Fierce Healthcare April 12, 2024
Anika Heavener

AI is riddled by bias, especially in healthcare. Just one well-known example is a study from 2019 that revealed racial bias in a clinical algorithm used by hospitals showing that Black patients had to be significantly sicker than white patients to receive the same care. The bias stemmed from training data reflecting historical healthcare spending disparities between Black and white patients.

From racism to ageism, these biases have already had profound implications in health outcomes, particularly for older adults. This is not an issue of the future but an issue of today. With biased healthcare algorithms being used every day, impacting who receives medical care and support, algorithmic bias is a public health issue that needs to be addressed with...

Today's Sponsors

LEK
ZeOmega

Today's Sponsor

LEK

 
Topics: AI (Artificial Intelligence), Equity/SDOH, Healthcare System, Technology
Using a Hospice Data ‘Toolbox’ to Tune Up Health Equity
Facing Political Attacks on Medical Education — The Future of Diversity, Equity, and Inclusion in Medicine
How The Trump Administration Could Amplify Health Inequities In America And Across The Globe
A Primer on Health Equity Research
Integrating Equity into Quality Measurement

Share This Article