BACKGROUND: Out-of-hospital cardiac arrest (OOHCA) is prevalent in the United States. Each year between 180,000 and 400,000 people die due to cardiac arrest. The automated external defibrillator (AED) has greatly enhanced survival rates for OOHCA. However, one of the important components of successful cardiac arrest treatment is emergency medical services (EMS) response time (i.e., the time from EMS "wheels rolling" until arrival at the OOHCA scene). Unmanned Aerial Vehicles (UAV) have regularly been used for remote sensing and aerial imagery collection, but there are new opportunities to use drones for medical emergencies. OBJECTIVE: The purpose of this study is to develop a geographic approach to the placement of a network of medical drones, equipped with an automated external defibrillator, designed to minimize travel time to victims of out-of-hospital cardiac arrest. Our goal was to have one drone on scene within one minute for at least 90% of demand for AED shock therapy, while minimizing implementation costs. METHODS: In our study, the current estimated travel times were evaluated in Salt Lake County using geographical information systems (GIS) and compared to the estimated travel times of a network of AED enabled medical drones. We employed a location model, the Maximum Coverage Location Problem (MCLP), to determine the best configuration of drones to increase service coverage within one minute. RESULTS: We found that, using traditional vehicles, only 4.3% of the demand can be reached (travel time) within one minute utilizing current EMS agency locations, while 96.4% of demand can be reached within five minutes using current EMS vehicles and facility locations. Analyses show that using existing EMS stations to launch drones resulted in 80.1% of cardiac arrest demand being reached within one minute Allowing new sites to launch drones resulted in 90.3% of demand being reached within one minute. Finally, using existing EMS and new sites resulted in 90.3% of demand being reached while greatly reducing estimated overall costs. CONCLUSION: Although there are still many factors to consider, drone networks show potential to greatly reduce life-saving equipment travel times for victims of cardiac arrest.
BACKGROUND: Out-of-hospital cardiac arrest (OOHCA) is prevalent in the United States. Each year between 180,000 and 400,000 people die due to cardiac arrest. The automated external defibrillator (AED) has greatly enhanced survival rates for OOHCA. However, one of the important components of successful cardiac arrest treatment is emergency medical services (EMS) response time (i.e., the time from EMS "wheels rolling" until arrival at the OOHCA scene). Unmanned Aerial Vehicles (UAV) have regularly been used for remote sensing and aerial imagery collection, but there are new opportunities to use drones for medical emergencies. OBJECTIVE: The purpose of this study is to develop a geographic approach to the placement of a network of medical drones, equipped with an automated external defibrillator, designed to minimize travel time to victims of out-of-hospital cardiac arrest. Our goal was to have one drone on scene within one minute for at least 90% of demand for AED shock therapy, while minimizing implementation costs. METHODS: In our study, the current estimated travel times were evaluated in Salt Lake County using geographical information systems (GIS) and compared to the estimated travel times of a network of AED enabled medical drones. We employed a location model, the Maximum Coverage Location Problem (MCLP), to determine the best configuration of drones to increase service coverage within one minute. RESULTS: We found that, using traditional vehicles, only 4.3% of the demand can be reached (travel time) within one minute utilizing current EMS agency locations, while 96.4% of demand can be reached within five minutes using current EMS vehicles and facility locations. Analyses show that using existing EMS stations to launch drones resulted in 80.1% of cardiac arrest demand being reached within one minute Allowing new sites to launch drones resulted in 90.3% of demand being reached within one minute. Finally, using existing EMS and new sites resulted in 90.3% of demand being reached while greatly reducing estimated overall costs. CONCLUSION: Although there are still many factors to consider, drone networks show potential to greatly reduce life-saving equipment travel times for victims of cardiac arrest.
Entities:
Keywords:
Out-of-hospital cardiac arrest; emergency medical service; cardiac arrest; geographic information systems; maximum coverage location problem
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