Medical AI study finds critical flaw across OpenAI, Anthropic, OpenEvidence, Doximity

The NOHARM study arrives at a critical juncture for medical AI regulation. The FDA's January decision to loosen oversight of AI-powered clinical decision-support tools came with a condition: doctors must be able to independently check the AI's reasoning. In direct contrast, more than a dozen states passed new laws in 2026 requiring human sign-off before any AI-assisted decision reaches a patient. This divergence reflects deep uncertainty about how to govern medical AI safely—neither regulators nor the legal system has settled who bears liability when an AI recommendation proves wrong. The distinction the study highlights—that omissions, not false statements, drive the most harm—cuts to the heart of this challenge. An AI that stays silent about a symptom or drug interaction cannot be fact-checked by a doctor unless the doctor already knows to look for it, undermining the assumption that human review alone can catch and correct AI errors.

OpenEvidence's rapid rise (from $1 billion（約1600億円） valuation in February to $12 billion（約1.9兆円） by January) reflects investor enthusiasm for free, evidence-based medical AI, while Doximity's enterprise model ($145.4 million（約230億円） in quarterly revenue this spring, up 5% year over year) demonstrates demand for AI tools embedded in hospital workflows with added guardrails. Yet both approaches assume that better performance scores and human oversight can resolve the omission problem. The NOHARM data suggests otherwise: even the best-performing model still leaves gaps. CEO Daniel Nadler's defense—that the study is not peer-reviewed and questions Doximity's methodology—reflects the broader tension: medical AI vendors and platforms are growing faster than the evidence frameworks and liability rules that govern medical practice can adapt.