It was a Monday night, the busiest time in the ED. The ED charge nurse received an alert on her Vocera smartphone app. The alert was from Qventus, which predicts operational bottlenecks and recommends course corrections. The alert was telling the charge nurse that the ED was going to have a surge of patients in two hours. Qventus predicted this with machine learning based on the current census in the ED, historical admit and discharge times, the practice patterns of the clinicians currently working in the ED, and the current queue and expected turnaround times for diagnostic tests.