Abstract
Public reporting of hospital-level outcomes is increasingly common as a means to target quality improvement strategies to ensure the delivery of optimal care. Despite the rapid dissemination of transcatheter aortic valve replacement (TAVR), there is a paucity of reliable case-mix adjustment models for hospital profiling in TAVR. Our objective was to develop models for calculating risk-standardized all-cause mortality rates (RSMR) post-TAVR. In this population-based study in Ontario, Canada, we identified all patients that underwent a TAVR procedure between April 1, 2012 and March 31, 2016. For each hospital, we calculated 30-day and 1-year RSMR, using 2-level hierarchical logistic regression models that accounted for patient-specific demographic and clinical characteristics as well as the clustering of patients within the same hospital using a hospital-specific random effects. We classified each hospital into one of three groups: performing worse than expected, better than expected, or performing as expected, based on whether the 95% confidence interval (CI) of the RSMR was above, below or included the provincial average mortality rate respectively. Our cohort consisted of 2,129 TAVR procedures performed at 10 hospitals. The observed mortality was 7.0% at 30-days and 16.4% at one-year with a range of 4%-10% and 8%-22% respectively across hospitals. We developed case-mix adjustment models using 28 clinically relevant, available variables. Using 30-days and one-year RSMR to profile each hospital, we found that all hospitals performed as expected, with 95% CI that included the provincial average. We found no significant inter-hospital variation in RSMR among hospitals, suggesting that quality improvement efforts should be directed at aspects other than the variation in observed mortality.View Large Image Figure ViewerDownload Hi-res image Download (PPT)
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