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Opportunities and Challenges in Health Care Simulation

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Advancing the Frontiers of Simulation

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 133))

Abstract

The delivery of health care is a complex and expensive process that presently is failing to meet the expectations and standards of patients, physicians, administrators and government entities. Simulation tools, both discrete-event simulation and system dynamics, enable managers to better understand the behavior of complex systems and predict their response to changes. After reviewing some successful applications of simulation in health care, this article examines how wellsuited simulation is to analyze health care systems, and explores the reasons why simulation has not been adopted as a routine part of health care systems analysis. Some ideas are presented regarding what can be done to encourage greater use of simulation in health care.

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Acknowledgements

The authors wish to thank Christos Alexopoulos, David Goldsman, and James R. Wilson for their work organizing and editing this volume. Our appreciation goes to Christos for suggesting the topic of this paper. We wish to thank David Block MD, PhD for reviewing an early version of the manuscript and providing very insightful comments on the topic, especially the cultural environment of health care. Dr. Seila wishes to thank his wife, Jodie, who is a registered nurse and has worked in both hospital and physician practice settings, for giving him an intimate view of health care delivery that he could not have gained otherwise. Dr. Seila also wishes to thank George Fishman for introducing him to discrete-event simulation, directing his dissertation research and providing guidance and encouragement over the past thirty years.

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Correspondence to Andrew F. Seila .

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Seila, A.F., Brailsford, S. (2009). Opportunities and Challenges in Health Care Simulation. In: Alexopoulos, C., Goldsman, D., Wilson, J. (eds) Advancing the Frontiers of Simulation. International Series in Operations Research & Management Science, vol 133. Springer, Boston, MA. https://doi.org/10.1007/b110059_10

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