title: 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.
authors.affiliation: Stanford Health Policy, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019, USA. jeremygf@stanford.edu
authors.forename: Jeremy D
authors.initials: JD
authors.lastname: Goldhaber-Fiebert
authors.forename: Stephanie L
authors.initials: SL
authors.lastname: Bailey
authors.forename: Michael S
authors.initials: MS
authors.lastname: Hurlburt
authors.forename: Jinjin
authors.initials: J
authors.lastname: Zhang
authors.forename: Lonnie R
authors.initials: LR
authors.lastname: Snowden
authors.forename: Fred
authors.initials: F
authors.lastname: Wulczyn
authors.forename: John
authors.initials: J
authors.lastname: Landsverk
authors.forename: Sarah M
authors.initials: SM
authors.lastname: Horwitz
mesh_terms: D000293:Adolescent; D000300:Adoption; D002140:California; D002648:Child; D002669:Child Welfare / Q000706:statistics & numerical data*; D002675:Child, Preschool; D003198:Computer Simulation; D003661:Decision Support Techniques; D055317:Evidence-Based Practice / Q000706:statistics & numerical data; D005581:Foster Home Care / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D011640:Public Policy; D016032:Randomized Controlled Trials as Topic