Economic evaluation in its most popular form--cost-effectiveness analysis (CEA)--is intended to provide evidence to decision makers for allocating scarce resources with the best value for the money. CEA includes evaluation of the patients’ health outcomes, usually in the form of quality-adjusted life-years (QALYs), in relation to the resources and costs associated with them to achieve these outcomes. CEA is conducted to compare the economic efficiency of alternative interventions.

The authors describe the results of the project undertaken in the framework of the National Institute for Health and Care Excellence (NICE), which is responsible for conducting CEA of drugs and other health technologies in England. Health economists are using decision models to estimate costs and outcomes.

A discrete-event simulation (DES) model has been developed that is capable of reflecting complex patterns of disease progression related to individual patients with an atrial fibrillation condition. The model has been used during the NICE guideline update process and has allowed for the realistic modeling of costs and outcomes for a complete diagnosis-to-death treatment pathway.

However, the authors admit that DES resulted in a much more complex model with higher input data requirements and longer runtimes compared to commonly used CEA models based on decision trees or state-transition Markov models.

The intended audience of the paper is academics in computer science, health economics, and economic evaluation. Readers who are interested in this topic can find additional information on the subject [1,2].