Expansion of quality preschool in Philadelphia: Leveraging an evidence-based, integrated data system to provide actionable intelligence for policy and program planning

Abstract

To address the national priority for school readiness, there is a growing body of research investigating early care and education (ECE) deserts. This research identifies geographies within jurisdictions where there are high demands for and low supplies of ECE programs. The current study used a new approach to investigate preschool deserts in Philadelphia that addressed shortcomings in existing research. This approach used evidence-based measures of supply and demand across neighborhoods to identify and respond to preschool deserts in real time. A population-based data model of early childhood risks derived from a disciplined, local Integrated Data System (IDS) was used to calculate demand and triage it by multiple evidence-based early risk experiences. Actual counts of the number of slots in preschool centers with an evidence-based high-quality rating were used to calculate supply. High-quality, preschool deserts were defined as the neighborhoods with the greatest number of children with multiple evidence-based early risks and the lowest number of high-quality preschool slots relative to the city average. Results showed that about 3 out of 10 preschool children in Philadelphia live in a high-quality preschool desert. A report on how policymakers used the findings to increase high-quality preschool capacity was provided. Findings demonstrate how this evidence-based approach to the investigation of preschool deserts can increase the possibility of providing relevant, actionable intelligence to local policymakers and public service providers.