Practical issues in operationalizing the design and outcome evaluation of cluster randomized trials

Abstract

Trial designs using cluster-level randomization are necessary when interventions have intended effects that cannot be measured with individual randomization. When an intervention is intrinsically only able to be delivered to a cluster or when implementation of an individual level intervention is only feasibly implemented at a cluster level, cluster-level randomization is required. In designing the strategy for evaluation of the primary outcome of a cluster randomized trial, there are a multitude of important decisions to consider. While these decisions are guided primarily by the intervention—who benefits, what is the intended effect and when will it be achieved—there are important detailed choices that affect potential bias and statistical power, and implementation considerations that require compromise for considerations of feasibility and practicality. Through the lens of three large completed cluster randomized trials in HIV prevention, we present specific choices made for the overall evaluation plan, together with some of the detailed considerations, compromises and modifications that occurred during trial implementation.