TY - JOUR
T1 - Optimising Clinical Epidemiology in Disease Outbreaks
T2 - Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation
AU - Merson, Laura
AU - Duque, Sara
AU - Garcia-Gallo, Esteban
AU - Yeabah, Trokon Omarley
AU - Rylance, Jamie
AU - Diaz, Janet
AU - Flahault, Antoine
AU - Abdalasalam, Sabriya
AU - Abdalhadi, Alaa Abdalfattah
AU - Abdalla, Walaa
AU - Abdalla, Naana Reyam
AU - Abdalrheem, Almthani Hamza
AU - Abdalsalam, Ashraf
AU - Abdeewi, Saedah
AU - Abdelgaum, Esraa Hassan
AU - Abdelhalim, Mohamed
AU - Abdelkabir, Mohammed
AU - Abdukahil, Sheryl Ann
AU - Abdulbaqi, Lamees Adil
AU - Abdulhamid, Widyan
AU - Abdulhamid, Salaheddin
AU - Abdulkadir, Nurul Najmee
AU - Abdulwahed, Eman
AU - Abdunabi, Rawad
AU - Abe, Ryuzo
AU - Abel, Laurent
AU - Abodina, Ahmed Mohammed
AU - Abouelmagd, Khaled
AU - Abrous, Amal
AU - Abu Jabal, Kamal
AU - Abu Salah, Nashat
AU - Abukhalaf, Salsabeel M.A.
AU - Abusalama, Abdurraouf
AU - Abuzaid, Tareg Abdallah
AU - Acharya, Subhash
AU - Acker, Andrew
AU - Adem, Safia
AU - Ademnou, Manuella
AU - Adewhajah, Francisca
AU - Adhikari, Neill K.J.
AU - Adrião, Diana
AU - Yaw Adu, Samuel
AU - Afum-Adjei Awuah, Anthony
AU - Agbogbatey, Melvin
AU - Ageel, Saleh Al
AU - Ahmed, Musaab Mohammed
AU - Ahmed, Aya Mustafa
AU - Ahmed, Shakeel
AU - Alaraji, Zainab Ahmed
AU - Vaillant, Michel
AU - ISARIC Clinical Characterisation Group
AU - CCP UK
AU - Mazankowski Heart Institute
AU - PHOSP Collaborative Group
AU - The Western Australian COVID-19 Research Response
N1 - Funding:
This work was made possible with the support of the UK Foreign, Common-
wealth and Development Office and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z and 220757/Z/20/Z]; the Bill & Melinda Gates Foundation [OPP1209135]; the philanthropic support of the donors to the University of Oxford’s COVID-19 Research Response Fund (0009109); grants from the National Institute for Health Research (NIHR; award CO-CIN-01/DH_/Department of
Health/United Kingdom), the Medical Research Council (MRC; grant MC_PC_19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE), (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award ISBRC-1215-20013), and NIHR Clinical Research Network providing in-Epidemiologia 2024, 5 570
frastructure support; the Comprehensive Local Research Networks (CLRNs), of which PJMO is an NIHR Senior Investigator (NIHR201385); Cambridge NIHR Biomedical Research Centre (award NIHR203312); CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and was coordinated out of Sunnybrook Research Institute; endorsement of the Irish Critical Care-Clinical
Trials Group, co-ordinated in Ireland by the Irish Critical Care-Clinical Trials Network at University College Dublin and funded by the Health Research Board of Ireland [CTN-2014-12]; Australian Department of Health grant (3273191); Gender Equity Strategic Fund at University of Queensland, Artificial Intelligence for Pandemics (A14PAN) at University of Queensland, The Australian Re-
search Council Centre of Excellence for Engineered Quantum Systems (EQUS, CE170100009), The Prince Charles Hospital Foundation, Australia; a Research Council of Norway grant no 312780, and a philanthropic donation from Vivaldi Invest A/S owned by Jon Stephenson von Tetzchner; the South Eastern Norway Health Authority and the Research Council of Norway; Innovative Medicines
Initiative Joint Undertaking under Grant Agreement No. 115523 COMBACTE, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies, in-kind contribution; grants from Instituto de Salud Carlos III, Ministerio de Ciencia, Spain; the French COVID cohort (NCT04262921) is sponsored by INSERM
and is funded by the REACTing (REsearch & ACtion emergING infectious diseases) consortium and by a grant of the French Ministry of Health (PHRC n◦20-0424); Stiftungsfonds zur Förderung der Bekämpfung der Tuberkulose und anderer Lungenkrankheiten of the City of Vienna; Project Number:
APCOV22BGM; Brazil, National Council for Scientific and Technological Development Scholarship number 303953/2018-7; the Firland Foundation, Shoreline, Washington, USA; Institute for Clinical Research (ICR), National Institutes of Health (NIH) supported by the Ministry of Health Malaysia; a
grant from foundation Bevordering Onderzoek Franciscus; funding from Saisei Mirai/Saisei Pharma, Japan; the U.S. DoD Armed Forces Health Surveillance Division, Global Emerging Infectious Diseases Branch to the U.S Naval Medical Research Unit No. TWO (NAMRU-2) (Work Unit #: P0153_21_N2).
The Lao-Oxford-Mahosot Hospital-Wellcome Trust Research Unit is funded by the Wellcome Trust.
The ISARIC Clinical Characterisation Group acknowledge the COVID clinical management team, AIIMS, Rishikesh, India; the COVID-19 Clinical Management team, Manipal Hospital Whitefield, Bengaluru, India; the Italian Ministry of Health “Fondi Ricerca corrente–L1P6” to IRCCS Ospedale
Sacro Cuore–Don Calabria; the Groote Schuur Hospital Covid ICU Team, supported by the Groote Schuur nursing; the University of Cape Town registrar bodies coordinated by the Division of Critical Care at the University of Cape Town; Vysnova Partners, Inc.; the Norwegian SARS-CoV-2 study team; the clinical, laboratory, research, and support staff at EFSTH and MRCG; and the Short Period Incidence Study of Severe Acute Respiratory Infection; and the support of Jeremy J Farrar and Nahoko Shindo. This work uses data provided by patients and collected by the NHS as part of their care and support #DataSavesLives. The data used for this research were obtained from ISARIC4C. We are extremely grateful to the 2648 front-line NHS clinical and research staff and volunteer medical students who collected these data in challenging circumstances, and the generosity of the patients and their families for their individual contributions in these difficult times. The COVID-19 Clinical
Information Network (CO-CIN) data were collated by ISARIC4C investigators.
Publisher Copyright:
© 2024 by the authors.
PY - 2024/8/30
Y1 - 2024/8/30
N2 - Standardised 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.
AB - Standardised 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.
KW - clinical epidemiology
KW - common data elements
KW - data collection
KW - data management
KW - infectious disease outbreaks
KW - ISARIC
UR - http://www.scopus.com/inward/record.url?scp=85205074166&partnerID=8YFLogxK
UR - https://pubmed.ncbi.nlm.nih.gov/39311356/
U2 - 10.3390/epidemiologia5030039
DO - 10.3390/epidemiologia5030039
M3 - Article
C2 - 39311356
AN - SCOPUS:85205074166
SN - 2673-3986
VL - 5
SP - 557
EP - 580
JO - Epidemiologia
JF - Epidemiologia
IS - 3
ER -