title: [Probabilistic Markov models in economic evaluation of health technologies: a practical guide].
abstract: OBJECTIVE
  Markov models are the standard method used in cost-effectiveness studies to represent the natural history of disease. The objective of this study was to show the key elements in building probabilistic Markov models.
  
  
  METHODS
  We used the example of a new treatment for a generic disease. A probabilistic Markov model was constructed using statistical distributions. Monte Carlo simulations were carried out to obtain the probabilistic sensitivity analysis. The results were analyzed in terms of the cost-effectiveness plane and acceptability curve.
  
  
  RESULTS
  The incremental cost-effectiveness rate for the average patient was 22,855 euro/quality adjusted life years (QALY). In the probabilistic sensitivity analysis, the results from all simulations were located in the northeast quadrant, corresponding to positive cost and effectiveness. However, 67% of the simulations were below the threshold of 30,000 euro/QALY.
  
  
  CONCLUSIONS
  The use of probabilistic Markov models requires the integration of concepts from economics, epidemiology, statistics, and the clinical setting. Some stages of the process, such as the construction and processing of these models, the management of absolute and relative risks and of statistical distributions, often pose major difficulties but are key steps required to reproduce the disease with validity.
authors.affiliation: Unidad de Gestión Sanitaria, Hospital Alto Deba, Arrasate-Mondragón, Gipuzkoa, España. javier.marmedina@osakidetza.net
authors.forename: Javier
authors.initials: J
authors.lastname: Mar
authors.forename: Fernando
authors.initials: F
authors.lastname: Antoñanzas
authors.forename: Roberto
authors.initials: R
authors.lastname: Pradas
authors.forename: Arantzazu
authors.initials: A
authors.lastname: Arrospide
mesh_terms: D020811:Biomedical Technology / Q000191:economics*; D003362:Cost-Benefit Analysis; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical