Using Integrated Data to Design and Support Pay For Success Interventions

• Main Authors: Claudia Coulton, Meghan Salas Atwell, Francisca Richter, Elizabeth Anthony
• Format: Article
• Language: English
• Published: Swansea University 2018-10-01
• Series: International Journal of Population Data Science
• Online Access: https://ijpds.org/article/view/1080

Pay for Success (PFS) interventions are increasingly being implemented in the U.S. and worldwide to assess social programs under a risk-sharing financial agreement between the public and private sectors. They seek to mitigate risk for the public sector and promote wider experimentation of programs to improve social outcomes.  PFS contracts encourage coordination and alignment of goals, outcomes, and metrics across all agents involved - government, service providers, service recipients, funders and investors. Accordingly, these interventions rely heavily on access to high quality data and analysis, making integrated data systems (IDS) valuable assets to support the design, implementation, and evaluation phases of these projects.   The ChildHood Integrated Longitudinal Data (CHILD) System, one of the most comprehensive county-level IDS in the nation, has been used to support and inform two Pay for Success projects in Cuyahoga County (Cleveland). Partnering for Family Success is a county-level intervention in the areas of child welfare and housing instability, now into its fourth year of operation. While the intervention was implemented under a randomized controlled trial, analysis with CHILD proved instrumental to inform the project design and address challenges in program implementation. CHILD has also been used to study the feasibility of PFS as a model to expand high quality preschool, under a grant awarded to eight communities nationally. A case study of both initiatives will be presented, highlighting the role of integrated data in supporting and facilitating PFS design and analysis of outcomes, challenges encountered and lessons learned.