BCEA: An R Package for Cost-Effectiveness Analysis

@article{Green2022BCEAAR,
  title={BCEA: An R Package for Cost-Effectiveness Analysis},
  author={Nathan Green and Anna Heath and Gianluca Baio},
  journal={J. Open Source Softw.},
  year={2022},
  volume={7},
  pages={4206}
}
We describe in detail how to perform health economic cost-effectiveness analyses (CEA) using the R package BCEA (Bayesian Cost-Effectiveness 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… 

Figures and Tables from this paper

References

SHOWING 1-10 OF 23 REFERENCES

Bayesian models for cost-effectiveness analysis in the presence of structural zero costs

  • G. Baio
  • Political Science
    Statistics in medicine
  • 2014
Bayesian modelling for cost‐effectiveness data has received much attention in both the health economics and the statistical literature, in recent years. Cost‐effectiveness data are characterised by a

Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis

In recent years, considerable attention has been devoted to the development of statistical methods for the analysis of uncertainty in cost-effectiveness analysis, with a focus on situations in which

Probabilistic Sensitivity Analysis in Cost-Effectiveness Models: Determining Model Convergence in Cohort Models

Probabilistic sensitivity analysis (PSA) demonstrates the parameter uncertainty in a decision problem. The technique involves sampling parameters from their respective distributions (rather than

Limitations of Acceptability Curves for Presenting Uncertainty in Cost-Effectiveness Analysis

The objective of this article is to demonstrate the limitations of CEACs for presenting uncertainty in cost-effectiveness analyses, and to rethink their use in communicating uncertainty.

A framework for cost-effectiveness analysis from clinical trial data.

A general Bayesian framework for cost-effectiveness analysis (CEA) from clinical trial data is presented, which allows for very flexible modelling of both cost and efficacy related trial data.

Bayesian Methods in Health Economics

  • G. Baio
  • Medicine, Political Science
  • 2012
Introduction to Health Economic Evaluation Introduction Health economic evaluation Cost components Outcomes Discounting Types of economic evaluations Comparing health interventions Introduction to

hesim: Health Economic Simulation Modeling and Decision Analysis

Hesim helps fill the gap by facilitating parameterization, simulation, and analysis of economic models in an integrated manner, and a modular design based on R6 and S3 classes allows users to combine separate submodels for disease progression, costs, and utility in a flexible way.

Model Parameter Estimation and Uncertainty Analysis

The article argues that the estimation of point estimates and uncertainty in parameters is part of a single process and explores the link between parameter uncertainty through to decision uncertainty and the relationship to value-of-information analysis.

Markov Models for Health Economic Evaluations: The R Package heemod

This paper 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, etc.