The Power of Modeling in Emergency Preparedness for COVID-19: A Moonshot Moment for Hospitals. (16th October 2022)

• Record Type: Journal Article
• Authors: Safavi, Kyan C.; Prestipino, Ann L.; Zenteno Langle, Ana Cecilia; Copenhaver, Martin; Hu, Michael; Daily, Bethany; Koehler, Allison; Biddinger, Paul D.; Dunn, Peter F.
• Is Part Of: Disaster medicine and public health preparedness. Volume 16:Number 5(2022)
• Page Start: 2182
• Page End: 2184
• Publication Date: 2022-10-16
• Subjects: hospital bed capacity -- health care facilities -- manpower and services -- surge capacity -- decision making -- organizational -- delivery of health care; Disaster medicine -- Periodicals; Emergency management -- Planning -- Periodicals; Public health -- Periodicals; 363.34
• DOI: 10.1017/dmp.2021.51
• Languages: English
• ISSNs: 1935-7893

Abstract

Abstract: Before coronavirus disease 2019 (COVID-19), few hospitals had fully tested emergency surge plans. Uncertainty in the timing and degree of surge complicates planning efforts, putting hospitals at risk of being overwhelmed. Many lack access to hospital-specific, data-driven projections of future patient demand to guide operational planning. Our hospital experienced one of the largest surges in New England. We developed statistical models to project hospitalizations during the first wave of the pandemic. We describe how we used these models to meet key planning objectives. To build the models successfully, we emphasize the criticality of having a team that combines data scientists with frontline operational and clinical leadership. While modeling was a cornerstone of our response, models currently available to most hospitals are built outside of their institution and are difficult to translate to their environment for operational planning. Creating data-driven, hospital-specific, and operationally relevant surge targets and activation triggers should be a major objective of all health systems.