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Origins of Racial and Ethnic Bias in Pulmonary Technologies.

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Title: Origins of Racial and Ethnic Bias in Pulmonary Technologies.
Authors: Sjoding, Michael W. (AUTHOR), Ansari, Sardar (AUTHOR), Valley, Thomas S. (AUTHOR)
Source: Annual Review of Medicine. 2023, Vol. 74 Issue 1, p401-412. 12p.
Abstract: Understanding how biases originate in medical technologies and developing safeguards to identify, mitigate, and remove their harms are essential to ensuring equal performance in all individuals. Drawing upon examples from pulmonary medicine, this article describes how bias can be introduced in the physical aspects of the technology design, via unrepresentative data, or by conflation of biological with social determinants of health. It then can be perpetuated by inadequate evaluation and regulatory standards. Research demonstrates that pulse oximeters perform differently depending on patient race and ethnicity. Pulmonary function testing and algorithms used to predict healthcare needs are two additional examples of medical technologies with racial and ethnic biases that may perpetuate health disparities. [ABSTRACT FROM AUTHOR]
Copyright of Annual Review of Medicine is the property of Annual Reviews Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Origins of Racial and Ethnic Bias in Pulmonary Technologies.
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  Data: <searchLink fieldCode="AR" term="%22Sjoding%2C+Michael+W%2E%22">Sjoding, Michael W.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ansari%2C+Sardar%22">Ansari, Sardar</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Valley%2C+Thomas+S%2E%22">Valley, Thomas S.</searchLink> (AUTHOR)
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  Data: Understanding how biases originate in medical technologies and developing safeguards to identify, mitigate, and remove their harms are essential to ensuring equal performance in all individuals. Drawing upon examples from pulmonary medicine, this article describes how bias can be introduced in the physical aspects of the technology design, via unrepresentative data, or by conflation of biological with social determinants of health. It then can be perpetuated by inadequate evaluation and regulatory standards. Research demonstrates that pulse oximeters perform differently depending on patient race and ethnicity. Pulmonary function testing and algorithms used to predict healthcare needs are two additional examples of medical technologies with racial and ethnic biases that may perpetuate health disparities. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Annual Review of Medicine is the property of Annual Reviews Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 2023
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