Harmonizing data to help identify care improvement targets for children with complex issues such as Autism.

Lack of access to combined mental health, educational and developmental disabilities services data limits our ability to understand how essential services provided by these systems can affect outcomes for children. While limited research to date suggests that services in one sector may affect utilization in another, identifying cross system patterns of care that lead to better outcomes for children with Autism Spectrum Disorder (ASD) is even more complex due to differences in classification processes and eligibility definitions. In particular, thus far neither researchers nor community agencies have leveraged educational outcomes, which are key for all children, including those with ASD, to help understand how we can improve coordinated care for children with complex mental health concerns.

DataLab is partnering with Dr. Sarah Dufek and her research team on an informatics challenge to examine the feasibility of systematically accessing, harmonizing and analyzing data from multiple systems of care in order to gain a better understanding of the unmet needs of people with ASD and their families, and to measure progress or impact at the population level.

Evaluating the potential and limitations of data aggregation across sectors (including California Department of Health Care Services, California Department of Developmental Services, and the California Department of Education) will support enumeration of children and youth with ASD and lead to a better understanding of the relationships between service use and individual outcomes. If data aggregation across datasets from these various departments is feasible, this research will support one of the first studies to examine cross-system patterns of care and associations with outcomes in children and youth with ASD. Data from this project have the potential to identify specific mechanisms that affect outcomes for children and youth with ASD across multiple systems of care. These mechanisms can then be examined and tested in future experimental studies with translation into actionable items for research, services, policy and methods generalizable to other childhood mental health disorders that cross systems and geographic locations.


DataLab: Carl Stahmer (technical lead), Pamela Reynolds, Naomi Kalman

MIND: Sarah Dufek (PhD), postdoctoral researcher Maya Mathies (PhD, MSW), and PhD student Sarah Vejnoska (MA)