tetano
Editor, Senior Moderator
Ann Fam Med
. Mar-Apr 2021;19(2):135-140.
doi: 10.1370/afm.2658.
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
Hajira Dambha-Miller, Simon J Griffin, Duncan Young, Peter Watkinson, Pui San Tan, Ashley K Clift, Rupert A Payne, Carol Coupland, Jemma C Hopewell, Jonathan Mant, Richard M Martin, Julia Hippisley-Cox
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 decisions 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 consistency in defining and reporting cases, exposures, confounders, stratification variables, 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.
Keywords: big data; coronavirus; epidemiology; primary health care.
. Mar-Apr 2021;19(2):135-140.
doi: 10.1370/afm.2658.
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
Hajira Dambha-Miller, Simon J Griffin, Duncan Young, Peter Watkinson, Pui San Tan, Ashley K Clift, Rupert A Payne, Carol Coupland, Jemma C Hopewell, Jonathan Mant, Richard M Martin, Julia Hippisley-Cox
- PMID: 33685875
- 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 decisions 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 consistency in defining and reporting cases, exposures, confounders, stratification variables, 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.
Keywords: big data; coronavirus; epidemiology; primary health care.