Javascript must be enabled to continue!
Abstract 9873: Comparing Base Locations for Drone-Delivered Defibrillators
View through CrossRef
Introduction:
Drone-delivered defibrillators may improve response for out-of-hospital cardiac arrest (OHCA). Prior studies have assumed that drones may be stationed at any police, fire, or paramedic station; however, cross-service implementation may not be logistically feasible. We sought to compare estimated response times by drone base location type.
Methods:
We included OHCAs (Jan. 2014 to Dec. 2020) in southern Vancouver Island, British Columbia, Canada where OHCA response includes fire and paramedic services. We created four models with candidate drone base locations at: police stations, fire stations, paramedic stations, and on a grid with 1 km sides as an optimistic model. We used mathematical optimization to select 1-5 drone bases for each model. Assuming a drone system had been in place during the study period and accounting for drone availability, we estimated 9-1-1 call-to-defibrillator intervals (measured to either drone, paramedic, or fire arrival) and calculated the proportion of OHCAs where a drone would arrive prior to fire and paramedic for each model. Median response times were compared to historical response using one-sided sign tests.
Results:
We included 1,610 OHCAs with a median historical response time of 6.4 mins (IQR 5.0-8.6). We identified 21 police stations, 59 fire stations, 21 paramedic stations, and 7,008 grid locations in the study area. Median 9-1-1 call-to-defibrillator intervals ranged from 4.3-5.3 mins for police, 4.3-5.3 mins for fire, 4.5-5.4 mins for paramedic, and 4.2-5.4 mins for grid locations (all P<0.001). Drones arrived prior to fire and paramedics in 36.6-65.4% of cases for police, 38.1-66.2% for fire, 37.3-63.2% for paramedic, and 35.7-66.8% for grid locations.
Conclusion:
Locating drone bases at different types of emergency service stations significantly decreases 9-1-1 call-to-defibrillator intervals, while resulting in similar response intervals to those achieved using optimistic grid-optimal locations.
Ovid Technologies (Wolters Kluwer Health)
Title: Abstract 9873: Comparing Base Locations for Drone-Delivered Defibrillators
Description:
Introduction:
Drone-delivered defibrillators may improve response for out-of-hospital cardiac arrest (OHCA).
Prior studies have assumed that drones may be stationed at any police, fire, or paramedic station; however, cross-service implementation may not be logistically feasible.
We sought to compare estimated response times by drone base location type.
Methods:
We included OHCAs (Jan.
2014 to Dec.
2020) in southern Vancouver Island, British Columbia, Canada where OHCA response includes fire and paramedic services.
We created four models with candidate drone base locations at: police stations, fire stations, paramedic stations, and on a grid with 1 km sides as an optimistic model.
We used mathematical optimization to select 1-5 drone bases for each model.
Assuming a drone system had been in place during the study period and accounting for drone availability, we estimated 9-1-1 call-to-defibrillator intervals (measured to either drone, paramedic, or fire arrival) and calculated the proportion of OHCAs where a drone would arrive prior to fire and paramedic for each model.
Median response times were compared to historical response using one-sided sign tests.
Results:
We included 1,610 OHCAs with a median historical response time of 6.
4 mins (IQR 5.
0-8.
6).
We identified 21 police stations, 59 fire stations, 21 paramedic stations, and 7,008 grid locations in the study area.
Median 9-1-1 call-to-defibrillator intervals ranged from 4.
3-5.
3 mins for police, 4.
3-5.
3 mins for fire, 4.
5-5.
4 mins for paramedic, and 4.
2-5.
4 mins for grid locations (all P<0.
001).
Drones arrived prior to fire and paramedics in 36.
6-65.
4% of cases for police, 38.
1-66.
2% for fire, 37.
3-63.
2% for paramedic, and 35.
7-66.
8% for grid locations.
Conclusion:
Locating drone bases at different types of emergency service stations significantly decreases 9-1-1 call-to-defibrillator intervals, while resulting in similar response intervals to those achieved using optimistic grid-optimal locations.
Related Results
PEMANFAATAN DRONE UNTUK MONITORING AKURASI PERENCANAAN TAMBANG BATUBARA TERBUKA
PEMANFAATAN DRONE UNTUK MONITORING AKURASI PERENCANAAN TAMBANG BATUBARA TERBUKA
ABSTRAKĀ Pertambangan batubara di Indonesia telah mengalami pasang surut harga yang sangat fluktuatif sejak 2012. Hal tersebut berdampak langsung kepada para pelaku usaha pertambang...
AKUISISI DATA SURVEI PARAMETER TINGGI POHON DAN LUASAN VEGETASI MANGROVE MENGGUNAKAN WAHANA UDARA NIR-AWAK (DRONE)
AKUISISI DATA SURVEI PARAMETER TINGGI POHON DAN LUASAN VEGETASI MANGROVE MENGGUNAKAN WAHANA UDARA NIR-AWAK (DRONE)
The image of an unmanned vehicle (Drone) is an image/photo obtained from an aerial survey using an unmanned aerial vehicle above the earth's surface at a low altitude and the resol...
Quality of Life and Psychological Status of Patients With Implantable Cardioverter Defibrillators
Quality of Life and Psychological Status of Patients With Implantable Cardioverter Defibrillators
⢠Background Implantable cardioverter defibrillators reduce mortality in patients at high risk for sudden cardiac death and in patients with heart failure. Patients with defibrilla...
PELATIHAN DAN PEMANFAATAN DRONE UNTUK PEMETAAN LAHAN PERTANIAN DALAM MENDUKUNG SMART FARMING PADA KELOMPOK TANI
PELATIHAN DAN PEMANFAATAN DRONE UNTUK PEMETAAN LAHAN PERTANIAN DALAM MENDUKUNG SMART FARMING PADA KELOMPOK TANI
Abstrak: Fokus tim PPK Ormawa pada kegiatan pengabdian di Desa Ciasihan yaitu menghasilkan data spasial lahan pertanian dan peningkatan kapasitas kelompok tani dalam pemahaman fung...
An Energy-Efficient Logistic Drone Routing Method considering Dynamic Drone Speed and Payload
An Energy-Efficient Logistic Drone Routing Method considering Dynamic Drone Speed and Payload
Unmanned aerial vehicle (UAV), or drone is recognized for its potential to improve efficiency and address last-mile delivery issues. As a result, there has been a lot of activity i...
A Comprehensive Collection and Analysis Model for the Drone Forensics Field
A Comprehensive Collection and Analysis Model for the Drone Forensics Field
Unmanned aerial vehicles (UAVs) are adaptable and rapid mobile boards that can be applied to several purposes, especially in smart cities. These involve traffic observation, enviro...
Weight Reduction of C-Drone Body Structure
Weight Reduction of C-Drone Body Structure
UTHM has successfully developed a high payload cargo drone, namely the C-Drone, with a weight of over 400 kg. Although this drone has successfully passed the hovering test, it is b...
Eyes on Air
Eyes on Air
Abstract
We at ADNOC Logistics & Services have identified the need for a Fully Integrated Inspection and Monitoring Solution to meet our operational, safety and ...

