Abstract 148: A Machine Learning-based Dispatch Rule for Drone-delivered Defibrillators

Abstract

Introduction: Drone-delivered defibrillators may reduce response time for out-of-hospital cardiac arrest (OHCA). However, an optimal dispatch rule is not yet known. Methods: We identified all suspected OHCAs in Peel Region, Ontario, Canada from Jan. 2014 to Dec. 2019. We trained a neural network model to predict emergency medical services (EMS) response times using OHCA location, distance from responding ambulance, day of week and time of day. Instead of least-squares loss, our model optimized a loss function that penalized weighted errors in the dispatch decision (type I/II error). Assuming drones were deployed from three bases in the region, we calculated drone response time to each suspected OHCA using real drone specifications. Our dispatch rule dispatched a drone when its calculated response time was shorter than the predicted EMS response time. Response time was calculated as the minimum of the drone and EMS response times. The performance of our dispatch rule was compared on out-of-sample OHCAs using 5-fold cross validation to the baseline cases of (1) no drones, and (2) drone dispatch to every suspected OHCA. Statistical analysis on the median response times was performed using a right-tailed sign test. Results: We identified 4774 suspected OHCAs with a median historical EMS response time of 6.0 minutes. Using our dispatch rule, median response time was significantly shorter at 3.9 minutes (P<0.001). Drones were dispatched to 3803 cases (79.7%) and of those, drone response was faster than EMS in 3076 cases (80.9%). When the drone was not dispatched, it would have been slower than EMS in 856 cases (88.1%). Sending a drone to every suspected OHCA resulted in an identical median response time of 3.9 minutes (P<0.001), with drones arriving before EMS in 3191 cases (66.8%). Conclusion: A machine learning-based dispatch rule can achieve similar response times as a policy that dispatches a drone to all suspected OHCAs, while dispatching drones less frequently.