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Ann Surg. 2013 Mar;257(3):483-9. doi: 10.1097/SLA.0b013e318273bf17.

Validity and feasibility of the american college of surgeons colectomy composite outcome quality measure.

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Division of Research and Optimal Patient Care, American College of Surgeons, Chicago, IL 60611, USA.



To develop a reliable, robust, parsimonious, risk-adjusted 30-day composite colectomy outcome measure.


A fundamental aspect in the pursuit of high-quality care is the development of valid and reliable performance measures in surgery. Colon resection is associated with appreciable morbidity and mortality and therefore is an ideal quality improvement target.


From 2010 American College of Surgeons National Surgical Quality Improvement Program data, patients were identified who underwent colon resection for any indication. A composite outcome of death or any serious morbidity within 30 days of the index operation was established. A 6-predictor, parsimonious model was developed and compared with a more complex model with more variables. National caseload requirements were calculated on the basis of increasing reliability thresholds.


From 255 hospitals, 22,346 patients were accrued who underwent a colon resection in 2010, most commonly for neoplasm (46.7%). A mortality or serious morbidity event occurred in 4461 patients (20.0%). At the hospital level, the median composite event rate was 20.7% (interquartile range: 15.8%-26.3%). The parsimonious model performed similarly to the full model (Akaike information criterion: 19,411 vs 18,988), and hospital-level performance comparisons were highly correlated (R = 0.97). At a reliability threshold of 0.4, 56 annual colon resections would be required and achievable at an estimated 42% of US and 69% of American College of Surgeons National Surgical Quality Improvement Program hospitals. This 42% of US hospitals performed approximately 84% of all colon resections in the country in 2008.


It is feasible to design a measure with a composite outcome of death or serious morbidity after colon surgery that has a low burden for data collection, has substantial clinical importance, and has acceptable reliability.

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