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This book explores the use of integrated administrative data to understand and address the significant public health problem of child maltreatment. It examines the use of linked, or integrated, administrative data to increase understanding of population-level needs and to inform decision-making efforts within the child welfare system and across other public systems. The book details the technological innovations that have allowed for the accumulation and centralization of large datasets critical to identifying risks of child maltreatment and its negative consequences and to target community and system responses more accurately to address these challenges. Leading experts from the fields of child maltreatment, child welfare, and human services research share their insights and experiences at the forefront of this critical research area and how it is shaping understanding of identification, intervention, and policy affecting children and families. Key areas of coverageinclude:
Examines the landscape for using integrated datasets to inform child welfare system efforts Explores use of integrated data to detect, prevent, and respond to child maltreatment Highlights multisystem use to conduct predictive analytics, risk monitoring,
Auteur
Christian M. Connell, Ph.D., is an Associate Professor of Human Development and Family Studies at the Pennsylvania State University. Dr. Connell is director of the Child Maltreatment Solutions Network, a unit of the university's Social Science Research Institute that engages in novel, interdisciplinary, and translational research to prevent, detect, and treat child abuse and neglect; provides educational programming in child maltreatment and advocacy at the undergraduate, graduate, and post-graduate levels; and serves as the university clearinghouse for child maltreatment information, awareness, and communications. His research focuses on individual, family, and system-level outcomes of youth who have been maltreated or involved in the child welfare and other child-serving systems, as well as the effectiveness of community-based interventions to reduce adverse outcomes associated with maltreatment and trauma. Dr. Connell's research has been funded by the National Institutes of Health, the Children's Bureau of the Administration for Children and Families, and the National Child Traumatic Stress Network of the Substance Abuse and Mental Health Services Administration, and through state and local contracts.
D. Max Crowley, Ph.D. is Professor of Human Development, Family Studies, and Public Policy and holds the Edna Bennett Pierce Endowed Professorship at Pennsylvania State University. Dr. Crowley directs the Evidence-to-Impact Collaborative, including its infrastructures the Administrative Data Accelerator, the Research Translation Platform, the Design4Impact Incubator, and the Social Investment Optimizer. Dr. Crowley's research focuses on methods for conducting economic evaluations of health and social programs and developing strategies to improve the use of evidence in policy and budget making. Dr. Crowley is the Principal Investigator on grants from the National Institute on Drug Abuse, National Institute of ChildHealth and Human Development as well as the Annie E. Casey, Laura & John Arnold, Robert Wood Johnson, William T. Grant, and Doris Duke Charitable Foundations. Dr. Crowley has received national awards recognizing his scholarship from the National Institutes of Health, National Bureau of Economic Research, Society for Prevention Research, Association for Public Policy & Management, Research Society on Alcoholism, and National Prevention Science Coalition.
Contenu
Chapter 1. Introduction and Volume Overview.- Chapter 2. Leveraging Administrative Data to Understand the Scope and Impact of Maltreatment.- Chapter 3. Using Harmonized Multisystem Data to Examine Experiences of Child Welfare-Involved Children, Youth, and Families.- Chapter 4. Innovative Uses for Geographical and Spatial Data Using Linked Child Welfare Datasets.- Chapter 5. How the NCANDS and AFCARS Can Provide Insight into Linked Administrative Data.- Chapter 6. Challenges in the Use of Predictive Risk Modeling and Predictive Analytics in Child Welfare.- Chapter 7. Integrating Data to Foster Child Safety and Well-Being.- Chapter 8. Housing Insecurity in Child Welfare: Designing Fair and Efficient Data-Driven Responses.- Chapter 9. Integrating Child Welfare and Medicaid Data to Identify and Predict Superutilization of Services for Youth in Foster Care.- Chapter 10. Strengths and Limitations of Administrative Data to Inform Services and Intervention Research.- Chapter 11. How Integrated Data Helps Identify Impact and Opportunity to Intervene with Children and Families.- Chapter 12. Prospects and Challenges for Big Data, Big Science, and the Evolution of Integrated Administrative Data.- Chapter 13. Conclusion and Panel Discussion.