Alternative decision modelling techniques for the evaluation of health care technologies: Markov processes versus discrete event simulation

Jonathan Karnon

Health Economics, 2003, vol. 12, issue 10, 837-848

Abstract: Markov models have traditionally been used to evaluate the cost‐effectiveness of competing health care technologies that require the description of patient pathways over extended time horizons. Discrete event simulation (DES) is a more flexible, but more complicated decision modelling technique, that can also be used to model extended time horizons. Through the application of a Markov process and a DES model to an economic evaluation comparing alternative adjuvant therapies for early breast cancer, this paper compares the respective processes and outputs of these alternative modelling techniques. DES displays increased flexibility in two broad areas, though the outputs from the two modelling techniques were similar. These results indicate that the use of DES may be beneficial only when the available data demonstrates particular characteristics. Copyright © 2002 John Wiley & Sons, Ltd.

Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

Downloads: (external link)
https://doi.org/10.1002/hec.770

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:hlthec:v:12:y:2003:i:10:p:837-848

Access Statistics for this article

Health Economics is currently edited by Alan Maynard, John Hutton and Andrew Jones

More articles in Health Economics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().