Economic evaluations are increasingly being conducted alongside clinical trials of health interventions, with resource consequences being estimated from stochastic data. It is, therefore, important that economic evaluation results, like the clinical results, reflect the underlying variance within the sample data. A statistical methodology, known as bootstrapping, has recently been put forward as a potential method for calculating confidence intervals for cost-effectiveness ratios, yet it is still unusual to see economic evaluations reporting confidence intervals. In this paper we demonstrate the practical application of bootstrapping using real data from clinical trials, and conclude that bootstrapping is easily transferable from theory to practice for the estimation of confidence intervals for cost-effectiveness ratios. We encourage further investigation into its applicability and use.