Temporal Detection of Guideline Interactions

Clinical practice guidelines are widely used to support physicians, but only on individual pathologies. On the other hand, the treatment of patients affected by multiple diseases is one of the main challenges for the modern healthcare. This requires the development of new methodologies, supporting physicians in the detection of interactions between guidelines. In a previous work, we proposed a flexible and user-driven approach, helping physicians in the detection of possible interactions between guidelines, supporting focusing and analysis at multiple levels of abstractions. However, it did not cope with the fact that interactions occur in time. For instance, the effects of two actions may potentially conflict, but practical conflicts happen only if such effects overlap in time. In this paper, we extend the ontological model to deal with the temporal aspects, and the detection algorithms to cope with them. Different types of facilities are provided to physicians, supporting the analysis of interactions between both guidelines “per se”, and the concrete application of guidelines to specific patients. In both cases, different temporal facilities are provided to user physicians, based on Artificial Intelligence temporal reasoning techniques.