An augmented form of Petri net, referred to as a choice-point net, that can capture timing and probability constraints is introduced. Choice-point nets were developed to model health-care protocols, in which the events or actions taken by health-care professionals, institutions and patients occur either at prespecified times or after a prespecified lapse of time. Furthermore, actions that occur and decisions that are made in health-care protocols occur with some probability and not with certainty and so choice-point nets also possess a mechanism for modeling probabilistic choice. In this data structure, timing is associated with event-based transitions that may fire multiple times to simulate the same event occurring several times in parallel. Events may result in several possible outcomes, or choices, each of which has a probability of occurrence. A choice-point net may be scaled without requiring structural changes to the model and may be analyzed by unravelling it into a finite-state automaton representing (perhaps portions of) the behavior of the system. Questions related to health-care protocols can be translated into the mathematical language of the net. Recursive algorithms have been developed to determine answers to such questions.