Using an automated external defibrillator (AED) to deliver a shock to a cardiac arrest patient before the arrival of emergency medical services (EMS) increases the chance of the patient’s survival. Studies both within the United States and abroad have explored using unmanned aerial systems (UASs, also known as drones) to deliver AEDs to cardiac arrest patients. By exploring similar research and legal restrictions and evaluating historical cardiac arrest data, this thesis examines a UAS solution for suburban and rural areas in which traditional emergency response may be delayed. Ultimately, the thesis seeks to determine if a UAS solution can be deployed in Washington’s Seattle/King County region to reduce morbidity and improve survival rates for patients experiencing out-of-hospital cardiac arrest.
To test this approach, the researcher gathered historical data from the Seattle/King County region on traditional EMS responses for 4,233 cardiac arrest cases that occurred between January 1, 2012, and December 31, 2017. The data evaluated the emergency response from the moment a 9-1-1 call was placed to the moment the emergency responder made contact with the patient to begin resuscitative care.
Models were then constructed and run to evaluate if a UAS could respond to the patient faster than a traditional ground unit. The models were run for four different sets of potential UAS launch points to determine which would provide the best coverage for King County: King County Medic One Medic unit stations, 9-1-1 dispatch centers, hospitals, and private industry locations (commercial package delivery organizations with potential UAS delivery systems). The models evaluated UASs flying at 25 mph (40 km/h), which is what current off-the-shelf technology can offer; 80 mph (129 km/h), which is what current experimental airframes can perform; and 100 mph (161 km/h), which is currently the full speed at which the Federal Aviation Administration allows UASs to operate. The model tests showed that response times can, indeed, be reduced using UASs; response times per test site and UAS speed are shown in Table ES 1.
Table ES 1. UAS Performance and Effect on Cardiac Arrest Cases
|Cardiac Arrest Cases of 4,233||King County Medic Units||Hospitals||Dispatch Centers||Private Industry|
|Median UAS Response Time for Cases Affected (Min:Sec)||11:55||11:48||11:42||11:59|
|Median Reduction in Response Time for Cases Affected||1:31||1:38||1:44||1:27|
|Median UAS Response Time for Cases Affected (Min:Sec)||4:04||4:18||4:10||4:13|
|Median Reduction in Response Time for Cases Affected||1:39||1:25||1:33||1:30|
|Median UAS Response Time for Cases Affected (Min:Sec)||3:22||4:06||4:08||4:12|
|Median Reduction in Response Time for Cases Affected||2:54||1:38||1:40||1:44|
Of the four locations tested, King County Medic One stations would provide the most effective coverage for the suburban and rural areas of King County. If the UASs were placed at these locations, 1,743 of the 4,233 cardiac arrest cases (41 percent) that were researched could have had a median improvement in response time by 1 minute and 31 seconds with a UAS traveling at 25 mph, and 4,198 of 4,233 of the cardiac arrest cases (99 percent) could have had a median time improvement of 2 minutes and 54 seconds with a UAS traveling at 100 mph.
Although this shows significant response time reductions in the rural areas of King County, it is possible that the deployment of UASs with AEDs may have a greater impact in the suburban areas of King County. For a patient in cardiac arrest, the chances of survival decrease cumulatively by about 10 percent for each minute that passes without intervention. A reduction in response time from 6 minutes to 4 minutes could therefore conceivably increase the patient’s chance of survival by 20 percent. However, in a rural setting, the difference between a response time of 18 minutes and 11 minutes might not have any impact on survival.
Because the data and models show that the UAS approach can reduce response time to patients in cardiac arrest, the next step—after addressing the considerations and limitations discussed in this thesis—is to explore the actual implementation process in King County and begin live testing.
 Data obtained from King County Public Health’s Cardiac Arrest Surveillance System, April 1, 2018.
 Monique L. Anderson et al., “Rates of Cardiopulmonary Resuscitation Training in the United States,” JAMA Internal Medicine 174, no. 2 (February 1, 2014): 194, https://doi.org/10.1001/jama internmed.2013.11320.