This brief explores how residential segregation shapes inequitable access to Head Start programs at the neighborhood level, by race/ethnicity, for two time periods (2014 and 2019). National and state level patterns are discussed.

An inventory of the elements and accessibility of early education and care data systems maintained by New York State and New York City agencies in the areas of: (1) program/provider supply; (2) enrollment, participant demographics, and demand; (3) early childhood workforce; (4) program quality; (5) outcomes for children and families; and (6) costs and financing; with recommendations for steps toward the development of integrated comprehensive early childhood data systems

This presentation details possible administrative datasets that can be used to perform a cost analysis, cost-effectiveness, cost-savings analysis, or benefit-cost analysis with an example.

This case study highlights AVANCE Houston, a Head Start program, that partnered with the Houston Independent School District to understand children's literacy and math skills in early elementary school and how they compared with other children from low-income families.

This research brief describes how integrated administrative data from the City of Philadelphia's CARES data system were used to inform the expansion of pre-K services in the City of Philadelphia. It provides a model for other states and municipalities seeking to use integrated data to inform policymaking, particularly for young children and their families.

This companion guide describes the methods used to extract information from the Florida Department of Education database for data on school leaders and transform it into an understandable structure for use. The report focuses on methods of data cleaning, merging, and analysis in order to help those interested in analyzing similar databases in other states or contexts.

This state spotlight focuses on recent work in Minnesota, where state agency leaders and the Children's Defense Fund-Minnesota are working together to use and share early care and education data.

This session by the Center for IDEA Early Childhood Data Systems (DaSy) shares Minnesota's journey using state data to answer critical questions, details steps for analyzing state-level data, and demonstrates the capabilities of CEDS myConnect to map elements for data analysis.

This video highlights the benefits of Minnesota's Early Childhood Longitudinal Data System, according to staff at local and state organizations.

This report assesses trends in proximity to child care as one component of a child's ability to attend a high-quality early childhood program. To describe this geographic proximity, in 2016, the Center for American Progress introduced a working definition of child care deserts—areas with an insufficient supply of licensed child care.

To build useful early childhood integrated data systems, states must start with a vision for how they would like the system to be used and, more specifically, a list of essential questions to be answered using the data. This brief offers examples of key early childhood policy questions and outlines why those questions are needed, how to create them, and who should be involved in developing questions that will guide ECIDSs. (author abstract)

This report highlights estimates by the Center for American Progress that the country could lose half of its licensed child care capacity without government intervention. The analysis provides a tool (found at www.childcaredeserts.org) that illustrates the state of child care supply before the novel coronavirus pandemic to show how child care closures will disproportionately affect some communities.

This brief shows how disaggregated data are key to identifying opportunity gaps and confronting barriers to student success. It also provides information for state leaders as they make sure that families have the data they need to ensure that their students get a high-quality, equitable education.

This report highlights current practices and proposes how states can better collect and use early childhood education (ECE) data in three areas: (1) tracking dual language learner (DLL) enrollment, (2) evaluating program quality, and (3) assessing kindergarten readiness.

This resource first highlights three uses of spatial analysis that are common in ECE research: (1) categorizing geographical areas, (2) creating variables using spatial information, and (3) analyzing spatial patterns and associations. This is not an exhaustive list of all that can be done with spatial analysis; rather, it is a summary of common approaches in ECE research that are most suitable for ECE researchers new to spatial analysis. (author abstract)

This presentation uses the Illinois-New York child care research partnership as an example to explain how to use administrative data to answer policy-relevant research questions through linking administrative data across states.

This brief describes the methodology to measure child care supply using distance-based measures, based on a 2019 paper by Davis, Lee, and Sojourner. (The 2019 paper, "Family-Centered Measures of Access to Early Childhood Education," is also included among this list of resources).

This paper assesses the infant and toddler child care capacity of communities across New York State over 9 years (2007-2016), using data from the NY State Education Department, the NYS Office of Children and Family Services, and the National Center for Education Statistics definitions of locale. Using negative binomial regression, we see overall stability in capacity for infant and toddler child care but important variation by demographic factors and geography.

As stakeholders of SLDSs become more adept at using data in their work and for decisionmaking, SLDS programs in many states are expanding and evaluating their use of data visualization to continue to meet their users’ demands for information. This spotlight examines the data visualization tools and processes used by SLDS programs in Michigan, Maryland, and Hawai‘i. (author abstract)

This study proposes new family-centered measures of access to early care and education (ECE) services with respect to quantity, cost, and quality and uses them to assess disparities in access across locations and socio-demographic groups in Minnesota. These distance-based measures use available geographic data to account for the fact that families can cross arbitrary administrative boundaries and thus better reflect the real experiences of families. Combining synthetic family locations simulated from Census demographic and geographic data and information on ECE provider locations, we calculate travel time between the locations of families with young children and ECE providers to measure families' access to providers of different types.

