Most health management programs, such as disease management or health promotion/wellness interventions, implement targeted interventions for an identified high-risk group, leaving the remaining non-managed lower-risk population as controls. This is problematic from an outcomes perspective...

Introduction: Frequently, within economic evaluations, data are subject to censoring, and ignoring censored data will lead to an underestimation of mean total costs. Several techniques have been published that can be used to estimate mean total costs and standard errors, and allow for censoring...

Evidence produced by multinational trial-based cost-effectiveness studies is often used to inform decisions concerning the adoption of new healthcare technologies. A key issue relating to the use of this type of evidence is the extent to which trial-wide economic results are applicable to every...

Sample size and power for cost-effectiveness analysis depend on assumptions about the difference in cost and effect, the standard deviations of cost and effect, the correlation of the difference in cost and effect, the α and β errors and maximum willingness to pay (W). The first seven of these...

The UK National Institute for Health and Clinical Excellence (NICE) has used its Single Technology Appraisal (STA) programme to assess several drugs for cancer. Typically, the evidence submitted by the manufacturer comes from one short-term randomized controlled trial (RCT) demonstrating...

Methods for determining sample size requirements for cost-effectiveness studies are reviewed and illustrated. Traditional methods based on tests of hypothesis and power arguments are given for the incremental cost-effectiveness ratio and incremental net benefit (INB). In addition, a full...

Basic sample size and power formulae for cost-effectiveness analysis have been established in the literature. These formulae are reviewed and the similarities and differences between sample size and power for cost-effectiveness analysis and for the analysis of other continuous variables such as...

Recently, enormous efforts to measure the quality of healthcare have been made to attain information on ways to improve the quality of healthcare. However, this area of research is still at an early stage of development and more research is required. This article outlines a framework by which...

Introduction: The ability of observational studies to draw conclusions on causal relationships between covariates and outcomes can be improved by incorporating randomly matched controls using the propensity scoring method. This procedure controls for pre-program differences between the enrolled...

Health economic modelling studies are of interest to many parties with different responsibilities and diverging interests. Therefore, it is obvious that recognising the relevance of statistical uncertainty and dealing with it appropriately are required to obtain unbiased results from health...