Temporal indeterminacy is common in clinical medicine because the time of many clinical events is frequently not precisely known. Decision support systems that reason with clinical data may need to deal with this indeterminacy. This indeterminacy support must have a sound foundational model so that other system components may take advantage of it. In particular, it should operate in concert with temporal abstraction, a feature that is crucial in several clinical decision support systems that our group has developed. We have implemented a temporal query system called Tzolkin that provides extensive support for the temporal indeterminacies found in clinical medicine, and have integrated this support with our temporal abstraction mechanism. The resulting system provides a simple, yet powerful approach for dealing with temporal indeterminacy and temporal abstraction.
