• David J Stone and Marie Csete.
• Departments of Anesthesiology and Neurosurgery, University of Virginia School of Medicine, Charlottesville, VA; Center for Wireless Health, University of Virginia School of Engineering and Applied Science, Charlottesville, VA. Electronic address: djs4v@virginia.edu.
• J Crit Care. 2016 Oct 1; 35: 90-5.

AbstractViewing the intensive care unit (ICU) as a control system with inputs (patients) and outputs (outcomes), we focus on actuation (therapies) of the system and how to enhance our understanding of status of patients and their trajectory in the ICU. To incorporate the results of these analytics meaningfully, we feel that a reassessment of predictive scoring systems and of ways to optimally characterize and display the patient's "state space" to clinicians is important. Advances in sensing (diagnostics) and computation have not yet led to significantly better actuation, and so we focus on ways that data can be used to improve actuation in the ICU, in particular by following therapeutic burden along with disease severity. This article is meant to encourage discussion about how the critical care community can best deal with the data they see each day, and prepare for recommendations that will inevitably arise from application of major federal and state initiatives in big data analytics and precision medicine.Copyright © 2016 Elsevier Inc. All rights reserved.

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