Primer on medical decision analysis: Part 5--Working with Markov processes.
Med Decis Making
; 17(2): 152-9, 1997.
Article
en En
| MEDLINE
| ID: mdl-9107610
ABSTRACT
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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Bases de datos:
MEDLINE
Asunto principal:
Árboles de Decisión
/
Cadenas de Markov
/
Técnicas de Apoyo para la Decisión
Tipo de estudio:
Health_economic_evaluation
/
Prognostic_studies
/
Qualitative_research
Límite:
Humans
Idioma:
En
Revista:
Med Decis Making
Año:
1997
Tipo del documento:
Article
País de afiliación:
Canadá