• Giorgia Carra, Salluh Jorge I F JIF Critical Care Dept, D'Or Institute for Research and Education, Rio de Janeiro, Brazil; Research dept Epimed Solutions, Postgraduation program Federal, Fernando José da Silva Ramos, and Geert Meyfroidt.
• Department of Intensive Care Medicine, University Hospitals Leuven, Leuven, Belgium, UZ Herestraat 49, box 7003, 3000 Leuven, Belgium. Electronic address: giorgia.carra@kuleuven.be.
• J Crit Care. 2020 Dec 1; 60: 300-304.

AbstractThe digitalization of the Intensive Care Unit (ICU) led to an increasing amount of clinical data being collected at the bedside. The term "Big Data" can be used to refer to the analysis of these datasets that collect enormous amount of data of different origin and format. Complexity and variety define the value of Big Data. In fact, the retrospective analysis of these datasets allows to generate new knowledge, with consequent potential improvements in the clinical practice. Despite the promising start of Big Data analysis in medical research, which has seen a rising number of peer-reviewed articles, very limited applications have been used in ICU clinical practice. A close future effort should be done to validate the knowledge extracted from clinical Big Data and implement it in the clinic. In this article, we provide an introduction to Big Data in the ICU, from data collection and data analysis, to the main successful examples of prognostic, predictive and classification models based on ICU data. In addition, we focus on the main challenges that these models face to reach the bedside and effectively improve ICU care.Copyright © 2020. Published by Elsevier Inc.

13 keywords...

hide…