Related Experiment Videos
Congenital Heart Surgery Case Mix Across North American Centers and Impact on Performance Assessment
Sara K Pasquali1, Amelia S Wallace2, J William Gaynor3
1Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, Ann Arbor, Michigan.
Insights
Congenital heart surgery case mix varies widely. Using benchmark operations for performance assessment offers less heterogeneity but lower statistical power, impacting center classification.
Area of Science:
- Cardiovascular Surgery
- Pediatric Cardiac Surgery
- Healthcare Quality Assessment
Background:
- Assessing performance in congenital heart surgery is complex due to diverse patient conditions and procedures.
- Understanding case mix variation across surgical centers is crucial for accurate performance evaluation.
Purpose of the Study:
- To describe the current case mix in congenital heart surgery across multiple centers.
- To evaluate performance assessment methodologies using all cardiac operations versus a benchmark subset.
- To analyze the implications of different methodologies on center performance classification.
Main Methods:
- Analysis of data from 119 centers in the Society of Thoracic Surgeons Congenital Heart Surgery Database (2010-2014).
- Description of index operation types and frequency across centers.
- Evaluation and classification of center performance (risk-adjusted operative mortality) using two approaches: all eligible operations versus benchmark operations.
Main Results:
- A total of 207 operation types were performed across 112,140 cases.
- Significant variation (7.9-fold) existed in the proportion of high-complexity cases (STAT 5) across centers.
- Benchmark operations, comprising 36% of cases, were performed by most centers; however, this methodology showed lower statistical power (35% meeting sample size thresholds vs. 78% for all operations) and led to performance classification changes for 15% of centers.
Conclusions:
- Wide variation in case mix necessitates careful consideration for performance assessment in congenital heart surgery.
- Benchmark-based metrics offer reduced heterogeneity but decreased statistical power, potentially altering performance classifications.
- Findings highlight the importance of selecting appropriate target populations and interpreting metrics cautiously for optimizing performance assessment.
Background:
Performance assessment in congenital heart surgery is challenging due to the wide heterogeneity of disease. We describe current case mix across centers, evaluate methodology inclusive of all cardiac operations versus the more homogeneous subset of Society of Thoracic Surgeons benchmark operations, and describe implications regarding performance assessment.
Methods:
Centers (n = 119) participating in the Society of Thoracic Surgeons Congenital Heart Surgery Database (2010 through 2014) were included. Index operation type and frequency across centers were described. Center performance (risk-adjusted operative mortality) was evaluated and classified when including the benchmark versus all eligible operations.
Results:
Overall, 207 types of operations were performed during the study period (112,140 total cases). Few operations were performed across all centers; only 25% were performed at least once by 75% or more of centers. There was 7.9-fold variation across centers in the proportion of total cases comprising high-complexity cases (STAT 5). In contrast, the benchmark operations made up 36% of cases, and all but 2 were performed by at least 90% of centers. When evaluating performance based on benchmark versus all operations, 15% of centers changed performance classification; 85% remained unchanged. Benchmark versus all operation methodology was associated with lower power, with 35% versus 78% of centers meeting sample size thresholds.
Conclusions:
There is wide variation in congenital heart surgery case mix across centers. Metrics based on benchmark versus all operations are associated with strengths (less heterogeneity) and weaknesses (lower power), and lead to differing performance classification for some centers. These findings have implications for ongoing efforts to optimize performance assessment, including choice of target population and appropriate interpretation of reported metrics.