Written to describe the various data tools and approaches Family to Family states and communities used for their self-evaluation, the document provides an overview of four data tools child welfare agencies can use to guide planning, policy and services. These include longitudinal analysis, population profiles, caseload projections and desktop mapping. States were just starting to develop their Statewide Automated Child Welfare Information Systems when the document was written; thus, some states may have incorporated some or all of these tools into their systems since this document’s original publication. The document also includes recommendations, suggestions of how to start and examples of lessons learned.
Self-evaluation teams in Family to Family locations included program staff, data managers, and data analysts. These teams were more successful when program staff led the teams and agency leaders participated in the work of the teams.
Use Unique Identifiers
Each child should have a unique identifier within the data system. This allows tracking a child’s entrances and exits within the child welfare system over time as well as determining other services the child might have received. It also provides an unduplicated count of children receiving child welfare services.
Statements & Quotations
In summary, perhaps the most important lesson learned was that even though the transition to using longitudinal data files is somewhat difficult and requires that a state or county devote precious staff time and resources to this exercise, the repercussions of not using longitudinal data are far-reaching.
In order for data to be suitable for use in self-evaluation, one has to understand the environment from which they are extracted….The most frequent impediments to using data for evaluation include unavailability of information because it is not collected, inaccuracies and unreliability of the data, inconsistency in definition, uncertainty regarding meaning and various other factors related to the compatibility of data and their quality.
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