Cluster-randomized trials randomize entire groups of participants, instead of individual participants, to different treatment arms. For certain interventions (eg, institutional policies, processes of care, treatment algorithms), these designs protect against contamination between study arms. However, cluster trials are logistically complex to implement and have unique vulnerabilities that must be evaluated for accurate interpretation. Here, we provide a general overview of the design and statistical issues in cluster trials to facilitate their interpretation by clinicians.