The effect of cluster randomization on sample size in prevention research.

BACKGROUND: This paper concerns the issue of cluster randomization in primary care practice intervention trials. We present information on the cluster effect of measuring the performance of various preventive maneuvers between groups of physicians based on a successful trial. We discuss the intracluster correlation coefficient of determining the required sample size and the implications for designing randomized controlled trials where groups of subjects (e.g., physicians in a group practice) are allocated at random. METHODS: We performed a cross-sectional study involving data from 46 participating practices with 106 physicians collected using self-administered questionnaires and a chart audit of 100 randomly selected charts per practice. The population was health service organizations (HSOs) located in Southern Ontario. We analyzed performance data for 13 preventive maneuvers determined by chart review and used analysis of variance to determine the intraclass correlation coefficient. An index of "up-to-datedness" was computed for each physician and practice as the number of a recommended preventive measure done divided by the number of eligible patients. An index called "inappropriateness" was computed in the same manner for the not-recommended measures. The intraclass correlation coefficients for 2 key study outcomes (up-to-datedness and inappropriateness) were also calculated and compared. RESULTS: The mean up-to-datedness score for the practices was 53.5% (95% confidence interval [CI], 51.0%-56.0%), and the mean inappropriateness score was 21.5% (95% CI, 18.1%-24.9%). The intraclass correlation for up-to-datedness was 0.0365 compared with inappropriateness at 0.1790. The intraclass correlation for preventive maneuvers ranged from 0.005 for blood pressure measurement to 0.66 for chest radiographs of smokers, and as a consequence required the sample size ranged from 20 to 42 physicians per group. CONCLUSIONS: Randomizing by practice clusters and analyzing at the level of the physician has important implications for sample size requirements. Larger intraclass correlations indicate interdependence among the physicians within a cluster; as a consequence, variability within clusters is reduced, and the required sample size increased. The key finding that many potential outcome measures perform differently in terms of the intracluster correlation reinforces the need for researchers to carefully consider the selection of outcome measures and adjust sample sizes accordingly when the unit of analysis and randomization are not the same.

Process evaluation of a tailored multifaceted approach to changing family physician practice patterns improving preventive care.

BACKGROUND: We conducted a process evaluation of a multifaceted outreach facilitation intervention to document the extent to which the intervention was implemented with fidelity. We also hoped to gain insight into how facilitation worked to improve preventive performance. METHODS: We used 5 data collection tools to evaluate the implementation of the intervention, and a combination of descriptive, quantitative, and qualitative analyses. Triangulation was used to attain a complete understanding of the quality of implementation. Twenty-two intervention practices with a total of 54 physicians participated in a randomized controlled trial that took place in Southwestern Ontario, Canada. The key measures of process were the frequency and time involved to deliver intervention components, the scope of the delivery and the utility of the components, and physician satisfaction with the intervention. RESULTS: Of the 7 components in the intervention model, prevention facilitators (PFs) visited the practice most often to deliver the audit and feedback, consensus building, and reminder system components. All the study practices received preventive performance audit and feedback, achieved consensus on a plan for improvement, and implemented a reminder system. Ninety percent of the practices implemented a customized flow sheet, and 10% used a computerized reminder system. Ninety-five percent of the intervention practices wanted critically appraised evidence for prevention, 82% participated in a workshop with opinion leaders in preventive care, and 100% received patient education materials in a binder. Content analysis of the physician interviews and bivariate analysis of physician self-reported changes between intervention and control group physicians revealed that the audit and feedback, consensus building, and development of reminder systems were the key intervention components. Ninety-five percent of the physicians were either satisfied or very satisfied with the intervention, and 90% would have been willing to have the PF continue working with their practice. CONCLUSIONS: Primary care practices in Ontario can implement significant changes in their practice environments that will improve preventive care activity with the assistance of a facilitator. The main components for creating change are audit and feedback of preventive performance, achieving consensus on a plan for improvement, and implementing a reminder system.