Sourav K Bose1,2, Serena Dasani3,4, Sanford E Roberts4,5, Chris Wirtalla4,5, Ronald P DeMatteo5, Gerard M Doherty1, Rachel R Kelz2,4,5. 1. Department of Surgery, Brigham and Women's Hospital, Boston, Massachusetts. 2. Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania. 3. Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts. 4. Center for Surgery and Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania. 5. Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
Abstract
OBJECTIVE: We sought to quantify the financial impact of elective surgery cancellations in the US during COVID-19 and simulate hospitals' recovery times from a single period of surgery cessation. BACKGROUND: COVID-19 in the US resulted in cessation of elective surgery-a substantial driver of hospital revenue-and placed patients at risk and hospitals under financial stress. We sought to quantify the financial impact of elective surgery cancellations during the pandemic and simulate hospitals' recovery times. METHODS: Elective surgical cases were abstracted from the Nationwide Inpatient Sample (2016-2017). Time series were utilized to forecast March-May 2020 revenues and demand. Sensitivity analyses were conducted to calculate the time to clear backlog cases and match expected ongoing demand in the post-COVID period. Subset analyses were performed by hospital region and teaching status. RESULTS: National revenue loss due to major elective surgery cessation was estimated to be $22.3 billion (B). Recovery to market equilibrium was conserved across strata and influenced by pre- and post-COVID capacity utilization. Median recovery time was 12-22 months across all strata. Lower pre-COVID utilization was associated with fewer months to recovery. CONCLUSIONS: Strategies to mitigate the predicted revenue loss of $22.3B due to major elective surgery cessation will vary with hospital-specific supply-demand equilibrium. If patient demand is slow to return, hospitals should focus on marketing of services; if hospital capacity is constrained, efficient capacity expansion may be beneficial. Finally, rural and urban nonteaching hospitals may face increased financial risk which may exacerbate care disparities.
OBJECTIVE: We sought to quantify the financial impact of elective surgery cancellations in the US during COVID-19 and simulate hospitals' recovery times from a single period of surgery cessation. BACKGROUND: COVID-19 in the US resulted in cessation of elective surgery-a substantial driver of hospital revenue-and placed patients at risk and hospitals under financial stress. We sought to quantify the financial impact of elective surgery cancellations during the pandemic and simulate hospitals' recovery times. METHODS: Elective surgical cases were abstracted from the Nationwide Inpatient Sample (2016-2017). Time series were utilized to forecast March-May 2020 revenues and demand. Sensitivity analyses were conducted to calculate the time to clear backlog cases and match expected ongoing demand in the post-COVID period. Subset analyses were performed by hospital region and teaching status. RESULTS: National revenue loss due to major elective surgery cessation was estimated to be $22.3 billion (B). Recovery to market equilibrium was conserved across strata and influenced by pre- and post-COVID capacity utilization. Median recovery time was 12-22 months across all strata. Lower pre-COVID utilization was associated with fewer months to recovery. CONCLUSIONS: Strategies to mitigate the predicted revenue loss of $22.3B due to major elective surgery cessation will vary with hospital-specific supply-demand equilibrium. If patient demand is slow to return, hospitals should focus on marketing of services; if hospital capacity is constrained, efficient capacity expansion may be beneficial. Finally, rural and urban nonteaching hospitals may face increased financial risk which may exacerbate care disparities.
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