title: Identification of physicians with unusual performance in screening colonoscopy databases: a Bayesian approach.
abstract: 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.
  
  
  METHODS
  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.
  
  
  METHODS
  Data from 422 physicians offering screening colonoscopy and participating in a quality assurance program in Bavaria, Germany, were used.
  
  
  METHODS
  A total of 69,738 asymptomatic individuals 55 to 79 years of age.
  
  
  METHODS
  Screening colonoscopy.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  Analysis of routine data.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany.
authors.forename: Christian
authors.initials: C
authors.lastname: Stock
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany.
authors.forename: Lorenz
authors.initials: L
authors.lastname: Uhlmann
authors.affiliation: Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Hoffmeister
authors.affiliation: Department of General Practice and Health Services Research, University Hospital Heidelberg, Heidelberg, Germany.
authors.forename: Gunter
authors.initials: G
authors.lastname: Laux
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany.
authors.forename: Meinhard
authors.initials: M
authors.lastname: Kieser
authors.affiliation: Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
authors.forename: Hermann
authors.initials: H
authors.lastname: Brenner
mesh_terms: D000236:Adenoma / Q000175:diagnosis*; D000368:Aged; D001499:Bayes Theorem; D002983:Clinical Competence / Q000706:statistics & numerical data*; D003113:Colonoscopy / Q000592:standards* / Q000706:statistics & numerical data; D015179:Colorectal Neoplasms / Q000175:diagnosis*; D016208:Databases, Factual; D055088:Early Detection of Cancer / Q000592:standards* / Q000706:statistics & numerical data; D005260:Female; D005858:Germany; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*