Administrative Data and Child Welfare Research

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Ace Scale
administrative data
Administrative Data Analysis
Adverse Childhood Experiences Questionnaire
Antipsychotic Users
Bethany R. Lee
Big Data
Bjorn Gustafsson
Bo Vinnerljung
Brett Drake
Bridgette Lery
Category=JBF
Category=JHBC
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Catherine Laurier
Catherine Pineau-Villeneuve
child maltreatment analysis
child welfare
Child Welfare Administrative Data
child welfare research
Cm Group
Cox Proportional Hazards Assumption
Cps Intervention
data analytics
data linking
data mining
data mining techniques
Entered Foster Care
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eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
foster care
foster care outcomes
Fostering Connections Act
Institutional Review Board
interagency collaboration
IPV
IPV Exposure
IPV Group
Jeffrey L. Edleson
Jennifer L. Hook
Jennifer L. Romich
Jennifer M. Haight
Jill L. Farrell
JiYoung Kang
JoAnn S. Lee
Journal of Public Child Welfare
Kristine N. Piescher
Labor Market Attachment
Lily Alpert
linked administrative datasets for policy research
Lisa R. Kiesel
Marie-Noele Royer
Math Scale Scores
Maureen Marcenko
Melissa Jonson-Reid
Ming-Hui Tai
Mixed MANOVA
Out-of Home Care
Placement Transition
predictive modelling
social services data
Sonia Helie
Strong Labor Market Attachment
Subsequent IPV
Susan dosReis
TANF Benefit
TANF Receipt
TANF Roll
Terry V. Shaw
Torun Osterberg
Washington State Institutional Review Board

Product details

  • ISBN 9781138295926
  • Weight: 430g
  • Dimensions: 174 x 246mm
  • Publication Date: 05 Dec 2017
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Every day, social service agencies collect millions of pieces of data about the children and families they serve. Agencies depend on this data to inform decision-making by personnel throughout the organization and to provide meaningful research and evaluation on program effectiveness and outcomes. As capacity for collecting and utilizing data has increased so has the recognition that this data can and should be used more broadly. Further, it should include not just single-system data, but data across different human service agencies.

Administrative/big data systems can be powerful tools in increasing the efficiency and effectiveness of public child welfare services. Understanding, harnessing, and using big data holds tremendous promise in creating transformative change in the social services. Data analytics and data mining can lead to a better understanding of what services work for specific populations (targeting and predictive modelling), provide a more nuanced understanding of service outcomes for the workforce and major stakeholders (transparency), and facilitate collaboration across existing service delivery silos to reduce duplication of services and enhance consumer access to services (efficiency). This book was originally published as a special issue of the Journal of Public Child Welfare.

Terry V. Shaw is Director of the Ruth H. Young Center for Families and Children and an Associate Professor in the School of Social Work at the University of Maryland, USA. His research is focused on the experience of children in the child serving systems and how to leverage existing administrative data systems to improve policy and practice. Bethany R. Lee is the Associate Dean for Research and an Associate Professor in the School of Social Work at the University of Maryland, USA. Her research is centered on services for youth involved in the public systems of child welfare and/or mental health. Jill L. Farrell is a Research Assistant Professor in the School of Social Work at the University of Maryland, USA. Her research centers on evidence-based practices and the use of data to inform policy, with particular regard to juvenile justice.