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.

Objective

To examine the validity of hybrid quality measures that use both clinical registry and administrative claims data, capitalizing on the strengths of each data source.

Background

Previous studies demonstrate substantial disagreement between clinical registry and administrative claims data on the occurrence of postoperative complications. Clinical data have greater validity than claims data for quality measurement but can be burdensome for hospitals to collect.

Methods

American College of Surgeons National Surgical Quality Improvement Program records were linked to Medicare inpatient claims (2005-2008). National Quality Forum-endorsed risk-adjusted measures of 30-day postoperative complications or death assessed hospital quality for patients undergoing colectomy, lower extremity bypass, or all surgical procedures. Measures use hierarchical multivariable logistic regression to identify statistical outliers. Measures were applied using clinical data, claims data, or a hybrid of both data sources. Kappa statistics assessed agreement on determinations of hospital quality.

Results

A total of 111,984 patients participated from 206 hospitals. Agreement on hospital quality between clinical and claims data was poor. Hybrid models using claims data to risk-adjust complications identified by clinical data had moderate agreement with all clinical data models, whereas hybrid models using clinical data to risk-adjust complications identified by claims data had routinely poor agreement with all clinical data models.

Conclusions

Assessments of hospital quality differ substantially when using clinical registry versus administrative claims data. A hybrid approach using claims data for risk adjustment and clinical data for complications may be a valid alternative with lower data collection burden. For quality measures focused on postoperative complications to be meaningful, such policies should require, at a minimum, collection of clinical outcomes data.