Industry Watcher’s Digest

Buzzworthy developments of the past few days.

• Line up four random healthcare professionals, and you can safely wager that one of them is burned out enough to be thinking about quitting. That’s according to digital healthcare company Innovaccer, which surveyed 568 clinicians across 386 provider organizations. More than 85% of leaders at those orgs indicated they’re pinning their hopes on AI to hold back a mad rush for the career exits, going by the survey report. “[I]nsiders are betting big on healthcare AI to streamline workflows and reduce burnout issues,” the authors write. “This highlights a broader shift where AI isn’t just a tool for incremental improvements but a transformative force for supporting critical areas in healthcare delivery.” Download the report.
   
• KLAS Research names some software suppliers that seem up to the above job. In the category of “Improve Clinician Experience,” KLAS’s contributing reviewers like Abridge, Redivus Health, Suki, Navina and Regard. Other categories in its October report on the top 20 emerging solutions include “Improve Outcomes,” “Reduce Cost of Care” and “Improve Patient Experience.” Find the report here (behind paywall). 
   
• Some say AI is soon to help patients coordinate care quicker, get seen sooner and understand costs better. Others aren’t so sure. Count Axios tech editor Megan Morrone as a member of the latter cohort. “As AI agents take over work on both sides of the health coverage game, acting on behalf of both patients and providers,” she writes, “the process of getting and paying for care could become an even more opaque and confusing bot-versus-bot interaction.” 
   
• The CEO of the country’s largest for-profit, publicly traded health system is bullish on healthcare AI. Asked in an Oct. 25 earnings call about investing in emerging technologies, Sam Hazen said he sees many opportunities to spend on AI over the next five to seven years. The aim will be to “improve our administrative functioning, our operational management of our business, and then ultimately the clinical outcomes for our patients,” he added. “It’s our view that we’re at an inflection point.” 
   
• Here’s help for healthcare professionals who want to join the AI revolution but don’t know where to begin. It’s a “quick-start guide” geared toward those who feel they’re outside looking in. “Getting started with AI is a major roadblock for clinicians,” Piyush Mathur, MD, of Cleveland Clinic and co-authors write in Cureus. The expanding adoption of AI across healthcare, they add, presents an “immense opportunity for clinicians to participate in all phases of research, development, evaluation and implementation.” The plan includes stops at four key junctions—setting goals, creating a roadmap, identifying resources and measuring success. Check it out.
   
• Oracle has unveiled its next-generation EHR. The platform is designed to embed AI across all clinical workflows at adopting sites. Oracle says its guiding goal is to “help streamline information exchange between payers and providers, support patient recruitment for clinical trials, simplify regulatory compliance, optimize financial performance and help accelerate the adoption of value-based care.” 
   
• Physicians who aren’t yet using large language AI models for help with complex cases: What are you waiting for? The question was more implied than asked when former FDA commissioner Scott Gottlieb expressed the sentiment this week. “I think very soon everyone is going to have to think about how to deploy this [technology at the] point of care,” he said, according to coverage by MedCity News. It’s telling that Gottlieb made the comments not to stakeholders in big-city academic medical settings but to attendees of the 3rd Annual Summit on the Future of Rural Healthcare in Sioux Falls, South Dakota. 
   
• Meanwhile tomorrow’s healthcare professionals are getting a leg up. At the University of Central Florida, for example, undergraduate students are learning how to get ChatGPT to help providers explain care to patients. One student tells the school’s news operation her only prior experience with LLM came from using it to check grammar and such. Thanks to a research mentoring class, she’s on her way to mastery of the technology. “You can’t just throw any dataset at it and expect good results,” she says. “We’ve been working on refining the prompts we use to get better, more accurate outputs from the model.” 
   
• Recent research in the news: 
   
  • Stanford: Can AI improve medical diagnostic accuracy?
     
  • University of Cambridge: AI algorithm accurately detects heart disease in dogs
     
  • University of Minnesota: New research shows promise and limitations of physicians working with GPT-4 for decision making
     
• Notable FDA Approvals:
   
  • HeartLung Technologies receives FDA ‘breakthrough’ designation and marketing authorization for AI that enables opportunistic detection of hidden heart disease 
     
• From AIin.Healthcare’s news partners:
   
  • Radiology Business: 5 of 7 Medicare Administrative Contractors approve payment for imaging AI software
     

  • Cardiovascular Business: New data highlight long-term benefits of HeartFlow’s AI-based CAD evaluations

     

  • Radiology Business: Radiology resident thumbs nose at Nobel Prize winner who predicted AI would make specialty obsolete