Abstract
Medical decision problems that confront a patient often involve chances of serious health consequences that may extend many years into the future. Conventional decision tree diagrams are not well suited to represent such continuously distributed temporal uncertainties. As a modeling aid for such problems, Hazen (1992) introduced the stochastic tree, a diagram which combines features of decision trees and stochastic-process transition diagrams. Stochastic tree diagrams can not only depict continuously distributed temporal uncertainties, but, like decision trees, can also be rolled back to determine optimal decisions. This rollback procedure is an instance of the method of successive approximations from stochastic dynamic programming. It can be applied not only for risk-neutral objective functions, such as mean quality adjusted life years (QALY), but also for the calculation of expected utility (Hazen and Pellissier 1994) leading to quality and risk adjusted life years or QRALY.
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© 1997 Springer Science+Business Media Dordrecht
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Hazen, G.B., Sounderpandian, J. (1997). Stochastic Trees and Medical Decision Making. In: Nau, R., Grønn, E., Machina, M., Bergland, O. (eds) Economic and Environmental Risk and Uncertainty. Theory and Decision Library, vol 35. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1360-3_4
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DOI: https://doi.org/10.1007/978-94-017-1360-3_4
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