Journal of evaluation in clinical practice · 2026
Reallocating Surgical Activity to Expand Critical Care Capacity During the SARS-CoV-2 Pandemic: A Descriptive and Analytical Study in a French University Hospital Network.
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Botrel Thomas, Moukebel Nesrine, Legros Benjamin, Menegaux Fabrice, Puybasset Louis, Rufat Pierre, Jouini Oualid, Raux Mathieu
Аннотация
RATIONALE: The ability to anticipate ICU beds mobilizable through elective surgical postponements during health system shocks remains poorly quantified.
AIMS AND OBJECTIVES: Using real-world COVID-19 deprogramming data, we combined a classification of acceptable surgical deferral times with predictive models of expected surgical activity to estimate ICU capacity that can be generated in crisis scenarios.
METHOD: We conducted a retrospective time-series analysis of all surgical procedures performed from 2017 to 2021 in three AP-HP university hospitals. Procedures were classified as non-deferrable (red), deferrable < 1 month (orange), or > 1 month (green). Expected weekly surgical volumes for 2020-2021 without pandemic disruption were predicted using models trained on 2017-2018 and validated on 2019 (XGBoost, Holt-Winters). Multivariable linear regression quantified the association between postponed procedures and ICU beds opened, enabling projection of capacity gains under different postponement scenarios.
RESULTS: Among 196,469 procedures, 59% were red, 20% orange, and 21% green. Surgical activity declined by 13% in 2020% and 8% in 2021, while ICU capacity increased by up to 85 and 46 beds, respectively. Reductions were mainly driven by postponement of green procedures (IRR 0.78 [0.75-0.80]). Only postponed green procedures were significantly associated with ICU bed expansion (β = 0.75, 95% CI 0.53-0.97; p < 0.001), accounting for 34.6% of ICU bed demand.
CONCLUSION: Clinically acceptable postponement of low-priority elective surgery contributes substantially to ICU surge capacity. Integrating prioritization and predictive modeling into preparedness strategies may support balanced, data-driven responses to future healthcare system shocks.
AIMS AND OBJECTIVES: Using real-world COVID-19 deprogramming data, we combined a classification of acceptable surgical deferral times with predictive models of expected surgical activity to estimate ICU capacity that can be generated in crisis scenarios.
METHOD: We conducted a retrospective time-series analysis of all surgical procedures performed from 2017 to 2021 in three AP-HP university hospitals. Procedures were classified as non-deferrable (red), deferrable < 1 month (orange), or > 1 month (green). Expected weekly surgical volumes for 2020-2021 without pandemic disruption were predicted using models trained on 2017-2018 and validated on 2019 (XGBoost, Holt-Winters). Multivariable linear regression quantified the association between postponed procedures and ICU beds opened, enabling projection of capacity gains under different postponement scenarios.
RESULTS: Among 196,469 procedures, 59% were red, 20% orange, and 21% green. Surgical activity declined by 13% in 2020% and 8% in 2021, while ICU capacity increased by up to 85 and 46 beds, respectively. Reductions were mainly driven by postponement of green procedures (IRR 0.78 [0.75-0.80]). Only postponed green procedures were significantly associated with ICU bed expansion (β = 0.75, 95% CI 0.53-0.97; p < 0.001), accounting for 34.6% of ICU bed demand.
CONCLUSION: Clinically acceptable postponement of low-priority elective surgery contributes substantially to ICU surge capacity. Integrating prioritization and predictive modeling into preparedness strategies may support balanced, data-driven responses to future healthcare system shocks.