BACKGROUND: Quality initiatives are increasingly focusing on the quality of oncologic surgery. However, there is concern that a lack of cancer-specific variables may make risk-adjusted hospital quality comparisons inadequate. Our objective was to assess whether hospital quality rankings for cancer surgery are influenced by the addition of cancer-specific variables to the risk-adjusted models. METHODS: Patients from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) and National Cancer Data Base (NCDB) who underwent colon or rectal resection for cancer were linked (2006-2008). Hierarchical models were developed predicting ACS NSQIP outcomes based on ACS NSQIP only vs a model using NSQIP and NCDB-derived cancer variables (e.g., stage and neoadjuvant therapy). Changes in hospital quality rankings were compared. RESULTS: A total of 11,405 patients underwent colon (n = 9,678, 146 hospitals) or rectal (n = 1,727, 135 hospitals) resection for cancer (2006-2008). Hospital-level complication rates (and standard deviation) after colon surgery were 2.2 % (±2.7 %) for mortality and 17.2 % (±8.7 %) for serious morbidity. After rectal cancer resection, complication rates were 0.9 % (±3.8 %) for mortality and 22.3 % (±20.4 %) for serious morbidity. When cancer-specific variables were included in risk-adjustment, outlier agreement was very good (kappa >0.85), and hospital odds ratio correlations were nearly identical (R > 0.98) for all outcomes assessed. Median changes in hospital rankings with the addition of the cancer-specific variables ranged from 1 to 2 after colon resection to 2-4 after rectal resection. CONCLUSIONS: Addition of the available cancer-specific variables to risk-adjustment models did not affect hospital quality rankings for cancer surgery. Existing ACS NSQIP risk-adjustment variables appears to be sufficient for accurate comparisons of hospital quality.
BACKGROUND: Quality initiatives are increasingly focusing on the quality of oncologic surgery. However, there is concern that a lack of cancer-specific variables may make risk-adjusted hospital quality comparisons inadequate. Our objective was to assess whether hospital quality rankings for cancer surgery are influenced by the addition of cancer-specific variables to the risk-adjusted models. METHODS:Patients from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) and National Cancer Data Base (NCDB) who underwent colon or rectal resection for cancer were linked (2006-2008). Hierarchical models were developed predicting ACS NSQIP outcomes based on ACS NSQIP only vs a model using NSQIP and NCDB-derived cancer variables (e.g., stage and neoadjuvant therapy). Changes in hospital quality rankings were compared. RESULTS: A total of 11,405 patients underwent colon (n = 9,678, 146 hospitals) or rectal (n = 1,727, 135 hospitals) resection for cancer (2006-2008). Hospital-level complication rates (and standard deviation) after colon surgery were 2.2 % (±2.7 %) for mortality and 17.2 % (±8.7 %) for serious morbidity. After rectal cancer resection, complication rates were 0.9 % (±3.8 %) for mortality and 22.3 % (±20.4 %) for serious morbidity. When cancer-specific variables were included in risk-adjustment, outlier agreement was very good (kappa >0.85), and hospital odds ratio correlations were nearly identical (R > 0.98) for all outcomes assessed. Median changes in hospital rankings with the addition of the cancer-specific variables ranged from 1 to 2 after colon resection to 2-4 after rectal resection. CONCLUSIONS: Addition of the available cancer-specific variables to risk-adjustment models did not affect hospital quality rankings for cancer surgery. Existing ACS NSQIP risk-adjustment variables appears to be sufficient for accurate comparisons of hospital quality.
Authors: Zaid M Abdelsattar; Robert W Krell; Darrell A Campbell; Samantha Hendren; Sandra L Wong Journal: J Am Coll Surg Date: 2014-05-02 Impact factor: 6.113
Authors: Ira L Leeds; Joseph K Canner; Jonathan E Efron; Nita Ahuja; Elliott R Haut; Elizabeth C Wick; Fabian M Johnston Journal: J Surg Res Date: 2017-09-18 Impact factor: 2.192
Authors: Jessica A Lavery; Allison Lipitz-Snyderman; Diane G Li; Peter B Bach; Katherine S Panageas Journal: J Eval Clin Pract Date: 2019-05-09 Impact factor: 2.431