Introduction
Research Questions
- How and to what extent do child welfare agencies and their partners collect and use data to advance equity?
- What emerging practices across the data life cycle support child welfare agencies in their efforts to advance equity?
- What factors support the implementation and use of emerging data practices intended to advance equity?
- What challenges and barriers may impede the implementation and use of emerging data practices to advance equity?
- What opportunities exist at agency and system levels to support child welfare agencies in using data to advance equity?
This case study highlights the New York State Office of Children and Family Services’ (OCFS) use of two data practices - a disproportionality minority report packet and blind removal meetings - to reduce racial disproportionality and disparities in their child welfare system. This case study describes how the state and three select New York counties implement these data practices, the motivation and context for their equity work, facilitators and barriers to implementing the data practices, and opportunities for furthering the data practices.
The following research questions helped guide the case studies, and do not include all the research questions for the overall project:
Purpose
This case study is part of a series of case studies that explore data practices child welfare agencies and their partners use to promote equity for families served by the child welfare system. The case studies were conducted as part of the Child Welfare Study to Enhance Equity with Data (CW-SEED) project and explored: how data are used to understand and address equity in service delivery and child and family outcomes; barriers or problematic practices; and child welfare agencies’ and their partners’ efforts to reduce barriers to equity across the continuum of child welfare services. Information in this case study may be useful for child welfare agency staff and their partners who aim to use data to support their equity efforts.
Key Findings and Highlights
Data practices:
- Disproportionality Minority Report packet: OCFS’ Office of Research, Evaluation, and Performance Analytics develops the disproportionality minority report packet for counties on an annual basis. It includes a data dashboard allowing counties to view data at the state and county level by race and ethnicity and shows five-year trends along different points of the child welfare services continuum. The packet also includes a separate file that shows county disparity rate comparisons and a document describing the contents of the packet. Counties can use this information to inform equity conversations and service delivery.
- Blind removal policy: To decrease racial disparities within the child welfare system, OCFS issued an administrative directive in 2020, requiring all counties to develop and implement blind removal meeting processes, and included information about who should be involved in the meetings. Blind removal meetings intentionally remove identifying information (data elements) such as names, gender, race, ethnicity, and ZIP code. By removing personal and demographic information about a family, the practice aims to reduce bias, so removal decisions are focused on safety, risk, and family strength considerations.
Implementation supports: The resources and trainings provided to county leadership and staff supported implementation of both data practices. Key implementation facilitators for the disproportionality minority report packet were OCFS’ focus on equity and having designated staff that continuously adapt the packet to make it user-friendly. Buy-in from county leadership and having broad and flexible guidance for implementing blind removals were key implementation facilitators for the blind removal policy.
Implementation challenges: Barriers for implementing the disproportionality minority report packet include: the timing of analysis and dissemination of the packet, need for additional and consistent guidance, difficulty locating data of interest, and a change in the data the used for comparing families involved with child welfare to the overall county population. Staff beliefs about their own biases posed as a barrier for implementing the blind removal policy.
Opportunities: OCFS hopes to continue improving data practices to enhance equity and reduce racial disparity and disproportionality. Some suggested strategies to do this include offering training to mandated reporters, using the dashboard created for tracking Family First Prevention Services Act implementation to understand equity in prevention services, and including people with lived experience in decision making.
Methods
Site identification. The CW-SEED project team gathered recommendations for potential case study sites from several sources, including: the project’s environmental scan of equity-focused data practices, project team members, the Administration for Children and Families’ regional program managers, and the CW-SEED expert group. The project team held preliminary information calls with child welfare agency staff in each site.
Data sources and data collection methods. The project team requested and reviewed documents related to the data practices and tailored semi-structured interview protocols to guide the site visit data collection. The primary data sources for each case study include information from the jurisdiction selection process, jurisdiction-specific documents, notes from interviews, focus group discussions, and observations.
Data analysis and case study findings. The project team developed a codebook and conducted qualitative analysis by coding the data sources using NVivo software. They exported codes and used them to identify key findings.
Citation
Lewis, G., Spielfogel, J., Miller, M. Weigensberg, E., & Bess, R. (2024). Case Study for the Child Welfare Study to Enhance Equity with Data (CW-SEED): New York Office of Children and Family Services, OPRE Report #. Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services.
Glossary
- Data:
- Information collected about individuals and families that come into contact with the child welfare system. Data include information about age, gender identity, disability, race/ ethnicity, and descriptive information such as how a household is structured or the events that led to a child’s placement in out-of-home care. In this study, we are particularly interested in data or information that can help assess and address equity—or inequities—in the child welfare system at the local level.
- Data practices:
- Activities that involve data, which includes data planning, collection, access, and analysis; use of statistical tools and algorithms; and data reporting and dissemination.
- Data life cycle:
- Five sequential stages that depict how data move through the earliest stages of data planning to eventual reporting and dissemination.
- Disparity:
- The unequal outcomes of one group compared with outcomes for another group (Child Welfare Information Gateway 2021).
- Disproportionality:
- The underrepresentation or overrepresentation of a particular group when compared with its percentage in the general population (Child Welfare Information Gateway 2021).
- Equity:
- The consistent and systematic fair, just, and impartial treatment of all individuals, including individuals who belong to underserved communities that have been denied such treatment, such as Black, Latino, and Indigenous and Native American persons; Asian Americans and Pacific Islanders and other persons of color; members of religious minorities; LGBTQI+ persons; persons with disabilities; persons who live in rural areas; and persons otherwise adversely affected by persistent poverty or inequality. This definition is consistent with President Biden’s Executive Order 13985, Advancing Racial Equity and Support for Underserved Communities Through the Federal Government (White House 2021).