What is a Markov model and when is it used?

• A. A static model with a single snapshot.
• B. A state-transition model used for chronic diseases to simulate progression and accumulate costs and utilities over time.
• C. A financial budgeting tool for short-term programs.
• D. A simple regression model predicting costs.

Answer: (B)

Markov models are state-transition tools that follow a group of individuals as they move between defined health states in discrete time steps. In each cycle, people can stay in the same state or transition to another according to specified probabilities. By tracking these movements over many cycles, you can accumulate costs and health outcomes (utilities) to estimate long-term results, often applying discounting for future costs and benefits.

They are especially useful for chronic diseases where a patient’s condition evolves over years and outcomes accumulate over time, not just at a single moment. You define the possible states (such as well, various disease stages, and death), choose a cycle length and a time horizon, and estimate the probabilities of moving between states each cycle. This lets you model progression, recurring events, and the associated costs and utilities to compare different strategies.

Other options describe a static snapshot, a general short-term budgeting tool, or a simple regression, none of which captures the ongoing state-to-state progression and long-term accumulation that a Markov model provides.