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

NYU Wagner’s Policies for Action Hub

PI: Dr. Sherry Glied, Dean of NYU Wagner

Furman Center for Real Estate and Urban Policy Rudin Center for Transportation NYC Government Agencies NYU Faculty (social

policy, health economics, etc.)

Institute for Education and Social Policy Center for Urban Science and Progress NYU Health Evaluation and Analytics Lab (HEAL)

Examples of projects

• Universal Pre-K Evaluation
• Cross-sector collaboration:
• Education sector researchers /

policy-makers

• Early childhood health experts
• ENT clinician
• Housing and gentrification
• Cross-sector collaboration:
• Furman Center for Real Estate and

Urban Policy

• NYU CUSP machine learning experts
• NYC Housing Authority
• Early childhood health experts

Evaluating the effect of today’s policies Producing evidence for tomorrow’s policies

Today’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,
• r overall utilization.
• These effects are not offset by lower

screening rates in the kindergarten year

Today’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 Today’s policies Tomorrow’s policies OR: 1.3 (p<0.0001) OR: 0.87 (p<0.0001)

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. Today’s policies Tomorrow’s policies OR: 0.72 (p<0.0001)

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. Today’s policies Tomorrow’s policies OR: 1.1 (p=0.04) OR: 1.4 (p<0.0001)

Thank you!

Questions? Feedback? Ideas?

Kacie Dragan, MPH Associate Research Scientist NYU Wagner | Policies for Action Hub kacie.dragan@nyu.edu 212-998-7564 Sherry Glied, PhD Dean & Professor of Public Service NYU Wagner sherry.glied@nyu.edu

https://healthanalyticsatnyu.org/