Explicit representation of time and change is an essential feature for building medical decision support systems. In this paper, we propose to use one of the well-known general theories of time and change, namely the Event Calculus [Ko86], to represent temporal aspects in intelligent medical monitoring systems. In particular, we explore the application of CEC [Ch96a] (an efficient implementation of the Event Calculus) to the management of mechanical ventilation, using it to interpret change in data over time, assess patient status and its evolution, and choose the proper respiratory therapy. First, we present the prototype we have built, which has been extensively tested on patient's data reflecting several real clinical situations. Then, we provide a thorough evaluation of the obtained results, pointing out both strengths and weaknesses of adopting the Event Calculus as a temporal reasoning formalism in patient monitoring. We also identify a number of extensions which can be extremely useful in order to ease the scaling up of the possible medical applications of the approach.