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Preventing Overdose Using Information and Data From the Environment
Sponsor: Brown University
Summary
The objectives of this project are to leverage surveillance data to predict future overdose outbreaks, and to evaluate the impact of a randomized, statewide, community-level intervention trial to target overdose prevention programs to neighborhoods at highest risk of future overdose deaths. This study develops and tests an opioid overdose forecasting tool, which will allow other states to identify and deploy interventions to communities at highest risk of opioid-related death. The findings from this study have the potential to significantly improve the allocation of resources to curb the opioid overdose epidemic in the United States.
Official title: Reducing Drug-Related Mortality Using Predictive Analytics: A Randomized, Statewide, Community Intervention Trial
Key Details
Gender
All
Age Range
Any - Any
Study Type
INTERVENTIONAL
Enrollment
39
Start Date
2021-11-15
Completion Date
2024-08-15
Last Updated
2026-04-09
Healthy Volunteers
No
Conditions
Interventions
PROVIDENT
Each of the state's 39 municipalities will be randomised to the intervention (PROVIDENT) or comparator condition. An interactive, web-based tool will be developed to visualize the PROVIDENT model predictions. Municipalities assigned to the treatment arm will receive neighborhood risk predictions from the PROVIDENT model, and state agencies and community-based organizations will direct resources to neighborhoods identified as high risk. Municipalities assigned to the control arm will continue to receive surveillance information and overdose prevention resources, but they will not receive neighborhood risk predictions from this study.
Locations (1)
Brown University School of Public Health
Providence, Rhode Island, United States