• January-February 2016
  • Vol. 16, No. 10

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Data-Driven Diligent Recruitment Webinar

Most child welfare systems collect data on children in foster care but lack data on how prospective families navigate the process from recruitment to licensure or approval and beyond. In February 2015, the National Resource Center for Diligent Recruitment (NRCDR) at AdoptUSKids held a free 1-hour webinar exploring ways child welfare systems can develop their capacity to efficiently use data to inform their recruitment, development, and support of foster, adoptive, and kinship families to meet the needs of children and youth in care.

The webinar, intended for child welfare program and data staff, offered an overview of using data, and presenters discussed the important resource family data elements that systems can collect and analyze to understand the effectiveness of their recruitment, development, and support efforts. Approaches for gathering these data were also shared.

The importance of and strategies for partnering between child welfare and data staff to strengthen a system's use of data were discussed. The webinar highlighted an example from Arizona, which is demonstrating the benefits of a strong partnership between child welfare and data staff to inform data-driven recruitment efforts. It also referenced and provided links to a number of diligent recruitment tools and resources, such as NRCDR's Diligent Recruitment Navigator, which helps guide States, Tribes, and territories through their own process of developing a comprehensive diligent recruitment program.

Presenters included an NRCDR consultant and data expert, as well as recruitment and geographic information systems staff with the highlighted Arizona project. For more information and to view the webinar, “Data-Driven Diligent Recruitment: Partnering and Prioritizing to Strengthen Your System's Use of Data,” visit the NRCDR website for links to the PowerPoint and Flash files and the NRCDR YouTube channel at http://www.nrcdr.org/news-and-e-notes/story?k=NRCDR-Webinar.

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