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The context for child care and early education (CCEE) changed rapidly in March 2020 as the global pandemic caused the closure of child care programs and schools, widespread job loss, and negative impacts on the broader economy and family life. Black and Latino families and families with lower income experienced disproportionately negative effects of the COVID-19 pandemic as a result of structural racism and a history of inequitable systems. Many of the negative impacts of the pandemic have directly impacted families' access to high-quality CCEE. As leaders in CCEE consider the implications of COVID-19 for children, families, policies, and programs, a research, evaluation, and data agenda that identifies key questions, research methods, and data needs will be a critical tool. This research, evaluation, and data agenda can (1) alert decision makers to racial and economic inequities in outcomes and promote tracking of key equity indicators, (2) encourage the development of new projects and data initiatives, (3) support the synthesis of information across projects, (4) identify key topics for consideration that may be otherwise overlooked, and (5) promote the application of knowledge to planning and development. The goal of this report is to get input on high priority questions that can inform the field's understanding of the pandemic's impact on the CCEE landscape, including children, families, CCEE programs, the CCEE workforce, and the broader system of agencies, local organizations, and institutes of higher education that support CCEE. The purpose of this work is to develop and revise a research, evaluation, and data agenda that can be used by a wide range of stakeholders (state administrators, policymakers, advocates, funders, etc.) to prioritize research questions that need to be addressed and identify potential data sources to answer these questions. [This report was produced through the Child Care and Early Education Policy Research and Analysis (CCEEPRA) project.]

Home visiting is an important component of the early childhood (EC) landscape. However, states often fail to prioritize home visiting data when developing their early childhood integrated data systems (ECIDS). Home visiting represents a range of services, models, and programs, each with different data requirements, so integrating the data can be challenging. Often, home visiting data is disconnected across different models, as well as from other EC data. To address this challenge to data integration, states can take an incremental approach, integrating one aspect of home visiting data at a time, rather than tackling it all at once. The advantages to taking an incremental approach when integrating home visiting data with other EC data include the following: (1) The process of integrating home visiting data into an ECIDS can be managed more easily when it focuses on one piece at a time, such as a specific model or geographic area; (2) States can treat the incremental integration as a pilot phase, learn from any challenges or policy barriers that arise, and apply that knowledge when scaling up to integrate other home visiting data; and (3) Incremental integration allows states to achieve small wins and demonstrate success on data integration. By showing why integrating home visiting data with other EC data is important and worth the investment of time and resources, states can build buy-in from stakeholders. The purpose of this resource is to provide states with examples of various ways to integrate their home visiting data into their ECIDS over time. This resource will highlight five examples of how states can approach this incremental integration of home visiting data.

Evidence-based home visiting programs exist in over half of the counties in the United States. Because home visiting programs aim to improve the health, education, and life circumstances of pregnant mothers and their children, they are a critical piece of the early childhood landscape. However, the data collected about these programs are siloed, making it difficult for policymakers to answer questions about programs' short- and long-term benefits. Data within and across home visiting models are fragmented because each program uses different methods for storing and reporting outcomes. To address this problem, state leaders, with input from early childhood stakeholders, are developing integrated longitudinal data systems to connect data from home visiting and other early childhood programs, which will lead to a better understanding of the collective impact of these investments. The purpose of this resource is to provide examples of policy questions that state leaders can answer when home visiting data are combined with other early childhood data. These sample questions are organized according to the type of integration of home visiting data needed to answer them. Depending on the policy question(s) to be answered, home visiting data can be integrated in one of three ways: (1) Across home visiting models; (2) With data from other early childhood services; and (3) With longitudinal data, to examine impact on both short- and long-term child outcomes. The sample questions highlighted in this resource are intended to help spark conversations with stakeholders and inform planning efforts to integrate early childhood integrated data, inclusive of home visiting data at the state level.