Insights From ARCOS-V's Transition to Remote Data Collection During the Covid-19 Pandemic: A Descriptive Study

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aut.relation.endpage15
aut.relation.journalNeuroepidemiology
aut.relation.startpage1
dc.contributor.authorHenry, Nathan IN
dc.contributor.authorNair, Balakrishnan
dc.contributor.authorRanta, Anna
dc.contributor.authorKrishnamurthi, Rita
dc.contributor.authorBhatia, Anjali
dc.contributor.authorFeigin, Valery
dc.date.accessioned2024-09-24T03:29:50Z
dc.date.available2024-09-24T03:29:50Z
dc.date.issued2024
dc.description.abstractINTRODUCTION: The ARCOS-V study, an epidemiological study on stroke and transient ischemic attack (TIA), faced the challenge of continuing data collection amidst the COVID-19 pandemic. This study aims to describe the methodological changes and challenges encountered during the transition from paper-based methods to digital data collection for the ARCOS-V study, and to provide insights into the potential of using digital tools to transform epidemiological research. METHODS: The study adapted to remote data collection using REDCap and Zoom, involving daily health record reviews, direct data entry by trained researchers, and remote follow-up assessments. The process was secured with encryption and role-based access controls. The transition period was analyzed to evaluate the effectiveness and challenges of the new approach. RESULTS: The digital transition allowed for uninterrupted monitoring of stroke and TIA cases during lockdowns. Using REDCap and Zoom improved data reach, accuracy, and security. However, it also revealed issues such as the potential for systematic data entry errors and the need for robust security measures to protect sensitive health information. CONCLUSION: The ARCOS-V study's digital transformation exemplifies the resilience of epidemiological research in the face of a global crisis. The successful adaptation to digital data collection methods highlights the potential benefits of such tools, particularly as we enter a new age of Artificial Intelligence (AI).
dc.identifier.citationNeuroepidemiology, ISSN: 1423-0208 (Print); 1423-0208 (Online), S. Karger AG, 1-15. doi: 10.1159/000541368
dc.identifier.doi10.1159/000541368
dc.identifier.issn1423-0208
dc.identifier.issn1423-0208
dc.identifier.urihttp://hdl.handle.net/10292/18043
dc.languageeng
dc.publisherS. Karger AG
dc.relation.urihttps://karger.com/ned/article/doi/10.1159/000541368/912996/Insights-from-ARCOS-V-s-Transition-to-Remote-Data
dc.rights© 2024 The Author(s). Published by S. Karger AG, Basel. This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC) http://www.karger.com/Services/OpenAccessLicense). Usage and distribution for commercial purposes requires written permission.
dc.rights.accessrightsOpenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0
dc.subject1109 Neurosciences
dc.subject1117 Public Health and Health Services
dc.subjectEpidemiology
dc.subject3202 Clinical sciences
dc.subject3209 Neurosciences
dc.subject4202 Epidemiology
dc.titleInsights From ARCOS-V's Transition to Remote Data Collection During the Covid-19 Pandemic: A Descriptive Study
dc.typeJournal Article
pubs.elements-id569094
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