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Markov processes are mathematical processes in which, given the present state of the process, the future is independent of the past. They are named after the Russian mathematician Andrei Markov (1856–1922), who provided the first theoretical results for this type of process. They offer a flexible and tractable framework for medical modeling and are typically used to analyze processes that evolve over time. They can be used to aggregate information from different sources and to extrapolate short-term study results into the future.

A Simple Two-State Example

Markov processes can be used to model lifetime duration, for humans as well as devices. For example, of a group of hearing aids, some may fail early on, whereas others will last a long time before they eventually break down. If ...

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