Child Welfare Data-Mining

Exploring trauma-informed practice in public child welfare through qualitative data-mining of case records

Taylor, S.
Battis, C.
Carnochan, S.
Henry, C.
Balk, M.
Austin, Michael J.
2018

The overwhelming majority of youth in the child welfare system (CWS) have experienced trauma. This qualitative data-mining study of case records explores how trauma manifests in child welfare and how child welfare workers engage youth who have experienced trauma. Case records revealed that youth exhibit many signs and symptoms of complex trauma, however, most did not have a trauma-related mental health diagnosis. The records included examples of how child welfare workers utilized elements of trauma-informed practice.

Using Qualitative Data-Mining for Practice Research in Child Welfare

Henry, C.
McBeath, B.
Austin, M.J.
2017

Qualitative data-mining (QDM), using the narrative data contained in child welfare case records, enables researchers to examine child welfare practice using relatively non-intrusive methods. QDM can increase our understanding of client populations and problems, child welfare worker actions, and case complexity. This paper reports on experiences from the Child Welfare Qualitative DataMining Project; outlines a seven-step guide to QDM methods; and describes how QDM can be used to enhance child welfare practice, research, and education.

Identifying Skillful Practice in Child Welfare Case Record Data Through the Use of Qualitative Data-Mining

Carnochan, S.
Weissinger, E.
Austin, M.J.
2015

This study addresses the need for research that examines child welfare practice. It documents frontline practice as reflected in the case records created by child welfare workers as part of their day-to-day work, and identifies skillful practices in these records. The analysis examines the relationship between child welfare worker practices and short-term client outcomes in cases involving youth in foster care, identifying examples from case record data to enhance our understanding of skillful child welfare practice.

Data Mining in Children and Family Services: The Contra Costa Experience

Winship, K.
Austin, M.J.
2012

Despite access to a comprehensive administrative database that would allow for timely data retrieval and utilization, regular use of data to inform service provision remained infrequent at one children and family services agency. To address this issue, a research and evaluation manager was hired to facilitate regular data use and evidence-informed service provision. This led to a shift in agency culture that moved from viewing data collection as a burden and threat, to now valuing data as a powerful tool for improving programs and outcomes for children and families.

Assessing the potential for qualitative data mining in practice-based child welfare research

Carnochan, S.
Jacobs, L.
Austin, M.J.
2015

The multifaceted, dynamic nature of child welfare interventions and the demand for evidence-informed practice calls for an array of practice-based research tools. This analysis examines the use of qualitative data mining related to narrative case record data to conduct practice-based research in child welfare. It includes a structured literature review, and case study results examining 1) qualitative data mining experiences in child welfare agencies and 2) the utility of case records as data sources.

Child Welfare Data Mining

The Mack Center initiated an innovative qualitative data mining project in partnership with the BASSC child welfare agencies in 2012. Utilizing narrative records contained in the agencies’ automated data systems, Mack Center researchers extract and analyze data to answer a wide array of practice questions. Previous analyses have examined case plan alignment and explored examples of skillful child welfare practice.