Promoting racial equity in COVID-19 resource allocation

Due to COVID-19’s strain on health systems across the globe, triage protocols determine how to allocate scarce medical resources with the worthy goal of maximising the number of lives saved. However, due to racial biases and long-standing health inequities, the common method of ranking patients base...

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Bibliographic Details
Authors: Bruce, Lori (Author) ; Tallman, Ruth (Author)
Format: Electronic Article
Language:English
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Published: BMJ Publ. 2021
In: Journal of medical ethics
Year: 2021, Volume: 47, Issue: 4, Pages: 208-212
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520 |a Due to COVID-19’s strain on health systems across the globe, triage protocols determine how to allocate scarce medical resources with the worthy goal of maximising the number of lives saved. However, due to racial biases and long-standing health inequities, the common method of ranking patients based on impersonal numeric representations of their morbidity is associated with disproportionately pronounced racial disparities. In response, policymakers have issued statements of solidarity. However, translating support into responsive COVID-19 policy is rife with complexity. Triage does not easily lend itself to race-based exceptions. Reordering triage queues based on an individual patient’s racial affiliation has been considered but may be divisive and difficult to implement. And while COVID-19 hospital policies may be presented as rigidly focused on saving the most lives, many make exceptions for those deemed worthy by policymakers such as front-line healthcare workers, older physicians, pregnant women and patients with disabilities. These exceptions demonstrate creativity and ingenuity—hallmarks of policymakers’ abilities to flexibly respond to urgent societal concerns—which should also be extended to patients of colour. This paper dismantles common arguments against the confrontation of racial inequity within COVID-19 triage protocols, highlights concerns related to existing proposals and proposes a new paradigm to increase equity when allocating scarce COVID-19 resources. 
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