Origins of Racial and Ethnic Bias in Pulmonary Technologies
Year: 2022
Type: review
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.
Source: Annual Review of Medicine
Institutions: University of Michigan, Michigan Medicine
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Awards: Data-Driven Identification of the Acute Respiratory Distress Syndrome, Human-AI Collaborations to Improve Accuracy and Mitigate Bias in Acute Dyspnea Diagnosis, Preventing avoidable deaths from pneumonia by improving use of intensive care, G6303801816, Promoting Change in Practice for Respiratory Failure: the PRECIPICE Study
OpenAlex ID: W4288384263