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

@article{Baio2014BayesianMF,
  title={Bayesian models for cost-effectiveness analysis in the presence of structural zero costs},
  author={Gianluca Baio},
  journal={Statistics in Medicine},
  year={2014},
  volume={33},
  pages={1900 - 1913}
}
  • G. Baio
  • Published 19 July 2013
  • Political Science
  • Statistics in Medicine
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 relatively complex structure of relationships linking a suitable measure of clinical benefit (e.g. quality‐adjusted life years) and the associated costs. Simplifying assumptions, such as (bivariate) normality of the underlying distributions, are usually not granted, particularly for the cost… 

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References

SHOWING 1-10 OF 56 REFERENCES

Bayesian Models for Cost-Effectiveness Analysis in the Presence of Structural Zero Costs.

  • G. Baio
  • Political Science
    Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
  • 2014

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

TLDR
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.

Predicting costs over time using Bayesian Markov chain Monte Carlo methods: an application to early inflammatory polyarthritis.

TLDR
This study compares the performance of four different multilevel/hierarchical models (which allow for both the within-subject and between-subject variability) for analysing healthcare costs in a cohort of individuals with early inflammatory polyarthritis who were followed-up annually over a 5-year time period from 1990/1991.

Bayesian cost‐effectiveness analysis from clinical trial data

TLDR
Bayesian computations for this curve in the case where data on both costs and efficacy are available from a clinical trial are presented, leading to a more conclusive assessment of cost‐effectiveness.

Use of Bayesian Markov Chain Monte Carlo Methods to Model Cost-of-Illness Data

TLDR
This article demonstrates how a hurdle model can be implemented from a Bayesian perspective by means of Markov Chain Monte Carlo simulation methods using the freely available software WinBUGS.

Confounding and missing data in cost-effectiveness analysis: comparing different methods

TLDR
A method based on Bayesian inference revealed the unexplained association of costs and effectiveness and demonstrated strong heteroscedasticity in positive costs, and should be accounted for in cost-effectiveness analyses, if the comparison groups are not randomized.

Estimating the cost-effectiveness of an intervention in a clinical trial when partial cost information is available: a Bayesian approach.

TLDR
A Bayesian approach is developed which simultaneously models both the clinical effectiveness data and the cost data, by modelling the individual components of a clinical trial consisting of 351 patients with advanced non-small cell lung cancer comparing chemotherapy with standard palliative care.

A Framework for Addressing Structural Uncertainty in Decision Models

TLDR
The authors show how 2 recent research proposals represent parts of a framework to formally account for all common structural uncertainties in decision analytic models for antiplatelet therapies for vascular disease and new biologic drugs for the treatment of active psoriatic arthritis.

How Sensitive Are Cost-Effectiveness Analyses to Choice of Parametric Distributions?

  • S. ThompsonR. Nixon
  • Medicine
    Medical decision making : an international journal of the Society for Medical Decision Making
  • 2005
TLDR
Using the lognormal distribution led to the conclusion that rMRI was cost-effective for a range of willingness-to-pay values where assuming a gamma or normal distribution did not.

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
...