This report provides an overview of a demonstration project conducted by Rhode Island KIDS COUNT that sought to use integrated data from early care and education programs to look at a population of children with high needs (young children who were maltreated in 2015) and their participation in high-quality early learning programs. (author abstract)

This report uses interviews from state leaders across the US and reviewed laws, documents, and policies to evaluate how administrative data are being used in all 50 states.

This webinar supports Child Care and Development Fund (CCDF) Lead Agency staff and partners in mapping access to care across their state or other region. The webinar covers (1) a review of basic mapping terms, concepts, and resources; (2) a presentation from a research partner in Pennsylvania on mapping child care deserts; and (3) a presentation from CCDF Lead Agency staff in Wisconsin on mapping trends in provider locations across the state.

For SLDS data analyses to be useful for leaders and policymakers, they must be designed soundly and presented in ways that align with users’ information needs. This document offers tips for planning, conducting, and sharing education data analyses that can inform policy decisions and allow stakeholders to take action. (author abstract)

This brief describes how Minnesota created the MN Kids Explorer data tool and a data story to help engage busy stakeholders in their statewide longitudinal data system (SLDS).

This report summarizes five years of geographic and spatial research on access to federally subsidized child care for low-income working families in Massachusetts.

This webinar shares lessons learned and recommendations from a new report released by the Early Childhood Data Collaborative. The report highlights examples of integrated data systems (IDS) that were used to produce policy research reports addressing key child advocacy issues.

To study the quality of care provided in the area and ultimately improving the well-being of children and families in South Carolina by linking different sources of child care administrative data to create analytic data cubes to allow examination of quality of care provided to children and factors contributing to it; Can use administrative data for potential impact on well-informed decision making and policy change to improve children and families' well-being

This study focuses on preschools' collection and use of administrative data on dosage, classroom quality, and early learning outcomes.

This report describes how the Minnesota Head Start community set out to describe the developmental progress of four-year-olds enrolled in Head Start across Minnesota using their research-based child assessment data. The exercise of aggregating data from diverse, locally-controlled Head Start programs offers many important lessons about building a state early childhood data system and establishing data variables that offer meaningful insights into the complex interactions that impact children's early developmental progress. It also contributes to the discussion about how children enrolled in Head Start make progress in essential developmental domains.

This report summarizes findings from analyses of Minnesota's Early Childhood Longitudinal Data System (ECLDS) data on access to early childhood programs for children of color and low-income children enrolled in the Minnesota Family Investment Program (MFIP) and food programs.

This webinar is designed to support Child Care and Development Fund (CCDF) Lead Agency staff and their partners in using existing administrative data. The webinar focuses on how to use data to address state legislators’, agency heads’, local child care providers’, and other stakeholders’ policy questions. The webinar covers a dozen policy and operational questions CCDF lead agencies have addressed by analyzing existing data. It provides tips for using administrative data. CCDF Lead Agency staff from Georgia and Massachusetts describe about how they have used data to answer their agency’s policy and operational questions.

This webinar describes how two states are using their data and reports from their Early Childhood Integrated Data Systems (ECIDS) to inform state policies and programs.

This research was conducted in 2009-2010 to provide a comparison of regulated child care in rural and urban counties in Pennsylvania. Specifically, the research explored the types of licensed child care available, child care quality, and the types of care most often used by families who receive subsidies in rural and urban counties.

This report provides considerations for using aggregate administrative data to analyze policy-relevant questions when it may be too difficult or costly to obtain individual-level administrative data.

The report examines the consequences of underreporting transfer programs in household survey data for low-income populations. The report also focuses on the Current Population Survey (CPS), the source of official poverty and inequality statistics. Administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State are linked to the CPS at the individual level.

This brief provides a step-by-step process for developing or improving a research agenda that the SLDS can support.

This report explores the feasibility of using electronic health record (EHR) and other electronic health data for research on small populations.

This guide will help CCDF/licensing Administrators assess current licensing data systems and identify needed changes. It explores new uses for licensing data, examines some strategies for dealing with common challenges, and provides additional resources for review and reference.

