Transformation of Markov Models for Cost-Effectiveness Analysis into the System Dynamics Methodology

Abstract

Markov cohort models are one of the standard methodologies for conducting cost-effectiveness analyses of health care interventions of chronic diseases. The system dynamics (SD) approach, where a model consists of stocks and their interconnecting flows, is rarely used, but in principle it can be used to conduct the same type of analysis. The authors show that a simple transformation from the transition probabilities of a Markov model to relative rates always leads to an equivalent system dynamics model. Here the stocks match the Markov states, because they store the same number of patients as in the corresponding state. The authors demonstrate an approach on an exemplary cost-effectiveness analysis for a smoking cessation programme for chronic obstructive pulmonary disease (COPD) with a simplified Markov model based on Menn (2009). Both the Markov model and the system dynamics model lead to nearly identical results. However, the latter offers more flexibility as it can incorporate interactions between different patient groups.