Statistical Methods for Cost-Effectiveness Analyses That Use Data from Cluster Randomized Trials

Abstract

Introduction. The best data for cost-effectiveness analyses (CEAs) of group-level interventions often come from cluster randomized trials (CRTs), where randomization is by cluster (e.g., the hospital attended), not by individual. Methods for these CEAs need to recognize both the correlation between costs and outcomes and that these data may be dependent on the cluster. General checklists and methodological guidance for critically appraising CEA ignore these issues. This article develops a new checklist and applies it in a systematic review of CEAs that use CRTs. Methods. The authors developed a checklist for CEAs that use CRTs, informed by a conceptual review of statistical methods. This checklist included criteria such as whether the analysis allowed for both clustering and the correlation between individuals’ costs and outcomes. The authors undertook a systematic literature review of full economic evaluations that used CRTs. The quality of studies was assessed with the new checklist and by the “Drummond checklist.” Results. The authors identified 62 papers that met the inclusion criteria. On average, studies satisfied 9 of the 10 criteria for the checklist but only 20% of criteria for the new checklist. More than 40% of studies adopted statistical methods that completely ignored clustering, and 75% disregarded any correlation between costs and outcomes. Only 4 studies employed appropriate statistical methods that allowed for both clustering and correlation. Conclusions. Most economic evaluations that use data from CRTs ignored clustering or correlation. Statistical methods that address these issues are available, and their use should be encouraged. The new checklist can supplement generic CEA guidelines and highlight where research practice can be improved.