The Center for IDEA Early Childhood Data Systems, the DaSy Center, was funded by the Office of Special Education Programs (OSEP) to provide technical assistance (TA) to states to support them in developing or enhancing Part C and Part B Section 619 (Part B 619) data systems. TA also will assist Part C and Part B 619 state agencies in participating in the development of integrated early childhood data systems and longitudinal data systems in their states. To inform the DaSy Center's work, the Center collected information about the current status of Part C and Part B 619 state data systems, priorities for improvement, and areas where the states would like TA. State Part C and Part B 619 coordinators, their respective data managers, and other state staff completed an online survey over the summer of 2013. Responses were obtained from 94% of the 50 states, DC, and Puerto Rico for Part C and from 96% for Part B 619. This report summarizes what was learned about the current status of Part C and Part B 619 data systems and where states are in moving to improve their data systems. (author abstract)

This brief describes key steps and considerations for communicating and carrying out a research agenda that a state longitudinal data system can support. The brief also discusses how to ensure that the research agenda is sustainable over time. The guidance in this brief is intended for states that have already developed a research agenda but have not taken steps to implement it.

A study of the characteristics of state and regional registries of early childhood and school-age practitioners and trainers, based on survey responses from 31 registries

The INQUIRE Data Toolkit was designed to provide tools to support effective data collection and the use of data to answer important policy and reporting questions through the use of common data elements.

The report describes the key practical and political considerations of transforming the information in these programmatic records into research-ready databases; identifies the strengths and weaknesses of administrative data, relative to that gathered in national surveys, for use in descriptive and evaluative research and in accountability-based monitoring of program performance; describes examples of several states' efforts to develop an ongoing capacity to use administrative data for both programmatic and policy evaluations; and makes initial recommendations that will improve the quality and usefulness of administrative data for policymakers and program administrators.

This issue brief (1) summarizes the uses and limitations of postsecondary data in raw form, (2) describes three sophisticated ways that K-12 officials can use these data to inform K-12 policy and practice, and (3) discusses the importance of dissemination.

This report details MIHOPE-Strong Start's process of acquiring administrative vital records and Medicaid data from 20 states and more than 40 state agencies. The study relies on administrative data to measure infant and maternal health, health care use, and cost outcomes. Policymakers have increasingly encouraged greater access to and use of administrative data to produce timely, rigorous, and lower-cost evaluations of health and social programs, since these records may be less costly and more accurate than information collected directly from families. The MIHOPE-Strong Start experience sheds light on the process of acquiring permission to access such data.

In this paper we assess the strengths and weaknesses of using survey or administrative data to measure the employment and income of low-income populations. We review a number of studies, most of which have been conducted in the past 10-15 years,(3) that assess the comparability of income and employment measures derived from surveys and administrative records.

The Child Care Data Tracker (Tracker), available to tribes and territories, is a comprehensive case management tool designed to support the collection, management, and utilization of the case-level information needed for the generation of the required ACF-700 and ACF-801 reports.

Data play an integral role in pay for success (PFS) projects. Knowing the kinds of data needed for a successful project, how to collect them, and how they should be used may seem straightforward. But the complexity of early childhood outcome measures and data systems can create challenges.

The Child Care Data Viewer, available to CCDF State and Territory grantees, is a software tool to help improve the quality of ACF-801 data and enhance its utilization.

This document was developed to help technical assistance (TA) providers and state staff define and limit the scope of data analysis for program improvement efforts, including the State Systemic Improvement Plan (SSIP); develop a plan for data analysis; document alternative hypotheses and additional analyses as they are generated; and summarize findings and document results.

The resource can help researchers prepare for issues that may arise when using administrative data in a research project.

The Statewide Longitudinal Data Systems Grant Program offers a variety of support resources.

This is an inventory that leaders can use to determine their teams' proficiency levels with each of the four data activities: prepare, collect, aggregate and analyze, and use and share.

This brief summarizes common themes across two studies of local Head Start programs and a multidisciplinary literature review. Preliminary evidence shows that Head Start programs experience similar challenges and facilitators to data use for continuous quality improvement as those experienced in other fields.

An online series on using data in Head Start and Early Head Start. The module includes an introduction and five interactive activities. Each activity includes scenarios that are based on real-life examples from actual Head Start and Early Head Start programs.

This resource provides a list of tips for building a data culture in Head Start programs.

This report summarizes research on the processes, facilitators, and impediments to data use for continuous quality improvement; develops a conceptual framework representing the elements of data use for continuous quality improvement; provides linkages between the disciplines from which the literature was drawn and the Head Start field; and suggests areas for future research.