicaid enrollment and moving patterns differ by neighborhood gentrification status OR: 1.3 (p<0.0001) OR: 0.87 (p<0.0001)

Today’s policies Tomorrow’s policies Gentrification & housing (cont.) Trend 2. Children born into persistently high income neighborhoods appear to be doing better than those in gentrifying or persistently poor neighborhoods. However, these differences taper off after 2013. OR: 0.72 (p<0.0001)

Today’s policies Tomorrow’s policies Gentrification & housing (cont.) Trend 2 (cont.). And these patterns do not seem to be due to racial residential segregation exclusively, but rather are moderated by race/ethnicity. White and Asian children do not experience differences by neighborhood type, whereas Black, Hispanic, Other, and Unknown races do (interaction terms significant at p < 0.0001).

Today’s policies Tomorrow’s policies Gentrification & housing (cont.) Trend 3. For some conditions, however, we see starkly similar rates across all levels of gentrification status.

Today’s policies Tomorrow’s policies Gentrification & housing (cont.) Trend 4. For anxiety and depression, rates among children born into gentrifying areas do begin to pull away from the other types of neighborhoods by 2014-2015. We also see differences among those who move compared with those who don’t. OR: 1.1 (p=0.04) OR: 1.4 (p<0.0001)

Thank you! Questions? Feedback? Ideas? Kacie Dragan, MPH Sherry Glied, PhD Associate Research Scientist Dean & Professor of Public Service NYU Wagner | Policies for Action Hub NYU Wagner kacie.dragan@nyu.edu sherry.glied@nyu.edu 212-998-7564 https://healthanalyticsatnyu.org/