Sina Bari
Healthcare AI authority

Latest analysis

Why ambient AI scribes fail some clinicians, and what safe documentation automation actually looks like

Ambient AI scribes do not fail because documentation automation is impossible. They fail when hospitals treat them like a transcription purchase instead of a clinical workflow redesign with governance, fallback paths, and measurable supervision.

May 28, 2026 · 10 Min Read

Claude Headaches and the Human Brain at Maximum Bandwidth in Healthcare AI

The emerging problem is not that clinicians lack AI, but that AI now lets them run too many high-value workstreams at once. In healthcare, that creates a new kind of cognitive overload, with implications for safety, attention, and decision quality.

May 22, 2026 · 9 Min Read

Why Medical Tech UIs Feel Unintuitive, and Why Dog-Fooding Still Matters

Medical technology often feels clumsy because it is built around regulatory survival, fragmented legacy workflows, and limited clinical input rather than daily use. The fix is not prettier screens alone, but physician-led design, real-world testing, and vendor teams that use their own products in the environments where care actually happens.

April 21, 2026 · 9 Min Read
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Clinical workflow design

How AI fits into triage, documentation, routing, review, escalation, and other high-friction clinical workflows.

Governance, safety, and evaluation

Practical guidance on model validation, monitoring, human oversight, risk controls, and safer adoption of medical AI.

Imaging, diagnostics, and adoption

Commentary on medical imaging AI, diagnostic support, and the organizational conditions needed for successful health-system rollout.

Positioning

Credible commentary for a fast-moving field

The tone stays clear, restrained, and evidence-aware. Claims should be specific, useful, and grounded in how care is actually delivered.

The goal is to help readers understand what works, what fails, and what responsible healthcare AI adoption looks like in practice.

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