How should cost data in pragmatic randomised trials be analysed?

Pragmatic randomised trials are usually large scale multicentre studies in which interventions or medical policies are compared in a realistic setting.1 The intention is that conclusions from these trials, if accepted, can be adopted directly into medical practice.2 Economic evaluations carried out alongside these trials are increasingly common because it is often important to assess costs and cost effectiveness as well as clinical outcomes.3 Costs are usually derived from information about the quantity of healthcare resources used by each patient in the trial. The quantities of each resource used are multiplied by fixed unit cost values and are then summed over the separate types of resource to give a total cost per patient.4 Distribution of costs from a trial comparing endometrial resection with hysterectomy in women with menorrhagia. Costs are based on health resource use from randomisation to two years; they include preoperative, operative, hospital stay, complications, retreatment, and primary care components5 This information leads to a range of different costs across participants in the trial. As an example, the figure shows the distribution of costs in women with menorrhagia randomised to treatment with endometrial resection or abdominal hysterectomy.5 Such highly skewed distributions are typical of cost data; the long right hand tail reflects the fact that some patients incur high costs because of factors such as medical complications, reoperation, or extended hospital stay. ### Summary points Health economic evaluations are now commonly included in pragmatic clinical trials that inform policy decisions Despite the usual skewness in the distribution of costs, it is the arithmetic mean that is the most informative measure Measures other than the arithmetic mean do not provide information about the cost of treating all patients, which is needed as the basis for healthcare policy decisions Statistical analysis based on transforming cost data or …