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September 26, 2026

Takeaways from the most recent news in the technology and policies shaping healthcare.

Health IT

Physician: AI's Bigger Risk Is Not Using It in Healthcare

The loudest AI debate is about extinction. A physician writing in Becker's Hospital Review wants to move it somewhere more concrete: the American health system that is already harming patients every day.

The argument is simple. The U.S. spends more on health care than any other wealthy country yet trails on outcomes. That gap, the author writes, is a threat to human life that is not theoretical but already here. Against that backdrop, worrying only about AI causing human extinction misses the more immediate calculation. The bigger risk may be failing to deploy tools that can cut administrative waste, ease clinician workload, and catch problems earlier.

The piece does not dismiss AI's dangers. It reframes them. For hospital and health system leaders, the takeaway is that inaction carries its own body count. As AI moves from pilots into diagnostics, documentation, and operations, the practical question is whether the technology reduces the harm baked into an expensive, underperforming system faster than it introduces new ones.

More in Health IT

Health IT

Pointcore Launches Perception to Turn Hospital Data Into Action

Pointcore's Perception platform aggregates hospital operational data and uses AI modeling to help leaders make faster, better-informed operational decisions.

Why it matters: Hospitals sit on vast operational data but rarely turn it into action, and tools that close that gap could reshape how systems manage cost and capacity.

Health IT

Tennr Hires CRO John Capaldi to Scale Sales Push

Patient orchestration platform Tennr hired John Capaldi as CRO and two enterprise sales executives to scale its go-to-market organization.

Why it matters: The hires show a well-funded health-tech startup pivoting to aggressive enterprise sales, a sign of maturing competition in referral and intake automation.

Health IT

AI Turns Messy Clinical Data Into Research-Ready Variables

AI and natural language processing are being deployed to convert fragmented, unstructured clinical data into structured, research-ready variables, easing a core bottleneck in clinical research.

Why it matters: Faster, cleaner data extraction can shorten trial timelines and unlock real-world evidence from records healthcare organizations already hold.