Comparing three software tools for implementing markov models for health economic evaluations
Related Experiment Video
Updated: Jun 20, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
1Helmholtz Zentrum München, Neuherberg, Germany. petra.menn@helmholtz-muenchen.de
Background:
Various software packages are commonly used for the implementation and calculation of decision-analytic models for health economic evaluations. However, comparison of these programs with regard to ease of implementing a model is lacking.
Objectives:
(i) to compare the assets and drawbacks of three commonly used software packages for Markov models with regard to ease of implementation; and (ii) to investigate how a technical model validation can be conducted by comparing the results of the three implementations.
Methods:
A Markov model on chronic obstructive pulmonary disease was implemented in TreeAge, Microsoft Excel and Arena with the same assumptions on model structure, transition probabilities and costs. A hypothetical smoking cessation programme for patients in stage 1 was evaluated against usual care. The packages were compared with respect to time and effort for implementation, run-time, features for the presentation of results, and flexibility. Agreement between the packages on average costs and life-years gained and on the incremental cost-effectiveness ratio was considered for technical validation in the form of expected values (between TreeAge and Excel only) and Monte Carlo simulations.
Results:
Ease of implementation was best in TreeAge, whereas Arena offered the highest flexibility. Deterministic results were in agreement between TreeAge and Excel, as were simulated values between all three packages.
Conclusions:
Excel offers an intuitive spreadsheet interface, but the acquisition of and the training in TreeAge or Arena is worthwhile for more complex models. Double implementation is a practicable validation technique that should be conducted to ensure correct model implementation.
Related Concept Videos
Statistical Software for Data Analysis and Clinical Trials
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Comparing the Survival Analysis of Two or More Groups
Statistical Methods for Analyzing Epidemiological Data
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...