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dc.contributor.authorMerson L.
dc.contributor.authorDuque S.
dc.contributor.authorGarcia-Gallo E.
dc.contributor.authorYeabah T.O.
dc.contributor.authorRylance J.
dc.contributor.authorDiaz J.
dc.contributor.authorFlahault A.
dc.contributor.authorAbdalasalam S.
dc.contributor.authorAbdalhadi A.A.
dc.contributor.authorAbdalla W.
dc.contributor.authorAbdalla N.R.
dc.contributor.authorAbdalrheem A.H.
dc.contributor.authorAbdalsalam A.
dc.contributor.authorAbdeewi S.
dc.contributor.authorAbdelgaum E.H.
dc.contributor.authorAbdelhalim M.
dc.contributor.authorAbdelkabir M.
dc.contributor.authorAbdukahil S.A.
dc.contributor.authorAbdulbaqi L.A.
dc.contributor.authorAbdulhamid W.
dc.contributor.authorAbdulhamid S.
dc.date.accessioned2025-01-15T20:49:14Z
dc.date.available2025-01-15T20:49:14Z
dc.date.issued2024
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85205074166&doi=10.3390%2fepidemiologia5030039&partnerID=40&md5=8bb42589847666fd53aa35c4b5ab7cc1
dc.identifier.urihttp://hdl.handle.net/10818/63309
dc.description.abstractStandardised forms for capturing clinical data promote consistency in data collection and analysis across research sites, enabling faster, higher-quality evidence generation. ISARIC and the World Health Organization have developed case report forms (CRFs) for the clinical characterisation of several infectious disease outbreaks. To improve the design and quality of future forms, we analysed the inclusion and completion rates of the 243 fields on the ISARIC-WHO COVID-19 CRF. Data from 42 diverse collaborations, covering 1886 hospitals and 950,064 patients, were analysed. A mean of 129.6 fields (53%) were included in the adapted CRFs implemented across the sites. Consistent patterns of field inclusion and completion aligned with globally recognised research priorities in outbreaks of novel infectious diseases. Outcome status was the most highly included (95.2%) and completed (89.8%) field, followed by admission demographics (79.1% and 91.6%), comorbidities (77.9% and 79.0%), signs and symptoms (68.9% and 78.4%), and vitals (70.3% and 69.1%). Mean field completion was higher in severe patients (70.2%) than in all patients (61.6%). The results reveal how clinical characterisation CRFs can be streamlined to reduce data collection time, including the modularisation of CRFs, to offer a choice of data volume collection and the separation of critical care interventions. This data-driven approach to designing CRFs enhances the efficiency of data collection to inform patient care and public health response. © 2024 by the authors.en
dc.formatapplication/pdfes_CO
dc.language.isoenges_CO
dc.publisherEpidemiologiaes_CO
dc.relation.ispartofseriesEpidemiologia vol. 5 n. 3 p. 557-580
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.otherCommon data elements
dc.subject.otherData collection
dc.subject.otherData management
dc.titleOptimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisationen
dc.typejournal articlees_CO
dc.type.hasVersionpublishedVersiones_CO
dc.rights.accessRightsopenAccesses_CO
dc.identifier.doi10.3390/epidemiologia5030039


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Attribution-NonCommercial-NoDerivatives 4.0 InternacionalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 Internacional