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Do implicit bias trainings on race improve health care? Not yet – but incorporating the latest science can help hospitals treat all patients equitably

Nao Hagiwara, University of Virginia and Tiffany Green, University of Wisconsin-Madison, The Conversation on

Published in News & Features

Developing and implementing effective implicit bias training in health care is a scientific endeavor that requires a strong supporting structure.

For example, the clinical and translational science, or CTS, framework, originally designed to help translate discoveries in the lab into treatments in the clinic, could also be applied to implicit bias training. This framework guides scientific progress across incremental stages, starting from confirming the mechanism behind an illness to developing and testing a new treatment for use in the broader community.

This framework is particularly relevant to the development and implementation of evidence-based implicit bias training. Researchers first focus on confirming the mechanisms that underlie implicit bias. Then, after developing and testing implicit bias training programs, they examine its effectiveness across institutions and among diverse health care professionals.

Applying a rigorous scientific process to the development of implicit bias training requires an institution’s long-term commitment, robust support and substantial resources. We believe this investment is a small price to pay for the invaluable progress it promises in reshaping health care for the better for everyone.

This article is republished from The Conversation, a nonprofit, independent news organization bringing you facts and analysis to help you make sense of our complex world.

 

Read more:
How racism in US health system hinders care and costs lives of African Americans

Heteronormativity in health care is harmful for LGBTQ+ patients – and a source of tension for queer and trans doctors

Nao Hagiwara receives funding from National Institute of Health.

Tiffany Green does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.


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