Decision models are becoming more and more complex to represent the underlying clinical conditions better and to provide more and better insight to decision makers. New methodological techniques around decision modeling are being developed that rely heavily on statistical and mathematical techniques (e.g., model calibration, value of information, evidence synthesis). Current commercially available software can be limiting as it sometimes provides limited flexibility in embedding such statistical techniques within a decision model framework.

R is an open-source software that provides a flexible environment where advanced statistical analyses can be combined with decision models of varying complexity within the same framework and the results can be presented in publication-ready tabular and graphical forms. The fact that R is freely available also improves model transparency and reproducibility.