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The Power of Modeling in Emergency Preparedness for COVID-19: A Moonshot Moment for Hospitals.
Safavi, Kyan C; Prestipino, Ann L; Zenteno Langle, Ana Cecilia; Copenhaver, Martin; Hu, Michael; Daily, Bethany; Koehler, Allison; Biddinger, Paul D; Dunn, Peter F.
  • Safavi KC; Healthcare Systems Engineering, Massachusetts General Hospital, Boston, MA, USA.
  • Prestipino AL; Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Zenteno Langle AC; Department of Perioperative Services, Massachusetts General Hospital, Boston, MA, USA.
  • Copenhaver M; Hospital Administration, Massachusetts General Hospital, Boston, MA, USA.
  • Hu M; Healthcare Systems Engineering, Massachusetts General Hospital, Boston, MA, USA.
  • Daily B; Healthcare Systems Engineering, Massachusetts General Hospital, Boston, MA, USA.
  • Koehler A; Healthcare Systems Engineering, Massachusetts General Hospital, Boston, MA, USA.
  • Biddinger PD; Healthcare Systems Engineering, Massachusetts General Hospital, Boston, MA, USA.
  • Dunn PF; Department of Perioperative Services, Massachusetts General Hospital, Boston, MA, USA.
Disaster Med Public Health Prep ; 16(5): 2182-2184, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-1085445
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Civil Defense / Disaster Planning / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Disaster Med Public Health Prep Journal subject: Public Health Year: 2022 Document Type: Article Affiliation country: Dmp.2021.51

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Civil Defense / Disaster Planning / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Disaster Med Public Health Prep Journal subject: Public Health Year: 2022 Document Type: Article Affiliation country: Dmp.2021.51