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Bayesian methods in health economics: uncertainty in health economic evaluation 3

Part 3 of 5
Published on February 16, 2009 Reviewed on March 30, 2022   44 min

A selection of talks on Methods

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0:00
Hello, I'm Tony O'Hagan. Welcome to the third talk in my series, Bayesian Methods in Health Economics. This talk is entitled Uncertainty in Health Economic Evaluation.
0:15
You remember the outline of the course as a whole. The first two talks were about Bayesian methods in general, and you should have heard and understand those in order to proceed now to the third talk in which we begin a discussion of how Bayesian methods are used in health economics. This talk is about uncertainty and discusses the ways in which uncertainty influences our judgment about cost-effectiveness. Then the next talk, number 4, deals with the most important topic of probabilistic sensitivity analysis which continues in the fifth talk where we discuss how we formulate the inputs uncertainties that go into that analysis.
0:56
Here's the road map for this to talk. We begin by discussing the basic ideas and principles of cost-effectiveness, and how treatments can be compared on the basis of both their costs and their efficacy. But at that point, it's as if we knew all the parameters that we need to know. In practice, we don't know them. We're uncertain about them. Then we discuss uncertainty and how we make decisions about cost-effectiveness in the presence of uncertainty. Statistical methods are used in health economics in a number of ways, and one of these is to analyse data in which both costs and efficacy have been observed, typically in a clinical trial designed for both those things to be observed. That's a relatively small part of what health economics is really about, because such trials very rarely give you all the answers you need to judge cost-effectiveness. In practice health economists nearly always work on the basis of economic modelling, and this talk ends with a very brief introduction to economic models, and then the remaining two talks are all about economic modelling and uncertainty in those models.

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