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When someone describes sudden chest pain, shortness of breath, or a neurological change, clinicians know time and speed are critical. So, can AI systems be trusted to recognize those scenarios and escalate appropriately? That’s the question Counsel’s AI Research team sought to answer using HealthBench Consensus, the first large-scale open-source benchmark for evaluating medical reasoning across emergency and non-emergency situations. With HealthBench Consensus, we were able to benchmark Counsel’s AI escalatory behavior against other leading models to see how well each performs in conversational triage. HealthBench is an open-source dataset of 5,000 synthetic healthcare scenarios. Each scenario is paired with physician-written rubrics for evaluation. In total, 262 physicians authored more than 48,000 rubrics, which created a rich but uneven set of criteria, since styles and standards varied widely across annotators. ‍ To reduce variability, we focused only on consensus rubrics, where at

AI Triage Safety: HealthBench & Emergency Escalation | Counsel Health Blog > Research > How Counsel leveraged HealthBench to assess emergency escalation How Counsel leveraged HealthBench to assess emergency escalation Research How Counsel leveraged HealthBench to assess emergency escalation Written by: Tony Sun Reviewed by: Dr. Cían Hughes Published: Aug 26, 2025 Updated on: February 5, 2026 copied Table of contents Table of Contents The modern front door to healthcare is just one click away Request a demo KEY TAKEAWAYs Can AI be trusted in a medical emergency? ‍ When a patient describes a sud

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