A SMALL AREA SIMULATION APPROACH TO DETERMINING EXCESS VARIATION IN DENTAL PROCEDURE RATES

All small area analyses need to compare the observed variability in rates to that expected by chance alone, but the expected variability is usually not known. This paper uses patient-level data for five dental procedures to simulate the distributions of the summary statistics that are usually generated in such studies. These statistics are found to vary greatly even under the ''null hypothesis'' that all dentists are using procedures at the same rates. The simulated dentist rates are compared to observed rates obtained in a different study. These findings illustrate problems that can occur in small area analysis studies, and emphasize the importance of using statistical techniques that are appropriate for the data that are to be analyzed. Investigators should make every effort to obtain patient-level data, or at least to understand the underlying distribution of the number of procedures per patient, to avoid mistaking significant deviations from an incorrect model as evidence for significant variation among small areas.