The usefulness of matched pair randomization for medical practice-based research

To be feasible, study designs for most intervention research in primary care settings must limit the number of participating physicians, without sacrificing the statistical power required to test the research hypotheses. A model was developed to examine sample size and statistical power requirements when using the physicians' practice as the unit of analysis. Randomized designs using either matched or unmatched samples of practices were compared under varying conditions. When baseline variability is small or the number of practice pairs is large, matching at best marginally increases power. However, in the typical case when baseline variability is large or the number of practice pairs is small, matching substantially increases the power to find intervention effects with a smaller sample. Thus, matching prior to randomization could improve the design of many intervention studies in primary care settings.