Nivel Corona Cohort: a description of the cohort and methodology used for combining general practice electronic records with patient reported outcomes to study impact of a COVID-19 infection

DOI

A population-based COVID-19 cohort was set up in the Netherlands to gain comprehensive insight in the short- and long-term effects of COVID-19 in the general population. A subset of this data, deposited and described here, was used for the aims to describe the methodology and infrastructure used to recruit individuals with COVID-19 and the representativeness of the population-based cohort and to characterize the population by description of their symptoms and health care usage during the acute COVID-19 phase.The starting point of the set-up of the cohort was to recruit participants in routinely recorded, general practice electronic health records (EHR) data, which are sent to the Netherlands Institute for Health Services Research Primary Care Database (Nivel-PCD) on a weekly basis. Patients registered with COVID-19 were flagged in the Nivel-PCD based on their COVID-19 diagnoses. Flagged patients were invited for participation by their general practitioner via a trusted third party. Participating patients received a series of four questionnaires over the duration of one year allowing for a combination of data from patient reported outcomes and EHRs.The Nivel Corona Cohort consists of 442 participants and here a subset of the data from the first questionnaire is shown. The Nivel Corona Cohort is population-based, containing a complete image of severity of symptoms from patients with none or hardly any symptoms to those who were hospitalized due to the COVID-19. The five most prevalent symptoms during the acute COVID-19 phase were fatigue (90.5%), reduced condition (88.2%), coughing/sneezing/stuffy nose (79.3%), headache (75.4%), and myalgia (66.7%). The population-based Nivel Corona Cohort provides ample opportunities for future studies to gain comprehensive insight in the short- and long-term effects of COVID-19 by combining patients’ perspectives and clinical parameters via the EHRs within a long-term follow-up of the cohort.

Date Submitted: 2023-07-31

Identifier
DOI https://doi.org/10.17026/dans-xzv-32r2
Metadata Access https://lifesciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-xzv-32r2
Provenance
Creator K. Hek ORCID logo; R. Veldkamp ORCID logo
Publisher DANS Data Station Life Sciences
Contributor L Holst; PLOSONE
Publication Year 2023
Rights DANS Licence; info:eu-repo/semantics/closedAccess; https://doi.org/10.17026/fp39-0x58
OpenAccess false
Contact L Holst (Nivel)
Representation
Resource Type Dataset
Format application/pdf; text/csv; application/zip
Size 740469; 184515; 19374
Version 2.0
Discipline Life Sciences; Medicine