Abstract
Cost-effectiveness analysis, the most common type of economic evaluation, estimates
a new option's additional outcome in relation to its extra costs. This is crucial
to study within the clinical setting because funding for new treatments and interventions
is often linked to whether there is evidence showing they are a good use of resources.
This article describes how to analyze a cost-effectiveness dataset using the framework
of a net benefit regression. The process of creating estimates and characterizing
uncertainty is demonstrated using a hypothetical dataset. The results are explained
and illustrated using graphs commonly employed in cost-effectiveness analyses. We
conclude with a call to action for researchers to do more person-level cost-effectiveness
analysis to produce evidence of the value of new treatments and interventions. Researchers
can utilize cost-effectiveness analysis to compare new and existing treatment mechanisms.
Keywords
net benefit regression - cost-effectiveness analysis - economic evaluation - health
economics - cost–benefit analysis
