Abstract 16570: Benchmarking Risk-Adjusted Outcomes in Congenital Heart Surgery
Ram Kumar Subramanyan, Dylan Thibault, Sean OBrien, J W Gaynor, David M Shahian, Emile Bacha, Vinay Badhwar, Chris Caldarone, Joseph A Dearani, Felix Fernandez, Jeffrey P Jacobs, David M Overman, Sara K Pasquali, Tabitha Rainey, Jennifer Romano, Subhadra Shashidharan, James Tweddell, John E Mayer- Physiology (medical)
- Cardiology and Cardiovascular Medicine
Background: Robust models exist to predict risk-adjusted mortality following congenital heart surgery. It is known that underlying diagnosis modifies predicted risk of operations, and institution-level outcomes vary based on their unique case mix. We therefore evaluated risk-adjusted outcomes for a subset of diagnosis-procedure (D-P) combinations within the Society of Thoracic Surgeons' (STS) congenital heart surgery database (CHSD).
Methods: A clinician panel identified the most frequently encountered D-P combinations in CHSD between 07/2017 and 06/2021. Candidate modeling techniques were compared in a random 80% development cohort. Model performance was assessed using internal and cross-validation calibration, discrimination plots and optimism adjusted C-statistics. The final selected model was evaluated in the 20% validation sample.
Results: The chosen subset of D-P combinations represented 45,384 of 87,589 (52%) unique episodes of surgical care in CHSD during this time-period. The development cohort (36,350 episodes) had 1.8% mortality (667 deaths). All candidate models had excellent discrimination with C-statistics ranging from 0.862 to 0.876. The model with the best combination of discrimination, calibration, and clinical face validity was a modified version of the current STS mortality risk model. This version included all current risk model variables with the addition of indicator variables for D-P combinations. In the 20% validation sample (9,034 episodes), this model was well calibrated (Figure) and had excellent discrimination (C = 0.879).
Conclusion: We describe a cohort of D-P combinations widely encountered in the STS CHSD. Further, we refined the existing STS CHSD risk model for application to these D-P dyads to derive empirical risk-adjusted benchmark outcomes. This approach will benefit quality improvement efforts at an institutional level and may have implications for publicly reporting congenital heart surgery outcomes.