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A model to estimate demand for personal protective equipment for Ontario acute care hospitals during the COVID-19 pandemic
Kali A Barrett; Yoshiko Nakamachi; Terra Ierasts; Yasin Khan; Stephen Mac; David Naimark; Nathan Stall; Raphael Ximenes; Andrew Morris; Beate Sander.
Affiliation
  • Kali A Barrett; Institute of Health Policy, Management and Evaluation, University of Toronto. University Health Network. IDDCCM, Toronto. THETA Collaborative. Department of Med
  • Yoshiko Nakamachi; University Health Network, Sinai Health System.
  • Terra Ierasts; University Health Network
  • Yasin Khan; Institute of Health Policy, Management and Evaluation, University of Toronto. University Health Network. IDDCCM, University of Toronto. Department of Medicine,
  • Stephen Mac; Institute of Health Policy, Management and Evaluation, University of Toronto. THETA Collaborative.
  • David Naimark; Institute of Health Policy, Management and Evaluation, University of Toronto. THETA Collaborative. Sunnybrook Hospital
  • Nathan Stall; Institute of Health Policy, Management and Evaluation, University of Toronto. Department of Medicine, University of Toronto. Sinai Health System. Women's Colleg
  • Raphael Ximenes; THETA Collaborative
  • Andrew Morris; University Health Network. Department of Medicine, University of Toronto. Sinai Health System
  • Beate Sander; Institute of Health Policy, Management and Evaluation, University of Toronto. THETA Collaborative. Public Health Ontario. ICES.
Preprint in English | medRxiv | ID: ppmedrxiv-20085142
ABSTRACT
In addition to instituting public health measures for COVID-19, managing healthcare resources is important for outcomes. The experiences in Italy and New York have shown that personal protective equipment (PPE) shortages can cause increased morbidity and mortality. We demonstrate a method to predict PPE demand across a health care system.
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study / Qualitative research Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study / Qualitative research Language: English Year: 2020 Document type: Preprint
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