Healthcare AI newswatch: Ambient AI costs, healthcare AI holdouts, an 86-year-old AI innovator, more

Buzzworthy developments of the past few days.

• Many AI documentation suppliers bill providers on a per-use basis. Use the vendor’s tool a lot, ring up a big vendor bill. At large healthcare organizations, this can be a ballooning problem, as the number of physicians using AI documentation has been increasing exponentially. And few have a way to pass these costs along to payers. So the more a healthcare system integrates ambient AI into its daily workflows, the heavier the cumulative financial burden becomes. And the faster it keeps accruing. Ronald Rodriguez, MD, PhD, of UT-San Antonio reminds the wise about these realities in a Q&A with HIMSS Media. “Unless hospitals and healthcare providers negotiate cost-effective pricing structures, implement usage controls or develop in-house AI systems, they may find themselves in a situation where AI adoption leads to escalating operational costs rather than the anticipated savings,” he says. Rodriguez, who heads the nation’s first MD/MS dual-degree program in AI, also issues wakeup calls for LLM users who are oblivious to patient-privacy risks inherent in the technology. In fact, he preaches attentiveness to several foolishly overlooked points of potential ethical, clinical and legal trouble for clinical AI adopters. See here, healthcare AI aficionados. 
   
• Like snacks on the shelves of dieters, the same tools can be hard to resist for overstretched healthcare providers. Ambient AI “helps us get through massive amounts of unstructured paperwork and data that insurance companies are trying to go through to figure out if this is an appropriate authorization,” Nishit Patel, MD, chief medical informatics officer at Tampa General Hospital, tells a local TV news operation. “Hopefully, if we use these tools in the optimal ethical way to do the right thing for the patient, we all win.” 
   
• It’s still fairly easy enough to find healthcare AI holdouts. As the Maine Reporter found on a recent assignment, AI resisters tend to cluster within smaller provider organizations. In a survey the newspaper conducted on the use of AI in healthcare, multiple respondents representing this provider category said they worried about people using AI to make medical decisions without consulting healthcare providers, healthcare journalist Rose Lundy reports. One mental health counselor from a small practice stated flatly that AI “doesn’t belong in healthcare.” Read the article. 
   
• One hospital executive who’s also a physician and a tech expert has a bold proposal for controlling AI usage costs. Just get AI vendors to commit, under contract, to sharing risk with their healthcare clients. “The problem with a time-and-materials contract is, if I have a great idea, and you agree to build it for me, wouldn’t you love to build it for a long period of time because then my bill keeps going up?” rhetorically asks Zafar Chaudry, MD, MBA, in remarks made to MedCity News. “It’s very hard to cost-control that.” Chaudry notes that, as things stand now, hospital contracts with tech vendors “usually don’t guarantee that the product you’re investing in will deliver the intended result.” Chaudry is senior vice president, chief digital officer and chief AI and information officer at Seattle Children’s. 
   
• Quality-wise, healthcare data is all over the place. Stated less diplomatically: Garbage in, garbage out. The inconsistency is a big problem when it comes to training and tracking any given healthcare AI model. Fortunately, the hurdle is clearable. All AI-implementing providers have to do is focus on six simple elements—accuracy, validity, data integrity, completeness, consistency and timeliness. OK, they’re not all that simple. But they surely are approachable. Wolters Kluwer solutions engineer Brian Laberge breaks it down in a March 10 blog post. “Through effective data governance and normalization practices,” he assures, “healthcare organizations can maximize AI capabilities and ensure the most accurate outputs for the betterment of patient care.”
   
• In like manner, computer vision for healthcare can’t be any better than the image data it’s fed for training. Andrew Gostine, MD, MBA, explains the dynamic. “Sight is our most powerful sensory capability, with up to 90% of our brains directly or indirectly participating in the processing of visual information,” he tells HealthTech magazine. “Similarly, computer vision is the most valuable form of AI-enabled perception.” Gostine, a critical care anesthesiologist and an AI entrepreneur, adds that high-bandwidth image processing with computer vision is “the only way to drive healthcare automation at the scale required to fix many of healthcare’s access and efficiency problems.”
   
• The world’s most populous country is home to an 86-year-old IT entrepreneur who recently beefed up his AI skills in a postgraduate program. Why? So he could do more to tech-enable healthcare services for underprivileged communities. Over the past 15 years, Mahendra Patel has helped more than 4,000 orphaned and handicapped children access education, the Ahmedabad Mirror reports. “His story inspires anyone contemplating new paths and illustrates that, with determination and support, anything is achievable,” the outlet adds. For Mahendra, the challenging AI curriculum that he completed “was not only an academic chase. It had become an urge to reinvent his passion for innovation.”
   
• Recent research in the news: 
   
  • University of Michigan: Clinical trial opens to study groundbreaking 3D printed device for babies with rare respiratory disease
     
  • Virginia Tech: Machine learning models fail to detect key health deteriorations, new research shows
     
  • Stanford: Medical research explores the promise and perils of AI in citizen science
     
  • Rand/Harvard: AI models are skilled at identifying appropriate responses to suicidal ideation, but professionals still needed
     
• Notable FDA approvals:
   
  • Johnson & Johnson MedTech wins FDA nod for enhanced robotic-assisted bronchoscopy
     
• M&A activity: 
   
  • Radiology AI firm Gleamer expands into MRI with 2 acquisitions
     
• Funding news of note:
   
  • Klaim secures $26M to ‘revolutionize’ healthcare payments in the Middle East and North Africa 
     
  • Ataraxis AI to transform precision medicine in cancer care with $20.4M Series A
     
  • AI healthcare platform Elea raises €4M ($4.3M) to cut diagnosis time from weeks to hours
     
  • Informed Ventures launches, managing early-stage fund focused on digital health, vertical applications of AI
     
• From AIin.Healthcare’s news partners:
   
  • Radiology Business: ‘Insufficient governance of AI’ is the No. 2 patient safety threat in 2025