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BMC Med Res Methodol. 2012; 12: 97.
Published online 2012 July 11. doi:  10.1186/1471-2288-12-97
PMCID: PMC3406984

Validation of colorectal cancer surgery data from administrative data sources

Abstract

Background

Surgery is the primary treatment for colorectal cancer for both curative and palliative intent. Availability of high quality surgery data is essential for assessing many aspects of the quality of colorectal cancer care. The objective of this study was to determine the quality of different administrative data sources in identifying surgery for colorectal cancer with respect to completeness and accuracy.

Methods

All residents in Alberta, Canada who were diagnosed with invasive colorectal cancer in years 2000-2005 were identified from the Alberta Cancer Registry and included in the study. Surgery data for these patients were obtained from the Cancer Registry (which collects the date of surgery for which the primary tumor was removed) and compared to surgery data obtained from two different administrative data sources: Physician Billing and Hospital Inpatient data. Sensitivity, specificity, positive predictive value, negative predictive value and observed agreement were calculated compared to the Cancer Registry data.

Results

The Physician Billing data alone or combined with Hospital Inpatient data demonstrated equally high sensitivity (97% for both) and observed agreement with the Cancer Registry data (93% for both) for identifying surgeries. The Hospital Inpatient data, however, had the highest specificity (80%). The positive predictive value varied by disease stage and across data sources for stage IV (99% for stages I-III and 83-89% for stage IV), the specificity is better for colon cancer surgeries (72-85%) than for rectal cancer surgeries (60-73%); validation measures did not vary over time.

Conclusion

Physician Billing data identify the colorectal cancer surgery more completely than Hospital Inpatient data although both sources have a high level of completeness.

Keywords: Colorectal cancer, Surgery, Data validation, Administrative data, Sensitivity, Specificity, Positive predictive value, Negative predictive value

Articles from BMC Medical Research Methodology are provided here courtesy of BioMed Central