Markov Models for Health Economic Evaluations: The R Package heemod

TL;DR

The paper introduces the R package heemod, which facilitates building and analyzing Markov models for health economic evaluations, supporting various advanced features and sensitivity analyses.

Contribution

It presents a comprehensive R package that implements advanced Markov modeling techniques for health economic evaluations, including sensitivity and heterogeneity analyses.

Findings

Successfully built and analyzed an example Markov model.

Demonstrated the package's features and capabilities.

Provided insights into health economic decision-making.

Abstract

Health economic evaluation studies are widely used in public health to assess health strategies in terms of their cost-effectiveness and inform public policies. We developed an R package for Markov models implementing most of the modelling and reporting features described in reference textbooks and guidelines: deterministic and probabilistic sensitivity analysis, heterogeneity analysis, time dependency on state-time and model-time (semi-Markov and non-homogeneous Markov models), etc. In this paper we illustrate the features of heemod by building and analysing an example Markov model. We then explain the design and the underlying implementation of the package.