Although cluster designs confer certain advantages in conducting PCTs, they are also characterized by significant theoretical limitations and implementation challenges (Torgerson et al. 2001) and careful consideration is needed before settling on a particular approach to randomization. The following assessment questions, adapted from Designing Multi-Center Cluster-Randomized Trials: An Introductory Toolkit (2014) may help clarify whether or not a CRT represents an appropriate design choice for answering a particular research question:
- Is the phenomenon of interest something that takes place primarily at the level of the individual patient or study participant (e.g., response to an experimental drug or comparator)? If so, a traditional RCT design may be most appropriate. However, if the phenomenon of interest affects individual patients but is primarily taking place at a different level (for example, whether implementation of new physician treatment guidelines is yielding better patient outcomes), a cluster-randomized design may be more appropriate.
- Is the proposed intervention delivered at the level of a group or organization rather than an individual study participant? For example, a study that investigated whether adoption of a new treatment guideline affected the efficiency of service provision across hospitals in a health system would lend itself to a cluster design.
- If individual participants are randomized, would it be difficult for physicians or other clinical staff to modify their approaches or behaviors in ways that allow contamination to be avoided? Similarly, is it likely that participants or study staff might have occasion or opportunity to discuss details of the study (“compare notes”) among themselves? If so, a cluster-randomized approach may be preferable for ensuring trial validity.
Finally, it is important to consider that any cluster-randomized design will introduce an important statistical effect known as clustering. When several participants (a cluster) are subjected to similar circumstances that may differ from those of other clusters, such as patients within the same ward being treated by the same providers, their outcomes can be correlated (please see also "Intraclass Correlation" under Analysis Plan). This important consideration should be addressed both when randomizing and when calculating the required sample size for a given power for the study.
For additional information about design considerations, please see Designing with Implementation and Dissemination in Mind.