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Data-driven decision-making (DDDM) in public child welfare (PCW) has become increasingly important with the passage of the Family First Prevention Services Act (FFPSA), making PCW agencies across the U.S. examine their various programs to ensure that they meet the service requirements of FFPSA. Family Preservation (FP) is an important program that is offered by PCW agencies nationwide, yet little is known about how programs like FP can implement DDDM to examine outcomes to improve practice. This study describes how one of the largest PCW agencies nationwide adopted DDDM in their FP program and presents preliminary findings along with lessons learned as part of the process to meet FFPSA requirements. For example, FP established a baseline recurrence rate using the standard federal definition of the recurrence of maltreatment adapted for FP; this rate was 6.6% for families receiving FP in the target county compared to 8.4% for families not receiving FP services. Subsequent case reviews revealed issues related to engagement, family expectations, and termination codes, which led to standardized definitions and practice changes. Several lessons learned are provided as part of the incorporation of DDDM in FP as well as implications for practice and research.

Incorporating data-driven decision making in family preservation: an examination of recurrence rates, case reviews, and lessons learned