Integrating Data, Models, and Reasoning in Critical Care

Modern intensive care units (ICUs) employ an impressive array of technologically sophisticated instrumentation to provide detailed measurements of various important variables and parameters for each patient. Providing care in the ICU is becoming an increasingly difficult task, however, because of the growing volume of relevant data that must be screened, integrated, and interpreted in order to extract clinically relevant and actionable information. This project combines the resources of an interdisciplinary team of investigators from academia (research groups from HST, CSAIL and RLE at MIT), industry (Philips Healthcare), and clinical medicine (Beth Israel Deaconess Medical Center in Boston) to develop and evaluate advanced ICU patient monitoring systems that will support improved efficiency, efficacy, and timeliness of clinical decision making in critical care. A substantial part of the effort on this project goes towards assembling a rich and extensive database of de-identified ICU data – the MIMIC II database – comprising high-resolution waveforms from bedside monitors, along with clinical notes and laboratory results, for several thousand patients. This database also constitutes the platform for much of the research on the project, and is being made available to researchers worldwide.