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Logo of aicSpringerOpen.comThis journalSubmit a manuscriptRegisterSpringerOpen.comAnnals of Intensive Care
Ann Intensive Care. 2012; 2: 18.
Published online Jun 15, 2012. doi:  10.1186/2110-5820-2-18
PMCID: PMC3464892
Systems modeling and simulation applications for critical care medicine
Yue Dong,1,2 Nicolas W Chbat,3 Ashish Gupta,4 Mirsad Hadzikadic,5 and Ognjen Gajiccorresponding author1,6
1Multidisciplinary Epidemiology and Translational Research in Intensive Care, Mayo Clinic, Rochester, MN, USA
2Mayo Clinic Multidisciplinary Simulation Center, Rochester, MN, USA
3Philips Research North America, Briarcliff Manor, NY, USA
4School of Business, Minnesota State University, Moorhead, MN, USA
5Department of Software and Information Systems, University of North Carolina, Charlotte, USA
6Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, 200 1st St. SW, Rochester, MN, USA
corresponding authorCorresponding author.
Yue Dong: dong.yue/at/; Nicolas W Chbat: chbat/at/; Ashish Gupta: gupta/at/; Mirsad Hadzikadic: mirsad/at/; Ognjen Gajic: gajic.ognjen/at/
Received January 16, 2012; Accepted June 15, 2012.
Critical care delivery is a complex, expensive, error prone, medical specialty and remains the focal point of major improvement efforts in healthcare delivery. Various modeling and simulation techniques offer unique opportunities to better understand the interactions between clinical physiology and care delivery. The novel insights gained from the systems perspective can then be used to develop and test new treatment strategies and make critical care delivery more efficient and effective. However, modeling and simulation applications in critical care remain underutilized. This article provides an overview of major computer-based simulation techniques as applied to critical care medicine. We provide three application examples of different simulation techniques, including a) pathophysiological model of acute lung injury, b) process modeling of critical care delivery, and c) an agent-based model to study interaction between pathophysiology and healthcare delivery. Finally, we identify certain challenges to, and opportunities for, future research in the area.
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