• Thomas Heldt, Bill Long, George C Verghese, Peter Szolovits, and Roger G Mark.
• Laboratory for Electromagntic & Electronic Systems, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
• Conf Proc IEEE Eng Med Biol Soc. 2006 Jan 1;1:350-3.

AbstractModern intensive care units (ICUs) employ an impressive array of technologically sophisticated instrumentation to provide detailed measurements of the pathophysiological state of each patient. Providing life support in the ICU is becoming an increasingly complex task, however, because of the growing volume of relevant data from clinical observations, bedside monitors, mechanical ventilators, and a wide variety of laboratory tests and imaging studies. The enormous amount of ICU data and its poor organization makes its integration and interpretation time-consuming and inefficient. There is a critical need to integrate the disparate clinical information into a single, rational framework and to provide the clinician with hypothesis-driven displays that succinctly summarize a patient's trajectory over time. In this paper, we present our recent efforts towards the development of such an advanced patient monitoring system that aims to improve the efficiency, accuracy, and timeliness of clinical decision making in intensive care.

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