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Big data and visual analytics in anaesthesia and health care
A F Simpao1, L M Ahumada2, M A Rehman3
1Department of Anesthesiology and Critical Care, Perelman School of Medicine at the University of Pennsylvania and the Children's Hospital of Philadelphia, 3401 Civic Center Boulevard, Suite 9329, Philadelphia, PA 19104-4399, USA simpaoa@email.chop.edu.
Abstract:
Advances in computer technology, patient monitoring systems, and electronic health record systems have enabled rapid accumulation of patient data in electronic form (i.e. big data). Organizations such as the Anesthesia Quality Institute and Multicenter Perioperative Outcomes Group have spearheaded large-scale efforts to collect anaesthesia big data for outcomes research and quality improvement. Analytics--the systematic use of data combined with quantitative and qualitative analysis to make decisions--can be applied to big data for quality and performance improvements, such as predictive risk assessment, clinical decision support, and resource management. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces, and it can facilitate performance of cognitive activities involving big data. Ongoing integration of big data and analytics within anaesthesia and health care will increase demand for anaesthesia professionals who are well versed in both the medical and the information sciences.
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