Can a Fairness-Focused AI reduce bias in ER admission decisions?
NCT ID NCT06434220
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This study tests whether a machine learning model, designed to be fair across different patient groups, can influence how ER doctors predict which patients will be admitted. Ten board-certified ER doctors at Boston Children's Hospital will review patient data and give their admission predictions before and after seeing the AI's recommendation. The goal is to see if the AI helps reduce healthcare disparities in admission decisions.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
Active substance
Fairness-aware machine learning model
What this could lead to
If successful, this could show that AI can help reduce bias in emergency room admission decisions, leading to fairer care.
What could go wrong
This is a very small, early study with only 10 doctors at one hospital, so results may not apply elsewhere. The AI is only a tool and may not change actual outcomes.
Disclaimer
Read more
Show less
This is a summary of
the original study
.
Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
Get updates
Get notified about this study
Sign up to get updates when this study changes or when new studies for PATIENT OUTCOME ASSESSMENT are added.
By submitting, you agree to our Terms of use
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Show contact details
Enter your email to view the contact information for this study.
By submitting, you agree to our Terms of use
Study contacts
-
Contact
Phone: •••-•••-•••• Email: •••••@•••••
-
Contact
Phone: •••-•••-•••• Email: •••••@•••••