Markov Model Toolkit: Concepts, Assumptions and Examples
Faculty: Stephanie R. Earnshaw, PhD, Anita J. Brogan, PhD
Course Description
This course is designed to provide an overview of Markov modeling and its application to assessing the economic value of new and existing health care technologies. The course will first introduce Markov modeling in the context of other model structures and cover the basic elements of a Markov model, including health states, cycle length, transition probabilities, the Markov property, parameter values associated with the health states, discounting, halfcycle correction, and sensitivity analyses. The course will present the mathematical concepts behind evaluating and building a Markov model, describe how to use a Markov model to assess the economic value of a health care technology, and present a fullscale example.
Learning Objectives
Upon completion of the Markov Model Toolkit: Concepts, Assumptions and Examples module, you will be able to:
 Determine when it is appropriate to use a Markov approach
 Understand the basic mechanics of Markov models and appropriate sensitivity analyses
 Apply Markov modeling concepts to realworld problems
 Construct a Markov model for assessing the economic value of a health care technology
