Accepted for/Published in: JMIR AI
Date Submitted: Mar 31, 2022
Open Peer Review Period: Mar 31, 2022 - Apr 14, 2022
Date Accepted: Jan 6, 2023
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
The Application of Artificial Intelligence in Healthcare-Resource Allocation Before and During the COVID Pandemic: Scoping Review
ABSTRACT
Background:
Imbalanced healthcare-resource distribution has been central in unequal health outcomes and political tension around the world. Artificial intelligence (AI) has emerged as a promising tool for facilitating resource distribution, especially during emergencies. However, no comprehensive review exists on the use and ethics of AI in healthcare-resource distribution.
Objective:
This study aims to conduct a systematic scoping review of the application of AI in healthcare-resource distribution and to explore the ethical and political issues in such situations.
Methods:
A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. A systematic and comprehensive search of relevant literature was conducted in Medline (Ovid), PubMed, Web of Science, and Embase from inception to February 2022. The review included qualitative and quantitative studies investigating the application of AI in healthcare-resource allocation.
Results:
The review involved 22 articles, including 9 on model development and 13 on theoretical discussion, qualitative studies, or review studies. Of the 9 on model development and validation, 5 were conducted in emerging economies, 3 in developed countries, and one study in a global context. In terms of content, 4 focused on resource distribution at the health-system level and 5 on resource allocation at the hospital level. Of the 13 qualitative studies, 8 were discussions on the COVID pandemic and the rest on hospital resources, outbreaks, screening, human resources, and digitalisation.
Conclusions:
This scoping review synthesised evidence on AI in health resource distribution, focusing on the COVID pandemic. The results suggest that the application of AI has potential to improve efficacy in resource distribution, especially during emergencies. Efficient data sharing and collecting structures are needed to make reliable and evidence-based decisions. Health inequality, distributive justice, and transparency must be considered when deploying AI models in real-world situations.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.