Background
As US healthcare increasingly focuses upon outcomes as a means for quantifying quality, there is a growing demand for risk models that can account for the variability of patients treated at different hospitals so that equitable comparisons between institutions can be made. We sought to apply aspects of prior risk-standardization methodology in order to begin development of a risk-standardization tool for the NCDR® IMPACT™ (Improving Pediatric and Adult Congenital Treatment) Registry.
Methods and Results
Using IMPACT, all patients undergoing diagnostic or interventional cardiac catheterization between January 2011 and March 2013 were identified. Multivariable hierarchical logistic regression was used to identify patient and procedural characteristics predictive of experiencing a major adverse event following cardiac catheterization. A total of 19,608 cardiac catheterizations were performed between January 2011 and March 2013. Amongst all cases, a major adverse event occurred in 378 (1.9%) of all cases. After multivariable adjustment, eight variables were identified as critical for risk-standardization: patient age, renal insufficiency, single-ventricle physiology, procedure-type risk group, low systemic saturation, low mixed venous saturation, elevated systemic ventricular end diastolic pressure, and elevated main pulmonary artery pressures. The model had good discrimination (C-statistic of 0.70), confirmed by bootstrap validation (validation C-statistic of 0.69).
Conclusions
Using prior risk-standardization efforts as a foundation, we developed and internally validated a model to predict the occurrence of a major adverse event following cardiac catheterization for congenital heart disease. Future efforts should be directed towards further refinement of the model variables within this large, multicenter dataset.