Data-driven ICU management: Using Big Data and algorithms to improve outcomes

The 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 defi...

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Bibliographic Details
Published in:Journal of critical care 2020-12, Vol.60, p.300-304
Main Authors: Carra, Giorgia, Salluh, Jorge I.F., da Silva Ramos, Fernando José, Meyfroidt, Geert
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Big Data
Clinical medicine
Critical care
Data analysis
Data mining
Datasets
Electronic health records
Feature selection
Human error
Illnesses
Intensive care unit
Knowledge
Machine learning
Patients
Predictive modeling
Regression analysis
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Summary:The 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. •Risks and potentialities of Big Data analysis in clinical research for the Intensive Care Unit.•Data mining applications in the Intensive Care Unit: current examples and barriers to implementation.•Best practice in Big Data analysis for clinical research: from model choice to model validation.•Big Data analysis for the Intensive Care Unit organization and patient management.
ISSN:0883-9441
1557-8615
DOI:10.1016/j.jcrc.2020.09.002