Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care
University of Chicago · Agency for Healthcare Research and Quality · +10 more institutions
Abstract
Health care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income.
To provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity. Evidence Review: The Agency for Healthcare Research and Quality and the National Institute for Minority Health and Health Disparities convened a diverse panel of experts to review evidence, hear from stakeholders, and receive community feedback.
Citation impact
- FWCI
- 7.72
- Percentile
- 100%
- References
- 36
Authors
21Topics & keywords
- Health equity
- Health care
- Algorithm
- Ethnic group
- Health policy
- Equity (law)
- Context (archaeology)
- Medicine
Funding
- UDU.S. Department of Health and Human Services
- GAGordon and Betty Moore Foundation
- AAmgen
- BSBristol-Myers Squibb
- CFCenters for Disease Control and Prevention
- HRHealth Resources and Services Administration
- AFAgency for Healthcare Research and Quality
- NONutrition Obesity Research Center, University of North Carolina
- CCChicago Center for Diabetes Translation ResearchAward: P30DK092949
- NINational Institute of Diabetes and Digestive and Kidney DiseasesAward: P30DK092949
- NINational Institute on Minority Health and Health Disparities