Identification of physicians with unusual performance in screening colonoscopy databases: a Bayesian approach
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Published on: September 27, 2024
Christian Stock1, Lorenz Uhlmann1, Michael Hoffmeister2
1Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany.
Background:
The adenoma detection rate (ADR) is an important surrogate measure of performance quality for screening colonoscopies.
Objective:
To demonstrate how physicians with unusual performance concerning the adenoma detection rate may be identified in screening colonoscopy databases.
Design:
Bayesian 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.
Setting:
Data from 422 physicians offering screening colonoscopy and participating in a quality assurance program in Bavaria, Germany, were used.
Patients:
A total of 69,738 asymptomatic individuals 55 to 79 years of age.
Intervention:
Screening colonoscopy.
Main Outcome Measurements:
Physician-specific ADRs.
Results:
The 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.
Limitations:
Analysis of routine data.
Conclusion:
The 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.
