CC BY-NC-ND 4.0 · Yearb Med Inform 2021; 30(01): 176-184
DOI: 10.1055/s-0041-1726503
Section 6: Knowledge Representation and Management
Survey

The Evolution of Clinical Knowledge During COVID-19: Towards a Global Learning Health System

Karin Verspoor
1  School of Computing Technologies, RMIT University, Melbourne VIC 3000 Australia
2  Centre for Digital Transformation of Health, The University of Melbourne, Melbourne VIC 3010 Australia
3  School of Computing and Information Systems, The University of Melbourne, Melbourne VIC 3010 Australia
› Author Affiliations

Summary

Objectives: We examine the knowledge ecosystem of COVID-19, focusing on clinical knowledge and the role of health informatics as enabling technology. We argue for commitment to the model of a global learning health system to facilitate rapid knowledge translation supporting health care decision making in the face of emerging diseases.

Methods and Results: We frame the evolution of knowledge in the COVID-19 crisis in terms of learning theory, and present a view of what has occurred during the pandemic to rapidly derive and share knowledge as an (underdeveloped) instance of a global learning health system. We identify the key role of information technologies for electronic data capture and data sharing, computational modelling, evidence synthesis, and knowledge dissemination. We further highlight gaps in the system and barriers to full realisation of an efficient and effective global learning health system.

Conclusions: The need for a global knowledge ecosystem supporting rapid learning from clinical practice has become more apparent than ever during the COVID-19 pandemic. Continued effort to realise the vision of a global learning health system, including establishing effective approaches to data governance and ethics to support the system, is imperative to enable continuous improvement in our clinical care.



Publication History

Publication Date:
03 September 2021 (online)

© 2021. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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