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Evaluating child welfare policies with decision-analytic simulation models.

Jeremy D Goldhaber-Fiebert1, Stephanie L Bailey, Michael S Hurlburt

  • 1Stanford Health Policy, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019, USA. jeremygf@stanford.edu

Administration and Policy in Mental Health
|August 24, 2011
PubMed
Summary

Decision-analytic modeling can help child welfare policymakers implement evidence-based interventions like KEEP. This approach projects increased permanency and stability for children in foster care, optimizing resource allocation.

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Area of Science:

  • Child Welfare Research
  • Health Services Research
  • Public Policy Analysis

Background:

  • Child welfare systems face challenges in improving permanency and stability for children.
  • Evidence-based interventions require robust evaluation before widespread implementation.
  • Policymakers need effective tools to assess the value of new programs.

Purpose of the Study:

  • To demonstrate decision-analytic modeling for evaluating child welfare interventions.
  • To assess the potential impact of the KEEP foster parenting intervention on child welfare outcomes.
  • To identify efficient strategies for implementing evidence-based interventions.

Main Methods:

  • Utilized a randomized trial of the KEEP intervention and NSCAW-1 data.
  • Developed a microsimulation model to generalize findings across child welfare systems.
  • Estimated rates of foster placement changes and the effects of KEEP.

Main Results:

  • The model projected that KEEP can enhance permanency and stability for children.
  • Identified targeted strategies for higher-risk children and specific regions for efficient benefit.
  • Decision-analytic models provide a framework for assessing implementation value.

Conclusions:

  • Decision-analytic modeling is a valuable tool for child welfare policy.
  • The KEEP intervention shows potential for improving child welfare outcomes.
  • Strategic implementation can maximize the efficiency and impact of interventions.