Quantifying randomness of clinician mobility and interaction in emergency department using entropy

Entropy is a fundamental measure of randomness in a time series of data. In this paper, we use entropy to quantify the randomness of events in the workflow in an emergency department (ED). We collect data using Radio Identification (RID) sensor system and compute the entropy of mobility and interaction events generated from behaviors of each tagged clinician. The result shows that the event data bears low entropy values and thus contains underlying regular patterns of interaction and mobility of clinicians.