CONNECTING PEOPLE TO PLACE: IMPROVING COMMUNITIES THROUGH INTEGRATED DATA SYSTEMS Leah Hendey Urban Institute June 21, 2013

Definition of an IDS  Integrate individual-level data from multiple administrative agencies on an ongoing basis  Levels: states, counties, and cities  Purposes: improve case management for individuals, inform advocacy, policymaking, targeting, and program evaluation.  Not IDS: management information system with only program service data  The timing of data integration varies considerably among IDS

Cross-site Project Goals  Enhance access to IDS by NNIP partners to apply IDS data to problems at the neighborhood level  Demonstrate value of adding place info to people data  Create two-way exchange of info between NNIP & IDS and establish relationships  Improve IDS data quality and demand for IDS

Project Criteria  Use data from an established IDS  Must use data from at least two sources of information.  Geographic location or neighborhood needs to be a data element in IDS and in the analysis.  Use local data from an NNIP Partner  Link at address/record level or aggregate data and link at neighborhood level  Inform specific local problem & share results with community.

Project Phasing  Phase I: Planning  Create full proposal for phase II.  Form relationships with IDS agency  Fast-Track Projects  Shorter planning period – begin phase II in  Phase II: Implementation  Data prep & analysis, report and community forum.  Cross-site Analysis & Dissemination

Add a Place-Based Perspective with NNIP Neighborhood Data to IDS Data  Problem:  Multisystem youth account for large share of service use and are spatially concentrated – how does their neighborhood affect system involvement?  IDS Data:  Youth in multiple systems (e.g. juvenile justice, child welfare, homeless, etc.)  NNIP Data:  Community assets, school performance, crime rates  Forum:  CBOs and School officials with facilitated discussion of appropriate interventions to aid these youth

Link Additional Individual-Level NNIP Data to IDS Data  Problem:  What is the effect of early childhood education (ECE), after- school programming, and public assistance use on children’s test scores? How does neighborhood influence the outcomes?  IDS Data:  K-8 education and public assistance records  NNIP Data:  ECE and after-school program enrollment; neighborhood context data  Forum:  Bring together community residents of underserved areas to help advocate for quality ECE and after-school programming.

Link Property-Level NNIP Data to IDS Data  Problem:  How to target limit housing rehabilitation resources in a city?  IDS Data:  Children’s asthma incidence and chronic absenteeism  NNIP Data:  Parcel data on code enforcement, housing inspections and property conditions, age of housing stock  Forum:  Bring agency officials, schools and parents together to increase awareness of consequences of unhealthy housing.

Key Dates & Deadlines  6/14: rSOI and Concept Paper released  Through 6/28: Questions accepted  7/1: Notice of Intent to apply  7/19: Complete SOIs due  8/9: Selected sites announced  9/1: Phase I begins

Questions?  Leah Hendey  