Original articleClinical endoscopyIdentification of physicians with unusual performance in screening colonoscopy databases: a Bayesian approach

BackgroundThe adenoma detection rate (ADR) is an important surrogate measure of performance quality for screening colonoscopies.ObjectiveTo demonstrate how physicians with unusual performance concerning the adenoma detection rate may be identified in screening colonoscopy databases.DesignBayesian random-effects modeling and Winsorization of potential outliers were applied to develop a robust model for the majority of providers. Divergence was assessed with adjustment for multiple testing. The steps in the analysis were visualized by using funnel plots. Additionally, minimum requirements for the number of colonoscopies with 1 or more detected adenomas were derived.SettingData from 422 physicians offering screening colonoscopy and participating in a quality assurance program in Bavaria, Germany, were used.PatientsA total of 69,738 asymptomatic individuals 55 to 79 years of age.InterventionScreening colonoscopy.Main Outcome MeasurementsPhysician-specific ADRs.ResultsThe overall ADR in the sample was 26%. From an initial model, 62 physicians (15%) were identified as potential outliers. A model with normally distributed random effects was then chosen as the robust null model. Of the potential outliers, 10 (16%) were confirmed as physicians with unusual performance at a false discovery rate of 5%. For all of them, the observed ADR was lower than expected, and together they accounted for 1.4% of all included colonoscopies.LimitationsAnalysis of routine data.ConclusionThe applied statistical approach appears suitable to identify unusual performance in screening colonoscopy databases. Its application may help to evaluate and improve the quality of colonoscopy in population-based colorectal cancer screening programs.