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New AI M&M Framework for Clinical AI Failure Review Proposed

By PulseAugur Editorial · [1 sources] ·

A new framework called AI Morbidity and Mortality (AI M&M) has been proposed to systematically review failures involving clinical artificial intelligence. This framework aims to reconstruct and learn from individual AI-related errors and near-misses within healthcare settings. It combines standardized case intake, evidence preservation, and a four-dimensional classification system (Trigger - Mechanism - Clinical Pathway - Corrective Action) to convert failures into actionable institutional learning, complementing existing monitoring and reporting systems. AI

IMPACT This framework could improve the safety and reliability of AI systems in healthcare by enabling better learning from failures.

RANK_REASON The item is a research paper proposing a new framework for clinical AI failure review. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New AI M&M Framework for Clinical AI Failure Review Proposed

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31 / 100
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The item is a research paper proposing a new framework for clinical AI failure review. [lever_c_demoted from research: ic=1 ai=1.0]
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safety, paper, other
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Paulius Mui, Dean F. Sittig, Steve Labkoff, Sanjay Basu ·

    AI Morbidity and Mortality: A Framework for Clinical AI Failure Review

    arXiv:2609.00076v1 Announce Type: new Abstract: Clinical artificial intelligence is increasingly embedded in real-world care, yet existing safety mechanisms are poorly suited to reconstructing and learning from individual AI-related errors and near-misses. Aggregate model monitor…

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