Optimal cost-effectiveness decisions: the role of the cost-effectiveness acceptability curve (CEAC), the cost-effectiveness acceptability frontier (CEAF), and the expected value of perfection information (EVPI).
OBJECTIVE
To demonstrate how the optimal decision and level of uncertainty associated with that decision, can be presented when assessing the cost-effectiveness of multiple options. To explore and explain potentially counterintuitive results that can arise when analyzing multiple options.


METHODS
A template was created, based on the assumption of multivariate normality, in order to replicate a previous analysis that compared the cost-effectiveness of multiple options. We used this template to explain some of the different shapes that the cost-effectiveness acceptability curve (CEAC), cost-effectiveness acceptability frontier (CEAF), and expected value of perfection information (EVPI) may take, with changing correlation structure and variance between the multiple options.


RESULTS
We show that it is possible for 1) an option that is subject to extended dominance to have the highest probability of being cost-effective for some values of the cost-effectiveness threshold; 2) the most cost-effective (optimal) option to never have the highest probability of being cost-effective; and 3) the EVPI to increase when the probability of making the wrong decision decreases. Changing the correlation structure between multiple options did not change the presentation of results on the cost-effectiveness plane.


CONCLUSIONS
The cost-effectiveness plane has limited use in representing the uncertainty surrounding multiple options as it cannot represent correlation between the options. CEACs can represent decision uncertainty, but should not be used to determine the optimal decision. Instead, the CEAF shows the decision uncertainty surrounding the optimal choice and this can be augmented by the EVPI to show the potential gains to further research.
Barton
Garry R
GR
School of Medicine, Health Policy and Practice, University of East Anglia, Norwich, UK. g.barton@uea.ac.uk
Briggs
Andrew H
AH
Fenwick
Elisabeth A L
EA
D001499:Bayes Theorem; D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data*; D003661:Decision Support Techniques; D006801:Humans; D018803:Models, Economic; D015233:Models, Statistical; D008962:Models, Theoretical; D015999:Multivariate Analysis; D011336:Probability; D012680:Sensitivity and Specificity; D035501:Uncertainty; D014481:United States