Global Collaborative Efforts During COVID-19 Study-A-Thon

OHDSI Foundation Of Open Science, High-Level Analytic Tools, Led Unprecedented Global Collaborative Efforts During COVID-19 Study-A-Thon
Published in Microbiology

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This deep phenotyping study of hospitalized COVID-19 patients around the world was initiated through the global community efforts that occurred during the OHDSI COVID-19 study-a-thon, an 88-hour international collaboration of experts across multiple disciplines who joined together under a shared belief in open science to design and, ultimately, execute both this and several other COVID-related studies to help inform global decision-making during this pandemic.

OHDSI — the Observational Health Data Sciences and Informatics community — is a multi-stakeholder, interdisciplinary network that collaborates to bring out the value of health data through large-scale analytics. In plainer terms, it is a community of people who volunteer their time and talents for the shared goal of improving healthcare through observational research.

This community brought together an international cohort of more than 34,000 hospitalized COVID-19 patients across three continents to describe their characteristics, an unprecedented effort that was only possible because of foundational work on OHDSI analytic tools over the span of years, and a dedication to openly sharing study protocols and all analytic code used across the globe.

Collaborators in South Korea, led by study co-lead Seng Chan You, were some of the first to observe COVID-19 experience in their patient-level data. These data were analyzed securely within their institution, and aggregate summary results were shared to provide some of the earliest real-world evidence of COVID disease natural history. This study also includes the summary information from the real-world experience of patients in Spain, South Korea and the United States, expanding the generalizability of the findings beyond what can typically be learned within a single-institution study.

As of mid-September, the OHDSI community has brought together an international COVID-19 data network that includes more than 4.5 million patients tested for COVID-19, 1.2 million diagnosed or tested positive, and 249,000 hospitalized with the disease. The network spans 20 different databases across nine nations, and will be the foundation of new characterization studies within the CHARYBDIS (Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2) Project.

Simultaneously, collaborators within the EHDEN Consortium are working to map COVID data throughout Europe. EHDEN aims to standardize more than 100 million patient records across Europe from different geographic areas and different data sources over a five-year span. Mapping of healthcare data to the OMOP-CDM used by the OHDSI community will facilitate the re-use for a variety of purposes, enhancing and accelerating research and healthcare decision-making for global benefit.

CHARYBDIS is an OHDSI initiative that attempts to describe the baseline demographic, clinical characteristics, treatments and outcomes of interest among individuals tested for SARS-CoV-2 and/or diagnosed with COVID-19 overall and stratified by sex, age and specific comorbidities, as compared to Influenza patients from 2017-2018. A study preprint of characteristics and outcomes of >627,00 COVID-19 patients with and without obesity is available via preprint, and many other studies (autoimmune disease, pregnancy, pediatrics, racial disparities, and more) are in the later stages of development.

OHDSI, which will hold its global symposium October 18-21 and is free for both community participants and those looking to learn more about this global collaborative, thrived in the midst of this global pandemic because of its foundational analytic tools and beliefs in both open science and collaboration. An international community generated studies on that foundation which have already impacted both clinical and methodological decision-making surrounding COVID-19, and will continue to work towards improving global healthcare in the future.

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Life Sciences > Biological Sciences > Microbiology

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