To derive meaningful conclusions in a changing medical setting, medical decision-support systems must represent and reason about the temporal nature of the clinical environments they attempt to model. Because all difficult medical problems have significant temporal features, designers of medical decision support systems must recognize the unique problems caused by representing and reasoning with temporal concepts. This report has three goals: 1) to describe a set of fundamental issues in creating and reasoning with computer models of a changing clinical environment, 2) to present a taxonomy for characterizing the temporal characteristics of computer models of temporal reasoning, and 3) to use this taxonomy to compare the models of time used in some implemented medical decision-support programs. From this examination, it is argued that computational models of time based on a single uniform representational or inferential method are limited by the expressive power of that method. Multiple modeling formalisms that express different temporal properties of the domain task and that work cooperatively are required to capture the subtlety and diversity of temporal features used in expert clinical problem solving. As an example of this approach, the author describes a program called TOPAZ that contains two temporal models that represent different temporal features of the clinical domain.