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J Gastrointest Surg ; 25(1): 260-268, 2021 01.
Article in English | MEDLINE | ID: covidwho-680287

ABSTRACT

BACKGROUND: All elective surgeries have been postponed at our institution starting 3/16/20 due to the COVID-19 pandemic. We assessed changes in hospital resource utilization and estimated the future backlog of cases in the colorectal surgery division of a large safety-net hospital. METHODS: Patients undergoing colorectal procedures from 3/16/20 to 4/23/20 (COVID) were compared with those from January through June 2018 (historical). Resource utilization rates were calculated by weekly case volumes and hospital stay in each group. A future catch up timeframe and new wait times from scheduling to surgery dates were calculated. RESULTS: The COVID and historical groups included 13 and 239 patients, respectively. The COVID group showed a 74% relative decrease in weekly surgical case rates (9.2 to 2.4 patients per week). Both groups had similar lengths of stay. The COVID group had a longer average ICU stay (1.4 ± 2.5 days vs. 0.4 ± 1.2 days, P = 0.016) and a 132% increase in ICU resource utilization. Overall, the COVID group had a 48% relative decrease in hospital resource utilization, owing to reduced volume but higher acuity. If the surgery numbers returns to pre-COVID volumes, the calculated "catch up" times range from 4.6 weeks to 9.2 weeks. Wait times for new cases may increase by 70% compared with pre-COVID levels. CONCLUSION: Cancelling elective colorectal surgeries results in a decrease in overall but increase in ICU-specific resource utilization. Though necessary, cancellations result in an increasing backlog of cases that poses significant future logistical and clinical challenges in an already overburdened safety-net hospital. Effective triage systems will be critical to prioritize this backlog.


Subject(s)
COVID-19 , Colorectal Surgery , Digestive System Surgical Procedures/statistics & numerical data , Elective Surgical Procedures/statistics & numerical data , Intensive Care Units/statistics & numerical data , Length of Stay/statistics & numerical data , Adult , Aged , Female , Forecasting , Humans , Male , Middle Aged , Pandemics , SARS-CoV-2
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