Background: Cluster randomized trials increasingly are being used in health services research and in primary care, yet the majority of these trials do not account appropriately for the clustering in their analysis.
Objectives: We review the main implications of adopting a cluster randomized design in primary care and highlight the practical application of appropriate analytical techniques.
Methods: The application of different analytical techniques is demonstrated through the use of empirical data from a primary care-based case study.
Conclusion: Inappropriate analysis of cluster trials can lead to the presentation of inaccurate results and hence potentially misleading conclusions. We have demonstrated that adjustment for clustering can be applied to real-life data and we encourage more routine adoption of appropriate analytical techniques.