Markov Models for Health Economic Evaluations. An implementation 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.

You can install:

• the latest released version from CRAN with:

install.packages("heemod")

• the latest development version from github with:

devtools::install_github("pierucci/heemod")

• heemod can be cited with:

Filipović-Pierucci A, Zarca K and Durand-Zaleski I (2017). “Markov Models for Health Economic Evaluation: The R Package heemod.” ArXiv e-prints. R package version 0.8.0, 1702.03252, <URL: https://pierucci.org/heemod>.

Main features:

• Graphical user interface with shiny.
• Accounting for time-dependency:
  • For both model time and state time.
  • Time-varying transition probabilities.
  • Time-varying values attached to states.
• Probabilistic uncertainty analysis (PSA).
  • With correlated resampling.
  • Covariance analysis for PSA.
  • Expected value of perfect information (EVPI).
• Deterministic sensitivity analysis (DSA).

Other features:

• Multiple state membership correction methods (life-table, custom method, etc.).
• Demographic analysis to compute population-level results.
• Heterogeneity analysis.
• Parallel computing support.
• Features for budget impact analysis.
• Interface with SAVI and BCEA.

Most of the analyses presented in Decision Modelling for Health Economic Evaluation can be performed with heemod. See the Reproducing Exact Results from DMHEE vignette for an exact reproduction of the analyses from the book.

To get started read the An Introduction to heemod vignette. Specific analysis examples (mostly inspired from Decision Modelling for Health Economic Evaluation) can be found in the package vignettes.

Kevin Zarca and Antoine Filipović-Pierucci.

• Matthew Wiener
• Zdenek Kabat
• Vojtech Filipec
• Jordan Amdahl
• Yonatan Carranza Alarcon
• Vince Daniels