Stochastic-Tree Models in Medical Decision Making

Gordon B. Hazen, James M. Pellissier and Jayavel Sounderpandian
Additional contact information
Gordon B. Hazen: Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208-3119
James M. Pellissier: Clinical and Health Economic Statistics, Merck Research Laboratories, 10 Sentry Parkway, BL3-2, Blue Bell, Pennsylvania 19422
Jayavel Sounderpandian: Department of Business, University of Wisconsin-Parkside, Box 2000, Kenosha, Wisconsin 53141-2000

Interfaces, 1998, vol. 28, issue 4, 64-80

Abstract: The stochastic tree is a recently introduced generalization of the decision tree which allows the explicit depiction of temporal uncertainty while still employing the familiar rollback procedure for decision trees. We offer an introduction to stochastic-tree modeling and techniques involved in their application to medical-treatment decisions. We also describe an application of these tools to the analysis of the decision to undergo a total hip replacement from the perspectives of an individual patient (via utility analysis) and of society (via cost-effectiveness analysis).

Keywords: health care; treatment; decision analysis; applications (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orinte:v:28:y:1998:i:4:p:64-80

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