Session: Leveraging Administrative Data to Advance Prevention Science: Opportunities, Challenges, and Future Directions (Society for Prevention Research 27th Annual Meeting)

Big data present a rich source of information for prevention researchers. A distinct type of big data is administrative data collected routinely by government entities and other organizations primarily for administrative purposes. The use of administrative data is not common in prevention science even though this type of data can be a valuable source of information on a wide range of prevention-related topics, from epidemiology and etiology to implementation and dissemination of prevention programs. The focus of the proposed symposium is integrating administrative (i.e. big) data into prevention research, and presenters will discuss various challenges and opportunities presented by both quantitative and qualitative administrative data. The proposed presentations and discussion will be instructive to other researchers using or considering the use of administrative data.

First, “Using administrative data to identify risk and protective factors of adverse youth outcomes: Lessons learned in the statewide implementation of the Communities That Care prevention system in Colorado” will describe the challenges associated with using administrative data for statewide planning and implementation of community-based prevention programs. Along with discussing specific challenges such as obtaining appropriate data, understating the data, and using data to inform decisions, the presenter will also focus on lessons learned during the process.

Second, “Documenting and learning from years of technical assistance to community coalitions and evidence-based programs” will describe the process and challenges of using qualitative administrative data to understand the type and nature of technical assistance (TA) received by prevention program providers in Pennsylvania. Results from the study indicate that six unique strategies were used by TA providers across nine different evidence-based prevention programs. Furthermore, the use of specific TA strategies seems to be associated with some programs more than others.

Third, “Explaining item bias in a student risk and needs assessment using school and community data” will demonstrate a novel method of combining administrative data from Washington State and Georgia with local assessment data to better understand item bias in student assessments. The presenters use contextual variables such as school climate rating, and school SES from state-gathered administrative data to explain sources of Differential item functioning (DIF) in Washington Assessment of Risk and Needs of Students (WARNS).

Finally, the discussant will draw upon the presentations as well as her own expertise in using administrative data to identify common themes across presentations to aid the discussion on leveraging administrative data to advance prevention science.