The decision on the most appropriate procedure to provide to the
patients the best healthcare possible is a critical and complex task in Intensive
Care Units (ICU). Clinical Decision Support Systems (CDSS) should deal with
huge amounts of data and online monitoring, analyzing numerous parameters
and providing outputs in a short real-time. Although the advances attained in
this area of knowledge new challenges should be taken into account in future
CDSS developments, principally in ICUs environments. The next generation of
CDSS will be pervasive and ubiquitous providing the doctors with the
appropriate services and information in order to support decisions regardless the
time or the local where they are. Consequently new requirements arise namely
the privacy of data and the security in data access. This paper will present a
pervasive perspective of the decision making process in the context of INTCare
system, an intelligent decision support system for intensive medicine. Three
scenarios are explored using data mining models continuously assessed and
optimized. Some preliminary results are depicted and discussed.Fundação para a Ciência e a Tecnologia (FCT