Big Data in State and Community Substance Use Prevention Decision Making: Epidemiological Outcomes Workgroups

For over 10 year the Substance Abuse and Mental Health Services Administration has encouraged their state, tribal, jurisdiction, and community grantees to prioritize data driven prevention efforts through the establishment of epidemiological outcomes workgroups (EOWs). EOWs provide data to guide funding decisions, needs assessments, strategy selection, and evaluation as well as to help grantees stay responsive to emerging trends and health disparities. This roundtable brings together agency staff and analysts from Georgia, Virginia, and the District of Columbia to discuss how EOWs extract and integrate data from various complex state- and community-level administrative and surveillance data sets; establish data repositories for sharing data; and disseminate the data to policymakers and community practitioners through highlight reports, social indicator studies, dashboards, and other products.

The discussants will describe some of the challenges of this work including the difficulties sustaining collaborations with key stakeholders across state agencies to access large data sets such as those related to drug and alcohol arrests; motor vehicle crashes; poisoning calls; behavioral and mental health treatment; prescription drug monitoring programs; emergency department admissions; overdoses and other substance-related mortality; and school health surveys. EOW work also requires collaborators with skills in data maintenance, statistical analysis, computer science, and informatics as well as experts in data visualization and the presentation of findings in plain language. These skills are all required to develop products that community members find easy to understand and use in their work. The discussants will share some of the products developed by their EOWs to meet community needs.

Overall, EOWs show how collaborative partnerships can turn ‘Big Data’ into accessible data for communities. We expect the roundtable to produce dialogue on such questions as: 1) What can EOWs teach prevention scientists about how policymakers and practitioners use Big Data to inform intervention selection and implementation? and 2) What new partnerships might prevention researchers form with federal, state, and local agencies to incorporate new data sources and new ways of looking at data into the EOWs?