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This JAMA Guide to Statistics and Methods describes the reasons for using cluster randomization in a clinical trial and how to analyze and interpret the results from a trial that did.
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Sometimes a new treatment is best introduced to an entire group of patients rather than to individual patients. Examples include when the new approach requires procedures be followed by multiple members of a health care team or when the new technique is applied to the environment of care (eg, a method for cleaning a hospital room before it is known which patient will be assigned the room). This avoids confusion that could occur if all caregivers had to keep track of which patients were being treated the old way and which were being treated the new way.
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One approach to evaluate the efficacy of such treatments—treatments for which the application typically involves changes at the level of the health care practice, hospital unit, or even health care system—is to conduct a cluster randomized trial. In a cluster randomized trial, study participants are randomized in groups or clusters so that all members within a single group are assigned to either the experimental intervention or the control.1,2 This contrasts with the more familiar randomized clinical trial (RCT) in which randomization occurs at the level of the individual participant, and the treatment assigned to one study participant is essentially independent of the treatment assigned to any other. In a cluster randomized trial, the cluster is the unit randomized, whereas in a traditional RCT, the individual study participant is randomized. In both types of trials, however, the outcomes of interest are recorded for each participant individually.
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Although there are both theoretical and pragmatic reasons for using cluster randomization in a clinical trial, doing so introduces a fundamental challenge to those analyzing and interpreting the results of the trial: study participants from the same cluster (eg, patients treated within the same medical practice or hospital unit) tend to be more similar to each other than participants from different clusters.2 This nearly universal fact violates a common assumption of most statistical tests, namely, that individual observations are independent of each other. To obtain valid results, a cluster randomized trial must be analyzed using statistical methods that account for the greater similarity between individual participants from the same cluster compared with those from different clusters.2-4
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In a JAMA article, Curley et al5 reported the results of the RESTORE trial, a cluster randomized clinical trial evaluating a nurse-implemented, goal-directed sedation protocol for children with acute respiratory failure receiving mechanical ventilation in the intensive care setting, comparing this approach with usual care. The trial evaluated the primary hypothesis that the intervention group—patients treated in intensive care units (ICUs) using the goal-directed sedation protocol—would have a shorter duration of mechanical ventilation. Thirty-one pediatric ICUs, the “clusters,” were randomized to either implement the goal-directed sedation ...