Insights from ARCOS-V's Transition to Remote Data Collection During the COVID-19 Pandemic: A Descriptive Study.

Abstract

INTRODUCTION 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).