Rowan Iskandar, PhD, presented a novel theoretical framework for Markov cohort models at a CHDS research seminar. Markov cohort models are commonly used in decision analysis to model the effect of different policies and interventions on population health, but these models are implicitly based on the probability distributions of a single individual transitioning through different health states. Dr. Iskandar explored this implicit assumption and presented a theoretical model that explicitly extends the basic Markov model framework to a discrete population with many individuals, including the derivation of a density function, mean, and variance for this stochastic process. This framework can be used to support the continued use of Markov cohort models in decision analysis and provides a way to rigorously resolve methodological issues that arise when Markov cohort models are used in research.
Rowan Iskandar, PhD, is an Assistant Professor of Health Services, Policy and Practice at the School of Public Health at Brown University.
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