Reducing the number of children in foster care requires actionable policy and practical solutions. By identifying subpopulations of children and youth who use intensive or frequent services, we might shed light on those who lack the right types of support at critical junctures, live in overly restrictive...
- Mixed methods evaluation
- Quantitative analysis with administrative data
- Child welfare programs and policies
- Workforce development programs and policies
- Performance measurement
- Predictive analytics
- Family Support
- Human Services
- Child Welfare
Elizabeth Weigensberg is an expert on designing and conducting evaluations, using both qualitative and quantitative methods, and developing and estimating performance measures for public child welfare agencies and workforce development programs. Her expertise includes linking and analyzing complex administrative data from state and local public agencies and providing technical assistance to facilitate the development and use of data to inform policy and practice.
Weigensberg helps lead Mathematica’s work with developing data, advanced analytic, and program improvement solutions for state and local child welfare agencies, including helping agencies develop and implement predictive risk modeling. She has also contributed to numerous research projects on child welfare and workforce development. She currently serves as project director for the State Child Abuse and Neglect (SCAN) Policies Database, which is a new data resource documenting states’ definitions and policies related to the incidence of child abuse and neglect for the U.S. Department of Health and Human Services, Administration for Children and Families, Office of Planning, Research, and Evaluation and the Children’s Bureau. She has also recently led several child welfare studies for the U.S. Department of Health and Human Services, Assistant Secretary for Planning and Evaluation, including studies on the relationship between foster care and substance use in local communities, the variability in states’ use of exceptions to timeline requirements for termination of parental rights, and how key child welfare measures have changed during the pandemic. She also serves in key roles for several other federal child welfare projects, including the national cross-site evaluation for the Regional Partnership Grants and the evaluation of the Center for Native Child and Family Resilience. She also recently directed a project with Casey Family Programs that involved linking child welfare administrative data with Medicaid data and applying advanced analytics to identify types of super-utilization of services and predictors of placement instability for children in foster care.
Weigensberg came to Mathematica in 2015 from Chapin Hall at the University of Chicago, where she was a senior researcher and principal investigator on numerous projects. She previously worked as a research instructor at the University of North Carolina at Chapel Hill and as an analyst at the U.S. Government Accountability Office. She holds a Ph.D. in social work from the University of North Carolina at Chapel Hill and an M.S. in social work from Columbia University.
Superutilization of Child Welfare and Other Services
Design Options for Understanding Child Maltreatment Incidence
This project will result in a set of rigorous and creative design options to address critical research questions and improve ongoing surveillance of child abuse and neglect as well as related risk factors.
Mathematica at the 2019 ISM Annual Conference
Join Mathematica at the 2019 ISM Annual Conference in Milwaukee, Wisconsin, as Elizabeth Weigensberg, Mathematica’s state and local child welfare lead, and Matthew Stagner, vice president and director of human services, team up to share their expertise on how being data driven can improve outcomes for...
Mathematica's Elizabeth Weigensberg Wins the Louis Brownlow Award
Elizabeth Weigensberg and her coauthors on a recent article in <em>Public Administration Review</em> are this year’s recipients of the Louis Brownlow Award. The Brownlow Award is presented to the authors of the best article by a practitioner or for a practitioner audience for the volume year.