ABSTRACT
Complex interdisciplinary teams of healthcare workers care for patients in a critical condition within critical care units. High-speed physiological data generated by the medical devices within critical care units is proving to be one of the most untapped resources in healthcare today based on the growing body of research studies demonstrating common physiological patterns for a range of conditions. Robust big data infrastructures to support clinical research and real-time clinical decision support are required to perform this function. This chapter provides an introduction to the application of big data analytics within the context of critical care medicine. The characteristics of the data that are created by various medical devices are introduced within the context of its frequency, availability, and quality. This is then followed by an introduction to the key components required for big data analytics in this setting relating to data acquisition, data transmission, real-time data analytics, data persistence, and knowledge discovery. A flagship big data analytics platform, Artemis, is then introduced, and details for the Artemis deployments to date are provided. The clinical research studies that have been enabled by Artemis are then presented.
