Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services

Key Points Question Can a machine learning model help medical dispatchers improve recognition of out-of-hospital cardiac arrest? Findings In this randomized clinical trial of 5242 emergency calls, a machine learning model listening to calls could alert the medical dispatchers in cases of suspected cardiac arrest. There was no significant improvement in recognition of out-of-hospital cardiac arrest during calls on which the model alerted dispatchers vs those on which it did not; however, the machine learning model had higher sensitivity that dispatchers alone. Meaning These findings suggest that while a machine learning model recognized a significantly greater number of out-of-hospital cardiac arrests than dispatchers alone, this did not translate into improved cardiac arrest recognition by dispatchers.