An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example

Decision models can combine information from different sources to simulate the long-term consequences of alternative strategies in the presence of uncertainty. A cohort state-transition model (cSTM) is a decision model commonly used in medical decision making to simulate the transitions of a hypothe...

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Bibliographic Details
Published in:Medical decision making 2023-01, Vol.43 (1), p.3-20
Main Authors: Alarid-Escudero, Fernando, Krijkamp, Eline, Enns, Eva A., Yang, Alan, Hunink, M. G. Myriam, Pechlivanoglou, Petros, Jalal, Hawre
Format: Article
Language:English
Subjects:
Cost-Benefit Analysis
Cost-Effectiveness Analysis
Humans
Markov Chains
Probability
Programming Languages
Quality-Adjusted Life Years
Software
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Summary:Decision models can combine information from different sources to simulate the long-term consequences of alternative strategies in the presence of uncertainty. A cohort state-transition model (cSTM) is a decision model commonly used in medical decision making to simulate the transitions of a hypothetical cohort among various health states over time. This tutorial focuses on time-independent cSTM, in which transition probabilities among health states remain constant over time. We implement time-independent cSTM in R, an open-source mathematical and statistical programming language. We illustrate time-independent cSTMs using a previously published decision model, calculate costs and effectiveness outcomes, and conduct a cost-effectiveness analysis of multiple strategies, including a probabilistic sensitivity analysis. We provide open-source code in R to facilitate wider adoption. In a second, more advanced tutorial, we illustrate time-dependent cSTMs.
ISSN:0272-989X
1552-681X
DOI:10.1177/0272989X221103163