By Harvey Castro MD MBA – Most hospital AI projects look convincing in a conference room. The slide deck is clean. The pilot cohort is curated. The demo patient has a complete chart. Then the model meets a real emergency department at 2 a.m., and the story changes.
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By Feynman Xu, Ph.D. – Independent medical practices are being asked to evaluate AI while already managing staffing gaps, payer friction, document backlogs, and patient access demands. The temptation is to start with a product demonstration. A safer and more useful starting point is the workflow itself.
Newly released episode of AI Amplified. Host Dr. Heather Bassett talks to Ben Scharfe, Executive Vice President of AI Initiatives at Altera Digital Health, to make the case that the biggest lever in healthcare AI isn’t the model, it’s the foundation underneath it.
By Kristy Drollinger – Advanced AI predictive models are getting better at finding patients with undiagnosed disease before symptoms, or a crisis, make the diagnosis unmistakable. They can interpret subtle clues already sitting in EHR data to surface elevated-risk patients who warrant further evaluation.
By Dr. Rohan Policherla – The traditional patient journey used to begin with a phone call, referral, or appointment. Today, it often begins with a search. Patients are researching symptoms, procedures, medications, recovery expectations, and treatment options before they ever speak with a healthcare provider. Increasingly, artificial intelligence is becoming part of the research process.
By Ramkumar Pichandi – Healthcare has automated a growing number of administrative actions, but we have been less disciplined about defining when the underlying work is actually finished. An eligibility response arrives. An authorization request is sent. A claim passes a pre-submission check. Each event can be recorded as successful even when the account still carries an unresolved issue.
By David Main DC – Of everything artificial intelligence was going to fix in healthcare, billing looked like the softest target. It is rule-bound, high-volume, repetitive. The code sets are published, the edits are published, the payer policies at least nominally so. If you had asked me three years ago where AI would land first and hardest, I would have said the revenue cycle without hesitating.
By Mat Steinlin – According to the AMA’s 2026 Physician Survey on Augmented Intelligence, over 80% now use AI in a professional context (roughly double the share reported in 2023). The same survey found physicians are significantly more concerned about patient privacy when using non-institutional AI tools (71%) than institutional ones (42%).
By Nikhil Bavaskar – Artificial intelligence is entering a new age of health care. Hospitals and health systems have been deploying AI in recent years to summarize clinical notes, automate administrative work, and enhance patient communication. These tools have shown measurable improvement in clinicians and staff completing tasks faster.