Economic evaluation of health programmes Department of Epidemiology, Biostatistics and Occupational Health Class no. 20: More on dealing with uncertainty Nov 17, 2008

Plan of class  Net benefit framework  Cost-effectiveness acceptability curves  ‘Marrying econometrics and cost- effectiveness analysis’

Bootstrapped replications that fall in all 4 quadrants Source: Drummond & McGuire 2001, p. 193

Why is this a problem?  How do we construct a confidence interval when values within the interval fall into several quadrants?  Recall problem is: Negative ICERs are not transitive: an intermediate value can represent a more cost-effective ICER than more extreme values When the difference in effects is close to zero, the ICER becomes very large – and there is a discontinuity at zero.  As example shows, not at all clear how to define a confidence interval when replicates fall into all quadrants

The net-benefit framework (1) ICER = Intervention considered cost-effective if: λ : maximum amount decision-maker willing to pay per unit of health gain (or ceiling ratio)

The net benefit framework (2) Intervention is cost-effective if: We can trace the NMB as a function of λ, based on the sample values of mean difference in cost and effect:

Where NMB =0, λ (here represented as R T ) is equal to the ICER (see formula on previous page) What is slope of NMB line? Where does it intersect the y axis? How are the 95% C.I. lines calculated?

CONSTRUCTING A CEAC: For various values of RT, we can estimate the probability that the intervention is cost-effective by counting the proportion of points that lie below the corresponding line

Another cost-effectiveness acceptability curve (CEAC) Source: Drummond & McGuire 2001, p % CI undefined: Decision-maker cannot be willing to pay less than 0 for a gain in LYs

Using NMB to identify factors that influence cost-effectiveness (1) It is true that: However the difference in mean benefit between the experimental (subscript 1) and control (subscript 0) inverventions can be written:

Using NMB to identify factors that influence cost-effectiveness (2) We can define a NMB for each subject: We can then estimate the model, using OLS: (where t=1 if subject received new treatment, t=0 otherwise)

Using NMB to identify factors that influence cost-effectiveness (3) We can then extend this framework to estimate the partial effects of other covariaates: It then becomes possible to estimate the effects of factors such as age and sex on net monetary benefit – hence on cost-effectiveness