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A commentary on the value of hospital data for covid-19 pandemic surveillance and planning.
Manuel, Douglas G; van Walraven, Carl; Forster, Alan J.
  • Manuel DG; Senior Scientist, Ottawa Hospital Research Institute, Civic Campus, 1053 Carling Ave., Ottawa ON, K1Y 4E9, Canada.
  • van Walraven C; Distinguished Professor of Family Medicine, School of Epidemiology and Public Health, University of Ottawa, 600 Peter Morand Crescent, Ottawa ON, K1G 5Z3, Canada.
  • Forster AJ; Senior Core Scientist, ICES.
Int J Popul Data Sci ; 5(4): 1393, 2021 Mar 03.
Article in English | MEDLINE | ID: covidwho-1772084
ABSTRACT
Hospital data for covid-19 surveillance, planning and modelling are challenging to find worldwide in public aggregation portals. Detailed covid-19 hospital data provides insights into covid-19's health burden including identifying which sociodemographic groups are at greatest risk of covid-19 morbidity and mortality. Timely hospital data is the best source of information for actionable forecasts and projection models of hospital capacity, including critical resources such as intensive care unit beds and ventilators that take time to plan or procure. A challenge to generate timely and detailed hospital data is the reliance on separation or discharge abstracts and census counts. What are needed are well-maintained lists of patients hospitalized with covid-19. From the standpoint of public health and health services researchers and practitioners, we describe the role of hospital data for studying covid-19, why admission data are hard to find, and how improved data infrastructure can meet surveillance and planning needs in the near future. Modern hospital electronic health records can create covid-19 patient lists and these decision support tools are increasingly used for research. These tools can generate patient lists that are transmitted and combined with public health data systems.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: Int J Popul Data Sci Year: 2021 Document Type: Article Affiliation country: Ijpds.v5i4.1393

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: Int J Popul Data Sci Year: 2021 Document Type: Article Affiliation country: Ijpds.v5i4.1393