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Modelling the backlog of COVID-19 cases for a surgical group.
Brandman, David M; Leck, Erika; Christie, Sean.
  • Brandman DM; From the Division of Neurosurgery (Department of Surgery), Dalhousie University, Halifax, NS.
  • Leck E; From the Division of Neurosurgery (Department of Surgery), Dalhousie University, Halifax, NS.
  • Christie S; From the Division of Neurosurgery (Department of Surgery), Dalhousie University, Halifax, NS.
Can J Surg ; 63(5): E391-E392, 2020 08 28.
Article in English | MEDLINE | ID: covidwho-732983
ABSTRACT

Summary:

The coronavirus disease 2019 (COVID-19) pandemic has had an unprecedented impact on health care delivery and has resulted in a backlog of patients needing surgery. There is a lack of experience and guidance in dealing with this increased demand on an already overburdened health care system. We created an online tool (www.covidbacklog.com) that helps surgeons explore how resource allocation within their group will affect wait times for patients. After inputting a handful of readily available variables, the computer program generates a forecast of how long it will take to see the backlog of patients. This information could be used to allow surgical groups to run simulations to explore different resource allocation strategies in order to help prevent downstream consequences of delayed patient care.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / General Surgery / Coronavirus Infections / Disease Transmission, Infectious / Delivery of Health Care / Surgeons / Betacoronavirus Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Can J Surg Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / General Surgery / Coronavirus Infections / Disease Transmission, Infectious / Delivery of Health Care / Surgeons / Betacoronavirus Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: Can J Surg Year: 2020 Document Type: Article