Current recommendations on the estimation of transition probabilities in Markov cohort models for use in health care decision-making: a targeted literature review
Authors Olariu E, Cadwell KK, Hancock E, Trueman D, Chevrou-Severac H
Received 23 February 2017
Accepted for publication 22 June 2017
Published 1 September 2017 Volume 2017:9 Pages 537—546
Checked for plagiarism Yes
Review by Single-blind
Peer reviewer comments 2
Editor who approved publication: Professor Dean Smith
Elena Olariu,1 Kevin K Cadwell,1 Elizabeth Hancock,1 David Trueman,1 Helene Chevrou-Severac2
1PHMR Ltd, London, UK; 2Takeda Pharmaceuticals International AG, Zurich, Switzerland
Objective: Although Markov cohort models represent one of the most common forms of decision-analytic models used in health care decision-making, correct implementation of such models requires reliable estimation of transition probabilities. This study sought to identify consensus statements or guidelines that detail how such transition probability matrices should be estimated.
Methods: A literature review was performed to identify relevant publications in the following databases: Medline, Embase, the Cochrane Library, and PubMed. Electronic searches were supplemented by manual-searches of health technology assessment (HTA) websites in Australia, Belgium, Canada, France, Germany, Ireland, Norway, Portugal, Sweden, and the UK. One reviewer assessed studies for eligibility.
Results: Of the 1,931 citations identified in the electronic searches, no studies met the inclusion criteria for full-text review, and no guidelines on transition probabilities in Markov models were identified. Manual-searching of the websites of HTA agencies identified ten guidelines on economic evaluations (Australia, Belgium, Canada, France, Germany, Ireland, Norway, Portugal, Sweden, and UK). All identified guidelines provided general guidance on how to develop economic models, but none provided guidance on the calculation of transition probabilities. One relevant publication was identified following review of the reference lists of HTA agency guidelines: the International Society for Pharmacoeconomics and Outcomes Research taskforce guidance. This provided limited guidance on the use of rates and probabilities.
Conclusions: There is limited formal guidance available on the estimation of transition probabilities for use in decision-analytic models. Given the increasing importance of cost-effectiveness analysis in the decision-making processes of HTA bodies and other medical decision-makers, there is a need for additional guidance to inform a more consistent approach to decision-analytic modeling. Further research should be done to develop more detailed guidelines on the estimation of transition probabilities.
Keywords: cost-effectiveness, decision models, probability, transitions
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