Abstract
In this chapter, we merge computer simulation modeling and intervention research within one analytical framework. In particular, we consider the argument that the evaluation of organizational changes in the delivery of health services should include the simulation of health system operations. In turn, the methodological rigor of evaluative studies should be applied to the analysis of simulation experiments. We review the implications of such an approach for both the design and analysis of simulation studies. We conclude with a brief discussion of the requirements for reporting the design, methods, and results of a simulation study.
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References
R. R. Barton. Designing simulation experiments. In Proceedings of the 33nd conference on Winter simulation, pages 47–52. IEEE Computer Society, 2001.
J. C. Benneyan. An introduction to using computer simulation in healthcare: Patient wait case study. Journal of the Society for Health Systems, 5(3):1–15, 1997.
G. E. P. Box, W. G. Hunter, and J. S. Hunter. Statistics for experimenters. Wiley-Interscience, New York, 1978.
M. K. Campbell, D. R. Elbourne, and D. G. Altman. CONSORT statement: Extension to cluster randomised trials. British Medical Journal, 328(7441):702–708, 2004.
Medical Research Council. A framework for the development and evaluation of RCTs for complex interventions to improve health. www.mrc.ac.uk/utilities/Documentrecord/index.htm?d=MRC003372, 2000.
H. T. Davies and R Davies. Simulating health systems: Modelling problems and software solutions. European Journal of Operational Research, 87:35–44, 1995.
J. E. Everett. A decision support simulation model for the management of an elective surgery waiting system. Health Care Management Science, 5(2):89–95, 2002.
D. Fone, S. Hollinghurst, M. Temple, A. Round, N. Lester, A. Weightman, K. Roberts, E. Coyle, G. Bevan, and S. Palmer. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. Journal of Public Health, 25(4):325–335, 2003.
J. J. Heckman. The scientific model of causality. Sociological Methodology, 35(1): 1–97, 2005.
L. Kuramoto, B. G. Sobolev, and M. G. Donaldson. On reporting results from randomized controlled trials with recurrent events. BMC Medica Research Methodology, 8:35, 2008.
A. M. Law. Simulation modeling and analysis. Tata McGraw-Hill, 4th edition, New York, 2007.
A. R. Mahachek. An introduction to patient flow simulation for health care managers. Journal of the Society for Health Systems, 3(3):73–81, 1992.
G. Maldonado and S. Greenland. Estimating causal effects. International Journal of Epidemiology, 31(2):422–429, 2002.
S. L. Morgan and C. Winship. Counterfactuals and causal inference: Methods and principles for social research. Cambridge University Press, Cambridge, UK, 2007.
G. T. O’Connor, S. K. Plume, E. M. Olmstead, L. H. Coffin, J. R. Morton, C. T. Maloney, E. R. Nowicki, D. G. Levy, J. F. Tryzelaar, F. Hernandez, and. Multivariate prediction of in-hospital mortality associated with coronary artery bypass graft surgery. Northern New England Cardiovascular Disease Study Group. Circulation, 85(6):2110–2118, 1992.
A. O’Hagan, M. Stevenson, and J. Madan. Monte Carlo probabilistic sensitivity analysis for patient level simulation models: Efficient estimation of mean and variance using ANOVA. Health Economics, 16(10):1009–1023, 2007.
J. Pearl. Causality: Models, reasoning, and inference. Cambridge University Press, Cambridge, UK, 2000.
D. Rickles. Causality in complex interventions. Medicine, Health Care and Philosophy, 12(1):77–90, 2009.
K. F. Schulz, D. G. Altman, D. Moher, and the CONSORT Group. CONSORT 2010 statement: Updated guidelines for reporting parallel group randomised trials. British Medical Journal, 340:c332, 2010.
B. Sobolev and L. Kuramoto. Policy analysis using patient flow simulations: Conceptual framework and study design. Clinical and Investigative Medicine, 28(6): 359–363, 2005.
B. Sobolev, D. Harel, C. Vasilakis, and A. Levy. Using the statecharts paradigm for simulation of patient flow in surgical care. Health Care Management Science, 11(1): 79–86, 2008.
V. Zellermeyer. Report of the Surgical Process Analysis and Improvement Expert Panel. Ontario Ministry of Health and Long-Term Care, 2005.
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Sobolev, B., Sanchez, V., Kuramoto, L. (2012). Simulation Studies. In: Health Care Evaluation Using Computer Simulation. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-2233-4_2
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DOI: https://doi.org/10.1007/978-1-4614-2233-4_2
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