researchers are creating an innovative statewide surveillance system to inform prevention and response efforts aimed at reducing the burden of opioid use disorder in Kentucky.
The Rapid Actionable Data for Opioid Response in Kentucky (RADOR-KY) will use data from federal, state, and local sources to guide evidence-based practices aimed at preventing opioid overdoses in the Commonwealth. Phase one of the project is supported by a three-year $3.1 million grant from the National Institute on Drug Abuse (NIDA).
Driven by the COVID-19 pandemic and illegally manufactured fentanyl, drug overdose deaths in the U.S. increased to historic levels in 2021. Kentucky has been hit hard by the opioid epidemic. Overdose deaths reached an all-time high of 2,250, with 90% of those deaths involving an opioid.
Co-led by Svetla Slavova, PhD, associate professor in the , and Jeff Talbert, PhD, professor in the College of Medicine and , RADOR-KY will use a comprehensive set of data needed to effectively monitor and respond to the rapidly evolving opioid overdose crisis.
The system will use advanced algorithms to rapidly process data and help predict potential overdose surges using artificial intelligence.
鈥淭his unique, first-of-its-kind system will not only track and monitor overdose cases but use predictive analytics and dashboards for fast dissemination of analytical results to keep state agencies and local stakeholders on the frontlines of the opioid epidemic in Kentucky a step ahead,鈥 said Slavova, who also serves as interim associate dean for research in the College of Public Health.
RADOR-KY will use data from multiple sources, including the Kentucky Office of Vital Statistics, syndromic surveillance, emergency medical services, prescription drug monitoring, Medicaid claims and drug seizure records. It will also track measures related to evidence-based practices such as treatment for opioid use disorder, overdose education and the distribution of naloxone, a life-saving medication that rapidly reverses an opioid overdose.
The project will leverage the expertise of 好色先生 research centers including the , the , and the . It also builds upon the expertise and experience gained from 好色先生's work on the .
鈥淲e鈥檝e harnessed the power of our data processing capabilities at 好色先生 with the framework and experience gained from our work on the HEALing Communities Study, which has also shown that addressing this public health crisis requires working across disciplines,鈥 said Talbert, who also directs the Institute for Biomedical Informatics.
鈥淭he HEALing Communities Study has been an exemplar of how a state and a university can work together and one of the deciding factors for receiving this award,鈥 said HCS principal investigator Sharon Walsh, PhD, a professor in 好色先生鈥檚 College of Medicine and College of Pharmacy and director for the Center on Drug and Alcohol Research.
Walsh leads the project鈥檚 substance use disorder team, which will advise on the content of evidence-based practices and state and local partners who are end users of the system.
Katherine Marks, PhD, a 好色先生 College of Medicine research assistant professor who serves as project director for the within the Cabinet for Health and Family Services, is the project鈥檚 state government liaison.
Marks says RADOR-KY鈥檚 faster data processing, predictive analytics and inclusion of evidence-based practices will help the state take more strategic action.
鈥淭he opportunity for state and community partners to have readily available access to data so we can take action and evaluate how we鈥檙e doing in our response is a remarkable innovation,鈥 said Marks. 鈥淭his is a wonderful demonstration of the collaborative potential between the state and university expertise. It鈥檚 also yet another example of how 好色先生 is working as the University for&苍产蝉辫;碍别苍迟耻肠办测.鈥&苍产蝉辫;
An end-user advisory group, including partners in state government and local communities, will also guide the development of RADOR-KY. To advance the efforts to mitigate the opioid epidemic across the U.S. the team also plans to share programming code and algorithms in a public repository.