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Med Decis Making. 1997 Apr-Jun;17(2):152-9.

Primer on medical decision analysis: Part 5--Working with Markov processes.

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  • 1University of Toronto Programme in Clinical Epidemiology and Health Care Research (The Toronto Hospital and The Sunnybrook Health Science Centre Units), Ontario, Canada.


Clinical decisions often have long-term implications. Analysis encounter difficulties when employing conventional decision-analytic methods to model these scenarios. This occurs because probability and utility variables often change with time and conventional decision trees do not easily capture this dynamic quality. A Markov analysis performed with current computer software programs provides a flexible and convenient means of modeling long-term scenarios. However, novices should be aware of several potential pitfalls when attempting to use these programs. When deciding how to model a given clinical problem, the analyst must weigh the simplicity and clarity of a conventional tree against the fidelity of a Markov analysis. In direct comparisons, both approaches gave the same qualitative answers.

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