The effect of nonmedical factors on variations in the performance of colonoscopy among different health care settings

Med Care. 2010 Feb;48(2):101-9. doi: 10.1097/MLR.0b013e3181c160ee.


Background: Previous published studies have shown significant variations in colonoscopy performance, even when medical factors are taken into account. This study aimed to examine the role of nonmedical factors (ie, embodied in health care system design) as possible contributors to variations in colonoscopy performance.

Methods: Patient data from a multicenter observational study conducted between 2000 and 2002 in 21 centers in 11 western countries were used. Variability was captured through 2 performance outcomes (diagnostic yield and colonoscopy withdrawal time), jointly studied as dependent variables, using a multilevel 2-equation system.

Results: Results showed that open-access systems and high-volume colonoscopy centers were independently associated with a higher likelihood of detecting significant lesions and longer withdrawal durations. Fee for service (FFS) payment was associated with shorter withdrawal durations, and so had an indirect negative impact on the diagnostic yield. Teaching centers exhibited lower detection rates and longer withdrawal times.

Conclusions: Our results suggest that gatekeeping colonoscopy is likely to miss patients with significant lesions and that developing specialized colonoscopy units is important to improve performance. Results also suggest that FFS may result in a lower quality of care in colonoscopy practice and highlight the fact that longer withdrawal times do not necessarily indicate higher quality in teaching centers.

Publication types

  • Comparative Study
  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Canada
  • Colonoscopy* / economics
  • Colonoscopy* / statistics & numerical data
  • Europe
  • Fee-for-Service Plans
  • Gatekeeping
  • Health Services Accessibility
  • Hospitals, Teaching
  • Humans
  • Likelihood Functions
  • Models, Econometric
  • Practice Patterns, Physicians'*
  • Predictive Value of Tests
  • Quality Indicators, Health Care
  • Quality of Health Care*
  • Regression Analysis
  • Reimbursement Mechanisms
  • Time Factors