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Balancing need and risk, supply and demand: Developing a tool to prioritize naloxone distribution
Claire A Wood1, Lauren Green1, Anna La Manna1
1Missouri Institute of Mental Health, University of Missouri-St. Louis, St Louis, MO, USA.
A new data-driven tool, the Naloxone Request Form (NRF) and algorithm, helps prioritize opioid overdose antidote (naloxone) distribution to those most at risk. This method is more effective than
Area of Science:
- Public Health
- Emergency Medicine
- Data Science in Healthcare
Background:
- National opioid overdose deaths are increasing.
- Demand for naloxone, an opioid overdose antidote, exceeds supply.
- Prioritization tools are needed for effective naloxone distribution.
Purpose of the Study:
- To develop a data-driven tool for prioritizing naloxone distribution.
- To create a standardized Naloxone Request Form (NRF) and prioritization algorithm.
- To improve the efficiency of distributing limited naloxone supplies.
Main Methods:
- Developed a standardized Naloxone Request Form (NRF).
- Created a weighted prioritization algorithm for naloxone distribution.
- Compared historical distribution with algorithm-generated priority quintiles.
Main Results:
- The NRF and algorithm successfully prioritized agencies by potential impact.
- Naloxone was distributed more to higher-priority agencies.
- The algorithm revealed limitations of the 'first come, first served' distribution method.
Conclusions:
- The developed tool provides a foundation for prospective, data-driven naloxone distribution.
- The tool is flexible and adaptable for various programs and locations.
- Ensures limited naloxone supplies have the greatest impact on overdose prevention.
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