A Bayesian Net Benefit Approach to Cost-effectiveness Analysis in Health Technology Assessment
The economic literature on cost-effectiveness analysis in the context of decisions by health technology assessment agencies assumes as the quantity of interest a linear combination of the mean of the sampling distribution of the effectiveness and the cost. We argue that this is not always reasonable. Our reasons for this assertion are that (i) treatments are compared on the basis of mean values, and for some useful models the mean of the distribution of the cost, which is conditional on the available data, does not exist, and (ii) even for models for which the mean does exist, it might not constitute an accurate reflection of the distribution. This paper presents a general Bayesian cost-effectiveness analysis of a single treatment, where the quantity of interest is the distribution, conditional on the data, of the net benefit. This approach permits a natural extension to several treatments, which enables us to make a statistical comparison. Illustrations with treatment comparisons for real and simulated data are given.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 16 (2009)
Issue (Month): 3 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/CIJB20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/CIJB20|
When requesting a correction, please mention this item's handle: RePEc:taf:ijecbs:v:16:y:2009:i:3:p:323-345. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.