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Cohort models are economic models that follow a hypothetical group of patients, treated as a single homogeneous cohort, through a set of defined health states over time in order to estimate expected costs and outcomes. The Markov model is the classic example, in which the cohort is distributed across mutually exclusive states and moves between them each cycle according to transition probabilities, accumulating costs and health effects along the way. Such models are efficient and transparent and are well suited to conditions that can be adequately described by average experience without reference to individual history. Where patient heterogeneity or dependence on past events is important, individual-level simulation may be required instead, but cohort models remain a mainstay of cost-effectiveness analysis.
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