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Ann Thorac Surg ; 110(6): 2020-2025, 2020 12.
Article in English | MEDLINE | ID: covidwho-165410


Background: The coronavirus disease 2019 (COVID-19) pandemic has dramatically reduced adult cardiac surgery case volumes as institutions and surgeons curtail nonurgent operations. There will be a progressive increase in deferred cases during the pandemic that will require completion within a limited time frame once restrictions ease. We investigated the impact of various levels of increased postpandemic hospital operating capacity on the time to clear the backlog of deferred cases. Methods: We collected data from 4 cardiac surgery programs across 2 health systems. We recorded case rates at baseline and during the COVID-19 pandemic and created a mathematical model to quantify the cumulative surgical backlog based on the projected pandemic duration. We then used the model to predict the time required to clear the backlog depending on the level of increased operating capacity. Results: Cardiac surgery volumes fell to 54% of baseline after restrictions were implemented. Assuming a service restoration date of either June 1 or July 1, we calculated the need to perform 216% or 263% of monthly baseline volume, respectively, to clear the backlog in 1 month. The actual duration required to clear the backlog highly depends on hospital capacity in the post-COVID period, and ranges from 1 to 8 months, depending on when services are restored and the degree of increased capacity. Conclusions: Cardiac surgical operating capacity during the COVID-19 recovery period will have a dramatic impact on the time to clear the deferred cases backlog. Inadequate operating capacity may cause substantial delays and increase morbidity and mortality. If only prepandemic capacity is available, the backlog will never clear.

Betacoronavirus , Cardiac Surgical Procedures/statistics & numerical data , Coronavirus Infections/epidemiology , Infection Control/organization & administration , Pneumonia, Viral/epidemiology , Surge Capacity/statistics & numerical data , COVID-19 , Coronavirus Infections/prevention & control , Elective Surgical Procedures/statistics & numerical data , Humans , Models, Statistical , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Procedures and Techniques Utilization , SARS-CoV-2