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April 2024Vol. 25, No. 3Harnessing Technology to Improve Data Quality and Protect Children

Written by Children's Bureau Division of State Systems staff

Today’s technology is rapidly changing how vulnerable children and families can be protected. April’s National Child Abuse Prevention Month (NCAPM) provides an excellent opportunity to increase awareness for safeguarding children from harm by leveraging technology that can enhance the quality of child welfare data and improve family outcomes.

Telling the Story Through Data

In a Comprehensive Child Welfare Information System (CCWIS), the Administration for Children and Families (ACF) defines the primary characteristics of quality data as completeness, timeliness, and accuracy with a goal to describe each child and their circumstances and to meet federal and state or tribal reporting requirements. High-quality data allow the child welfare system to "tell the story" of a child and their family.

Establishing the Importance of Quality Data

Ensuring data quality in CCWISs is a foundation block for successful child abuse prevention initiatives. Situations such as missed interventions, delayed responses, and undesirable outcomes can stem from incorrect or missing information. However, by incorporating technology into the child welfare process, agencies can lay a solid groundwork for more successful outcomes and improved results.

Making a Difference

Access to quality data is imperative for child welfare activities. Technologies and automations that support data quality help agencies with activities such as the following:

  • Risk assessments: Quality data can provide a holistic view of attributes such as caregiver history, consistency of care, environmental elements, and past allegations of domestic violence. Knowing these risks up front helps caseworkers make more informed decisions for the affected children and their families.
  • Tracking outcomes: Having better data allows agencies to identify gaps and strengths in their child protection system and monitor their program’s overall effectiveness. Using these individualized findings, agencies can address business needs and concerns as well as consider future system enhancements.
  • Case management: Analytical data-management tools can streamline the workflow process and reduce administrative loads. As a result, this workflow efficiency can allow agency staff more time to directly support children and families in other ways.
  • Resource collaboration: Sharing up-to-date case information with the appropriate resources, both internal and external to the agency, ensures a better coordinated response for all involved participants.
  • Providing metrics: Analytical tools can provide your agency with valuable data to produce better metrics for state and federal reporting requirements.

Protecting Children Using Data-Driven Tools

While ACF does not endorse specific products, there are technologies available that can support child abuse prevention efforts through enhanced CCWIS functionality, such as the following:

  • Address verification: Validating addresses supports prompt engagement and accurate service delivery, and it can uncover patterns or connections that warrant further scrutiny.
  • Fuzzy logic for duplicates: "Fuzzy logic" tackles common data entry errors like misspellings or variations in names, helping to uncover potential duplicates and streamline records.
  • Artificial intelligence or machine learning: These technologies offer potential for predictive risk modeling and pattern recognition, as well as enhancing proactive intervention strategies.
  • Robust search tools: Tools with advanced algorithms enable effective searches across databases, facilitating the identification of possible connections or relevant historical reports.

Looking Ahead

While technology holds much promise for providing agencies with quality data, the responsible adoption of these tools is also vital for protecting children and families. Analytical tools should provide data that is ethical, transparent, privacy-protective, and implemented with safeguards to minimize bias. Additionally, human judgment remains essential when interpreting the data to provide interventions.

For More Information

For more information or to discuss tools mentioned in this article, please contact your state or tribe’s assigned federal analyst in the Children’s Bureau’s Division of State Systems.

 

Additional Resources

Center for State Child Welfare Data, Chapin Hall at the University of Chicago

Children's Bureau. (2018). Technical bulletin #6: CCWIS data quality plan. U.S. Department of Health and Human Services, Administration for Children and Families. https://www.acf.hhs.gov/cb/training-technical-assistance/ccwis-technical-bulletin-6 

 

 

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