TDAI wins NSF Big Data Spoke award to combat opioid epidemic in rural communities

TDAI has received an NSF Big Data Spoke award to help small and rural communities in the Midwest harness big data to combat the opioid epidemic.

In partnership with Nationwide Children’s Hospital, Wright State University and the University of Chicago, the project, entitled “Community-Driven Data Engineering for Substance Abuse Prevention in the Rural Midwest,” will create an openly accessible tool called OpenOD to help agencies and organizations addressing the epidemic link and analyze data from myriad sources.

TDAI Interim Executive Director Raghu Machiraju will lead the collaborative project along with co-PIs Anish AroraAyaz Hyder, Courtney Lynch and Pamela Salsberry. Ohio State’s $651,000 portion of the $900,000 grant will last three years.

Communities of every type face barriers to getting crucial data into the hands of individuals on the frontlines, including data siloes across multiple organizations such as law enforcement, public health departments and health care providers; the stigma of drug abuse and privacy and security concerns that deter information sharing; and disparate methods for collecting and managing data.

Communities of every type face barriers to getting crucial data into the hands of individuals on the frontlines. The OpenOD tool will be designed specifically for use in rural communities, where “dead zones” in cellular service and a lack of communication infrastructure can compound these challenges significantly.

OpenOD will be designed specifically for care providers’ use in rural communities such as Ohio’s Appalachian counties, where “dead zones” in cellular service and a lack of communication infrastructure can compound these challenges significantly. The new, cloud-amenable framework will include Internet connectivity with both mobile and non-mobile capabilities as well as a data commons and user-friendly data analytics and visualization tools.

Leveraging input from community organizations will be key to ensuring that OpenOD fulfills end users’ needs. Researchers will partner with local stakeholders to understand existing strengths and gaps in local cyber infrastructure, the local landscape of available data, and the types of training modules and courses that local educators and other partners can utilize within their communities to combat opioid addiction long-term.

The resulting tools could help first responders and health care providers obtain critical up-to-date information, or help individuals and families dealing with addiction to locate resources such as a treatment center.

“To be a translational success, the tools we make must effectively address stakeholders’ needs as defined by those stakeholders, not by us,” says Machiraju. “We will be building and validating the tools with them and for them.”

Ultimately, these new links among data sources will empower communities to save and improve lives with accelerated responses and improved preventive strategies around opioid use, deliver valuable data sets to researchers and educators in addition to care providers, and increase big data-related literacy and engagement among rural populations that are underrepresented in STEM fields.

Down the road, the OpenOD model can also be scaled and applied to other societal problems such as infant mortality, crime and natural disasters that require multi-pronged strategies and many different community groups to address. Those, too, would be based on input from policymakers, care providers, first-responders and others.

“We learn from our community partners what they feel will be most efficient and beneficial at the local level,” Machiraju says. “Creating solutions to the challenges they are facing every day is how we as researchers can make the greatest contribution toward improving the human condition.”

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