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The development of data-intensive systems in medical domains has received increasing attention in recent years. In this work we present ACUDES (Architecture for Intensive Care Units Decision Support) in which we have combined traditional techniques for managing and representing time, together with a temporal diagnosis task in a decision support platform. ACUDES has been designed to manage the patient's temporal evolution data base and to describe the patient's evolution in terms of the temporal sequence diseases suffered. These functionalities are supported by an ontology which simplifies the knowledge acquisition and sharing and guarantees the semantic consistency of the patient's data.