Time-to-scene for opioid overdoses: are unmanned aerial drones faster than traditional first responders in an urban environment?

Autor: Tukel, Connor Andrew, Tukel, Matthew Ryan, Weinbaum, Robert Jacob, Mika, Valerie H., Levy, Phillip D.
Předmět:
Zdroj: Practical Neurology; Oct2020, Vol. 20 Issue 5, p204-208, 5p
Abstrakt: Introduction Opioid overdoses claim tens of thousands of lives every year. Many of these deaths might be prevented if overdose-reversal medications such as naloxone are administered in a timely manner. Drones may help overcome barriers to timely arrival on scene for opioid overdoses. This study analyses the time required for a drone carrying naloxone to traverse various distances, simulating the response time for a drone to the scene of an opioid overdose. For comparison, we used the time required for ambulances to traverse similar distances while responding to the scene of actual or suspected opioid overdoses. Methods Fifty flight trials, using a modified Dà-Jiāng Innovations (DJI) 'Inspire 2' drone, were conducted across seven distances, and the travel time for the drone was then compared with historical response time data from 200 actual or suspected opioid overdose cases that occurred within Detroit, Michigan. Results We determined with 95% certainty that drone arrival times were discernibly quicker than ambulance arrival times at all distances where sufficient data were available to perform statistical comparisons including 0.5 km, 1.0 km, 1.5 km, 2.0 km and 3.0 km. Conclusion We have shown that a drone is capable of travelling several ranges of straightline (ie, 'as the crow flies') distance faster than an ambulance. Further exploration into the use of drones to deliver life-saving therapies in urban and rural settings is warranted. Headto- head prospective trials that consider the practical challenges of medical drone delivery are needed to better understand the viability of incorporating this technology into existing emergency response infrastructure. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index