Factored Stochastic Trees: A Tool for solving Complex Temporal Medical Decision Models

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18 Scopus citations

Abstract

The stochastic tree is a continuous-time version of a Markov-cycle tree, useful for constructing and solving medical decision models in which risks of mortality and morbidity may extend over time. Stochastic trees have advantages over Markov-cycle trees in graphic display and computational solution. Like the decision tree or Markov-cycle tree, stochastic tree models of complex medical decision problems can be too large for convenient graphic formulation and display. This paper introduces the notion of factoring a large stochastic tree into simpler components, each of which may be easily displayed. It also shows how the rollback solution procedure for unfactored stochastic trees may be conveniently adapted to solve factored trees. These concepts are illustrated using published examples from the medical literature. Key words: stochastic trees; DEALE models; decision analysis; Markov-cycle trees; temporal medical decision modeling.

Original languageEnglish (US)
Pages (from-to)227-236
Number of pages10
JournalMedical Decision Making
Volume13
Issue number3
DOIs
StatePublished - Aug 1993

ASJC Scopus subject areas

  • Health Policy

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