Validation of 5 key colonoscopy-related data elements from Ontario health administrative databases compared to the clinical record: a cross-sectional study

CMAJ Open. 2018 Aug 13;6(3):E330-E338. doi: 10.9778/cmajo.20180013. Print Jul-Sep 2018.


Background: Colonoscopy is used widely, but its quality is highly variable, which may adversely affect patients. Research and quality-improvement initiatives in a variety of jurisdictions have sought to address this issue, often supported by the use of health administrative data. As these data are generally not collected for these purposes, it is critical to measure their validity before use. The aim of this study was to validate health administrative data definitions for 5 key colonoscopy elements through comparison to the clinical record.

Methods: In a cross-sectional study, we randomly sampled 1968 colonoscopy and noncolonoscopy procedures performed at 23 hospitals and 5 nonhospital endoscopy clinics between April 2008 and March 2009 in Ontario. We compared definitions for 5 key colonoscopy elements (colonoscopy case, colonoscopy setting, colonoscopy completeness, anesthesiologist assistance and polypectomy) derived from the health administrative data to the clinical record. We calculated weighted and unweighted sensitivity, specificity and positive predictive value, adjusted for clustering of patients within physicians, for each definition relative to the reference standard.

Results: We abstracted 1845 records; in 1282 cases (69.5%), colonoscopy was intended or performed. The weighted sensitivity and specificity of colonoscopy case, nonhospital colonoscopy setting and anesthesiologist assistance exceeded 95%. The weighted sensitivity for colonoscopy completeness and polypectomy exceeded 95%, but specificity was less than 90%.

Interpretation: Ontario health administrative data definitions for 5 key colonoscopy data elements performed well, with sensitivity and specificity values acceptable for use in research and quality-improvement initiatives. In jurisdictions where health administrative data are similarly used for research or quality improvement, similar studies could be considered.