Intensive Care Units (ICUs) are hospital departments that focus on the evolution of patients. In this scenario, the temporal dimension plays an essential role in understanding the state of the patients from their temporal information. The development of methods for the acquisition, modelling, reasoning and knowledge discovery of temporal information is, therefore, useful to exploit the large amount of temporal data recorded daily in the ICU. During the past decades, some subfields of Artificial Intelligence have been devoted to the study of temporal models and techniques to solve generic problems and towards their practical applications in the medical domain. The main goal of this paper is to present our view of some aspects of practical problems of temporal reasoning in the ICU field, and to describe our practical experience in the field in the last decade. This paper provides a non-exhaustive review of some of the efforts made in the field and our particular contributions in the development of temporal reasoning methods to partially solve some of these problems. The results are a set of software tools that help physicians to better understand the patient's temporal evolution.