Predictors of cumulative cost for patients with severe aortic stenosis referred for surgical or transcatheter aortic valve replacement: a population-based study in Ontario, Canada.

AIMS: Transcatheter aortic valve replacement (TAVR) as an alternative to surgical aortic valve replacement (SAVR) has transformed severe aortic stenosis (AS) management. Our aim was understand AS cost drivers from referral to 1-year post-procedure. METHODS AND RESULTS: We identified patients referred for either TAVR/SAVR between 1 April 2015 and 31 March 2018, with follow-up until 31 March 2019 in Ontario, Canada. We stratified costs into (i) a referral phase, (ii) a procedural phase from the procedure date to 60 days post-procedure, and (iii) post-procedure phase from 61 days to 1 year. Multivariable regression modelling using generalized linear models with a log link gamma distribution was used to identify cost drivers in each phase. The study cohort included 12 086 AS patients; 4832 were referred for TAVR and 7254 were referred for SAVR. The median cost for TAVR was higher than SAVR in the referral ($3593 vs. $2944) and post-procedural ($5938 vs. $3257) phases. In contrast, for the procedural phase, SAVR had a median cost of $29 756 vs. $27 907 for TAVR. Predictors of high cost in the referral phase were longer wait-time, and an urgent in-hospital procedure. In the procedural phase, procedural complications were the major drivers of higher cost. In the post-procedural phase, patient co-morbidities were the major drivers, specifically dialysis, liver disease, cancer, peripheral vascular disease, and diabetes mellitus. CONCLUSION: We identified distinct patterns of cost accumulation and modifiable drivers for SAVR compared with TAVR; these drivers may guide clinical and health policy decisions to make AS care more efficient.

The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic.

In Ontario on March 16, 2020, a directive was issued to all acute care hospitals to halt nonessential procedures in anticipation of a potential surge in COVID-19 patients. This included scheduled outpatient cardiac surgical and interventional procedures that required the use of intensive care units, ventilators, and skilled critical care personnel, given that these procedures would draw from the same pool of resources required for critically ill COVID-19 patients. We adapted the COVID-19 Resource Estimator (CORE) decision analytic model by adding a cardiac component to determine the impact of various policy decisions on the incremental waitlist growth and estimated waitlist mortality for 3 key groups of cardiovascular disease patients: coronary artery disease, valvular heart disease, and arrhythmias. We provided predictions based on COVID-19 epidemiology available in real-time, in 3 phases. First, in the initial crisis phase, in a worst case scenario, we showed that the potential number of waitlist related cardiac deaths would be orders of magnitude less than those who would die of COVID-19 if critical cardiac care resources were diverted to the care of COVID-19 patients. Second, with better local epidemiology data, we predicted that across 5 regions of Ontario, there may be insufficient resources to resume all elective outpatient cardiac procedures. Finally in the recovery phase, we showed that the estimated incremental growth in waitlist for all cardiac procedures is likely substantial. These outputs informed timely data-driven decisions during the COVID-19 pandemic regarding the provision of cardiovascular care.