Optum Algorithmic Health Risk Scores Reportedly Underestimated Black Patients' Needs

October 24, 2019

A study on an Optum algorithm, widely used by a major academic hospital, revealed potential bias towards underestimating the healthcare needs of Black patients. This could lead to disparities in prioritization for additional care programs when compared with white patients with similar health profiles.

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Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MAP 1.6 — similarity 0.685, rank 1. TAIM detail and related incidents →
GOVERN 3.1 — similarity 0.682, rank 2. TAIM detail and related incidents →
MEASURE 2.6 — similarity 0.681, rank 3. TAIM detail and related incidents →

Alleged deployer: unnamed-large-academic-hospital
Alleged developer: optum
Alleged harmed parties: black-patients

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/124

Data source

Incident data is from the AI Incident Database (AIID).

When citing the database as a whole, please use:

McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.

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