BCEA: An R package to perform Bayesian Cost-Effectiveness Analysis

BCEA

Bayesian statistics

Health economics

Author

Gianluca Baio

Published

March 11, 2018

BCEA is a R library specifically designed to post-process the result of a Bayesian health economic evaluation. Typically, this consists in the estimation of a set of relevant parameters that can be combined to produce an estimation of suitable measures of cost (\(c\)) and clinical benefits (\(e\)) associated with an intervention. Within the Bayesian framework, this amounts to estimating a posterior distribution for the pair \((e,c)\).

Health economic evaluations then proceed by computing some relevant summaries of the resulting decision process: is the innovative intervention \(t=1\) more “cost-effective” than the standard intervention \(t=0\)? BCEA provides a set of functions that can be used to produce a standardised analysis. The package has been created to complement my book on Bayesian methods in health economics where it features heavily (some discussion of the package in the blog can be found here, here, here and here). A discussion of the changes in release 2.0 is here..

BCEA produces a synthesis of the decision process given the current evidence and uncertainty, as well as several indicators that can be used to perform Probabilistic Sensitivity Analysis to parameter and model uncertainty. These include the Cost-Effectiveness Acceptability Curve and the analysis of the Expected Value of Information, that can be used to prioritize research. Examples of the output of the function are given below.

library(BCEA)
data(Vaccine)
ints=c("Standard care","Vaccination")
m <- bcea(eff,cost,ref=2,interventions=ints)
summary(m)


Cost-effectiveness analysis summary 

Reference intervention:  Vaccination
Comparator intervention: Standard care

Optimal decision: choose Standard care for k < 20100 and Vaccination for k >= 20100


Analysis for willingness to pay parameter k = 25000

              Expected net benefit
Standard care              -36.054
Vaccination                -34.826

                                EIB  CEAC  ICER
Vaccination vs Standard care 1.2284 0.529 20098

Optimal intervention (max expected net benefit) for k = 25000: Vaccination
           
EVPI 2.4145

Installation

There are two ways of installing BCEA. A “stable” version (currently 2.3.1) is packaged and available from CRAN. So you can simply type on your R terminal

install.packages("BCEA")

The second way involves using the “development” version of BCEA - this will usually be updated more frequently and may be continuously tested. On Windows machines, you need to install a few dependencies, including Rtools first, e.g. by running

pkgs <- c("MASS","Rtools","devtools")
repos <- c("https://cran.rstudio.com", "https://www.math.ntnu.no/inla/R/stable") 
install.packages(pkgs,repos=repos,dependencies = "Depends")

before installing the package using devtools:

devtools::install_github("giabaio/BCEA")

Under Linux or MacOS, it is sufficient to install the package via devtools:

install.packages("devtools")
devtools:install_github("giabaio/BCEA")

Note

We recommend using the GitHub installation from the master repository as it will fix minor issues that may become known quicker than the stable version on CRAN.

Last updated: 22 August 2024

Relevant publications

Baio, G. 2020. “survHE: Survival Analysis for Health Economic Evaluation and Cost-Effectiveness Modelling.” Journal of Statistical Software 95 (October): 1–47. https://doi.org/10.18637/jss.v095.i14.

Baio, G, A Berardi, and A Heath. 2017. Bayesian Cost-Effectiveness Analysis with the R Package BCEA. Springer. https://doi.org/10.1007/978-3-319-55718-2.

Baio, G, and AP Dawid. 2011. “Probabilistic Sensitivity Analysis in Health Economics.” Statistical Methods in Medical Research, September. https://doi.org/10.1177/0962280211419832.