BCEA: An R Package for CostEffectiveness Analysis
Abstract
We describe in detail how to perform health economic costeffectiveness analyses (CEA) using the R package $\textbf{BCEA}$ (Bayesian CostEffectiveness Analysis). CEA consist of analytic approaches for combining costs and health consequences of intervention(s). These help to understand how much an intervention may cost (per unit of health gained) compared to an alternative intervention, such as a control or status quo. For resource allocation, a decision maker may wish to know if an intervention is cost saving, and if not then how much more would it cost to implement it compared to a less effective intervention. Current guidance for costeffectiveness analyses advocates the quantification of uncertainties which can be represented by random samples obtained from a probability sensitivity analysis or, more efficiently, a Bayesian model. $\textbf{BCEA}$ can be used to postprocess the sampled costs and health impacts to perform advanced analyses producing standardised and highly customisable outputs. We present the features of the package, including its many functions and their practical application. $\textbf{BCEA}$ is valuable for statisticians and practitioners working in the field of health economic modelling wanting to simplify and standardise their workflow, for example in the preparation of dossiers in support of marketing authorisation, or academic and scientific publications.
 Publication:

The Journal of Open Source Software
 Pub Date:
 September 2022
 DOI:
 10.21105/joss.04206
 arXiv:
 arXiv:2203.09901
 Bibcode:
 2022JOSS....7.4206G
 Keywords:

 Statistics  Computation;
 Statistics  Applications