The use of primary care big data in understanding the pharmacoepidemiology of COVID-19: A consensus statement from the COVID-19 primary care database consortium
The use of primary care big data in understanding the pharmacoepidemiology of COVID-19: A consensus statement from the COVID-19 primary care database consortium
The use of big data containing millions of primary care medical records provides an opportunity for rapid research to help inform patient care and policy deci-sions during the first and subsequent waves of the coronavirus disease 2019 (COVID-19) pandemic. Routinely collected primary care data have previously been used for national pandemic surveillance, quantifying associations between exposures and outcomes, identifying high risk populations, and examining the effects of interventions at scale, but there is no consensus on how to effectively conduct or report these data for COVID-19 research. A COVID-19 primary care database consortium was established in April 2020 and its researchers have ongoing COVID-19 projects in overlapping data sets with over 40 million primary care records in the United Kingdom that are variously linked to public health, secondary care, and vital status records. This consensus agreement is aimed at facilitating transparency and rigor in methodological approaches, and consis-tency in defining and reporting cases, exposures, confounders, stratification vari-ables, and outcomes in relation to the pharmacoepidemiology of COVID-19. This will facilitate comparison, validation, and meta-analyses of research during and after the pandemic.
Big data, Coronavirus, Epidemiology, Primary health care
135-140
Dambha-Miller, Hajira
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Griffin, Simon J.
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Young, Duncan
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Watkinson, Peter
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Tan, Pui San
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Clift, Ashley K.
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Payne, Rupert A.
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Coupland, Carol
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Hopewell, Jemma C.
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Mant, Jonathan
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Martin, Richard M.
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Hippisley-Cox, Julia
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10 March 2021
Dambha-Miller, Hajira
58961db5-31aa-460e-9394-08590c4b7ba1
Griffin, Simon J.
1f8d5095-3c10-4973-a2c4-84ce6415d118
Young, Duncan
70edf578-9c08-4a7c-b740-e9c5e222cfb5
Watkinson, Peter
b0ba6163-5c95-474c-a82f-c6839082dbb1
Tan, Pui San
66f64b43-84a2-4362-afdd-f68e410f6571
Clift, Ashley K.
cd174dd3-ed3a-46c4-bf08-0471b333901e
Payne, Rupert A.
510c53d5-e691-41ed-8c2e-5cc77e40a75a
Coupland, Carol
5d123e7a-f406-4d6b-a09d-2e019de3686f
Hopewell, Jemma C.
fb0c923b-16c6-4b35-9d10-aabf018779d7
Mant, Jonathan
0d1a0061-0f04-45c7-b20a-15798b1f465c
Martin, Richard M.
ce5c4184-4432-4435-bd1e-221f665d42d8
Hippisley-Cox, Julia
ffe3b07c-6ca2-4487-b69b-6ea2b039ab13
Dambha-Miller, Hajira, Griffin, Simon J., Young, Duncan, Watkinson, Peter, Tan, Pui San, Clift, Ashley K., Payne, Rupert A., Coupland, Carol, Hopewell, Jemma C., Mant, Jonathan, Martin, Richard M. and Hippisley-Cox, Julia
(2021)
The use of primary care big data in understanding the pharmacoepidemiology of COVID-19: A consensus statement from the COVID-19 primary care database consortium.
Annals of Family Medicine, 19 (2), .
(doi:10.1370/afm.2658).
Abstract
The use of big data containing millions of primary care medical records provides an opportunity for rapid research to help inform patient care and policy deci-sions during the first and subsequent waves of the coronavirus disease 2019 (COVID-19) pandemic. Routinely collected primary care data have previously been used for national pandemic surveillance, quantifying associations between exposures and outcomes, identifying high risk populations, and examining the effects of interventions at scale, but there is no consensus on how to effectively conduct or report these data for COVID-19 research. A COVID-19 primary care database consortium was established in April 2020 and its researchers have ongoing COVID-19 projects in overlapping data sets with over 40 million primary care records in the United Kingdom that are variously linked to public health, secondary care, and vital status records. This consensus agreement is aimed at facilitating transparency and rigor in methodological approaches, and consis-tency in defining and reporting cases, exposures, confounders, stratification vari-ables, and outcomes in relation to the pharmacoepidemiology of COVID-19. This will facilitate comparison, validation, and meta-analyses of research during and after the pandemic.
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More information
Published date: 10 March 2021
Keywords:
Big data, Coronavirus, Epidemiology, Primary health care
Identifiers
Local EPrints ID: 448933
URI: http://eprints.soton.ac.uk/id/eprint/448933
ISSN: 1544-1709
PURE UUID: f1d4f661-4ab4-4a79-8888-4b42f5239d1f
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Date deposited: 11 May 2021 16:48
Last modified: 18 Mar 2024 03:50
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Contributors
Author:
Simon J. Griffin
Author:
Duncan Young
Author:
Peter Watkinson
Author:
Pui San Tan
Author:
Ashley K. Clift
Author:
Rupert A. Payne
Author:
Carol Coupland
Author:
Jemma C. Hopewell
Author:
Jonathan Mant
Author:
Richard M. Martin
Author:
Julia Hippisley-Cox
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