NarxCare’s Risk Score Model Allegedly Lacked Validation and Trained on Data with High Risk of Bias
Description
NarxCare's overdose risk algorithm, lacking peer-reviewed validation, uses sensitive data like doctor visits, prescriptions, and possibly genetic information, leading to significant biases against women and Black patients. Factors like sexual abuse and criminal records exacerbate stigmas and disparities, often resulting in unjust denial of necessary pain medication. The newly approved AvertD genetic test shares similar issues, further complicating and potentially harming medical treatment decisions.
Actors
Alleged Deployers
- narxcare
- avertd
- appriss
Alleged Developers
- appriss
Harmed Parties
- american-physicians
- american-pharmacists
- american-patients-of-minority-groups
- american-patients
Classification
Risk Domain
AI Safety & FailuresRisk Subdomain
7.3. Lack of capability or robustness
MIT Risk Profile
Topics
Source
Related Incidents (AI Safety & Failures)
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Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
Mitigation Tools
Tools related to this risk domain, via shared responsible AI topics.