Measuring Quality Across Three Child Care Quality Rating and Improvement Systems: Findings from Secondary Analyses

Publication Date: August 15, 2011
Current as of:

Introduction

States and communities have adopted Quality Rating and Improvements Systems (QRIS) as a tool to promote, measure, and monitor the quality of early child care programs. The primary goal of a QRIS is to improve quality across a range of child care programs, with the intent of providing positive experiences for all children. The fundamental design decision then is to define and measure quality.

States and localities have used the information and knowledge that is available from research, program administrator’s experiences, and key stakeholders to design systems they hope are valid and meaningful in defining quality for providers, parents, and children alike. At this time, information about the components to include in a QRIS, in what combination, and at what cut-points per level is lacking. In an environment in which adoption, implementation, and refinement of QRIS are moving quickly but the research base to inform decision-making is slim, the Office of Planning, Research, and Evaluation (OPRE), within the Administration for Children and Families, initiated the Child Care Quality Rating Systems (QRS) Assessment project.

This report, produced as part of the QRS Assessment, presents findings from an exploratory analysis of administrative data from three QRIS, which examines the prevalence of quality components across providers and how they function in relation to observed quality. As QRIS enters its second decade, it is clear there has been a growing sophistication in data collection, providing opportunities for in-depth analysis of distinctive QRIS as well as cross-QRIS analysis. This analysis is developmental in nature; the findings are tenable within the limitations and scope, but should be interpreted with caution and are not confirmatory. The larger contribution of this work ties back to the intent of the Assessment project as a whole—to contribute to and build avenues for future analysis that can support a growing body of research that will inform decision making.