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Evaluating Child Welfare Policies with Decision-Analytic Simulation Models

Abstract  

The objective was to demonstrate decision-analytic modeling in support of Child Welfare policymakers considering implementing
evidence-based interventions. Outcomes included permanency (e.g., adoptions) and stability (e.g., foster placement changes).
Analyses of a randomized trial of KEEP—a foster parenting intervention—and NSCAW-1 estimated placement change rates and KEEP’s
effects. A microsimulation model generalized these findings to other Child Welfare systems. The model projected that KEEP
could increase permanency and stability, identifying strategies targeting higher-risk children and geographical regions that
achieve benefits efficiently. Decision-analytic models enable planners to gauge the value of potential implementations.

  • Content Type Journal Article
  • Category Original Paper
  • Pages 1-12
  • DOI 10.1007/s10488-011-0370-z
  • Authors
    • Jeremy D. Goldhaber-Fiebert, Stanford Health Policy, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019, USA
    • Stephanie L. Bailey, Stanford Health Policy, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019, USA
    • Michael S. Hurlburt, School of Social Work, University of Southern California, Los Angeles, CA, USA
    • Jinjin Zhang, Child and Adolescent Services Research Center, Rady Children’s Hospital, San Diego, CA, USA
    • Lonnie R. Snowden, School of Public Health, University of California Berkeley, Berkeley, CA, USA
    • Fred Wulczyn, Chapin Hall, University of Chicago, Chicago, IL, USA
    • John Landsverk, Child and Adolescent Services Research Center, Rady Children’s Hospital, San Diego, CA, USA
    • Sarah M. Horwitz, Stanford Health Policy, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019, USA