Uncertainty in Decision Models Analyzing Cost-Effectiveness

Markov chains have been increasingly used to describe the progression of a medical condition through distinct health states.2 Markov chains are described by the transition matrix that contains the probabilities that a subject moves from one state to another state by the end of a cycle (e g., a month or a year). Because this is a matrix of probabilities, the path that a subject follows is stochastic or random. This inherent variability, termed sampling uncertainty by Hunink et al., is what makes the Markov