2021
DOI: 10.21203/rs.3.rs-279400/v1
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Unraveling COVID-19: a large-scale characterization of 4.5 million COVID-19 cases using CHARYBDIS

Abstract: Background: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response [1,2]. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) [3] Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.Methods: We conducted a descriptive cohort study using a federated network of data partners in the United States, Euro… Show more

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Cited by 10 publications
(8 citation statements)
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“…The study protocol and analytical package were released on 11 June 2020, and iterative updates are continually released through GitHub 18. Our study was also published as a preprint 19…”
Section: Methodsmentioning
confidence: 99%
“…The study protocol and analytical package were released on 11 June 2020, and iterative updates are continually released through GitHub 18. Our study was also published as a preprint 19…”
Section: Methodsmentioning
confidence: 99%
“…The Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) study is a multinational cohort study using retrospective electronic health records and claims data on COVID-19 patients from three continents, the North America (US), Europe, and Asia 7 . All data for were standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) 8,9 .…”
Section: Methodsmentioning
confidence: 99%
“…A multinational, multidatabase cohort study was conducted using data from 1 March to 31 October 2020 included in ‘The Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2’ (CHARYBDIS 23 ) study. This is a large-scale multinational cohort study aimed to characterise health-associated risks and baseline diseases in SARS-CoV-2 patients using routinely collected primary care and hospital electronic health records (EHR), hospital billing and insurance claims data from the USA, Europe (the Netherlands, Spain, UK, Germany and France) and Asia (South Korea and China).…”
Section: Methodsmentioning
confidence: 99%
“…Data results for this paper were extracted on 21 January 2021. 23 Fifteen databases complied with the aforementioned inclusion criteria. Of these, five had data for outpatients: IQVIA-Longitudinal Patients Database ‘LPD’ (France), IQVIA-Longitudinal Patients Database ‘LPD’ (Italy), IQVIA-Disease Analyser ‘DA’ (Germany), Clinical Practice Research Datalink ‘CPRD’ (UK) and Integrated Primary Care Information ‘IPCI’ (the Netherlands); two had data for inpatients: Health Insurance Review and Assessment Service ‘HIRA’ (South Korea) and Hospital del Mar ‘HMAR’ (Spain); and eight had both inpatient and outpatient data: IQVIA-OpenClaims, HealthVerity, Information System for Research in Primary Care ‘SIDIAP’ (Spain 24 ), Optum de-identified Electronic Health Record Dataset ‘OPTUM-HER’ (USA), United States Department of Veterans Affairs (VA-OMOP), Columbia University Irving Medical Center ‘CUIMC’ (USA), University of Colorado Anschutz Medical Campus Health Data Compass ‘CU-AMC-HDC’, and STAnford Medicine Research Data Repository ‘STARR-OMOP’ (USA 25 ).…”
Section: Methodsmentioning
confidence: 99%