Comparison between clinical registry and medicare claims data on the classification of hospital quality of surgical care.Ann Surg. 2015 Feb; 261(2):290-6.AnnS
OBJECTIVE
To compare the classification of hospital statistical outlier status as better or worse performance than expected for postoperative complications using Medicare claims versus clinical registry data.
BACKGROUND
Controversy remains as to the most favorable data source for measuring postoperative complications for pay-for-performance and public reporting polices.
METHODS
Patient-level records (2005-2008) were linked between the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) and Medicare inpatient claims. Hospital statistical outlier status for better or worse performance than expected was assessed using each data source for superficial surgical site infection (SSI), deep/organ-space SSI, any SSI, urinary tract infection, pneumonia, sepsis, deep venous thrombosis, pulmonary embolism, venous thromboembolism, and myocardial infarction by developing hierarchical multivariable logistic regression models. Kappa statistics and correlation coefficients assessed agreement between the data sources.
RESULTS
A total of 192 hospitals with 110,987 surgical patients were included. Agreement on hospital rank for complication rates between Medicare claims and ACS-NSQIP was poor-to-moderate (weighted κ: 0.18-0.48). Of hospitals identified as statistical outliers for better or worse performance by Medicare claims, 26% were also identified as outliers by ACS-NSQIP. Of outliers identified by ACS-NSQIP, 16% were also identified as outliers by Medicare claims. Agreement between the data sources on hospital outlier status classification was uniformly poor (weighted κ: -0.02-0.34).
CONCLUSIONS
Despite using the same statistical methodology with each data source, classification of hospital outlier status as better or worse performance than expected for postoperative complications differed substantially between ACS-NSQIP and Medicare claims.
