AI buyers & sellers | Partner voice | Newswatch: Fail-fast AI skunk works, writerly doctors avoiding AI scribes, more

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AI buyers & sellers | Partner voice | Newswatch: Fail-fast AI skunk works, writerly doctors avoiding AI scribes, more

Friday, April 4, 2025
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Epic, Microsoft lead the AI vendor charge into healthcare: KLAS

Many if not most hospitals and other provider organizations take a decided interest in what their peer institutions are doing with AI. A major motivator for the keen curiosity is gauging how well one is keeping up with the Joneses. So to speak.

Happily for many, KLAS Research has done much of the snooping for them. The results are published in a report released this week, “Healthcare AI 2025: Are You Keeping Pace with Industry Adoption?”

KLAS arrived at some insightful conclusions after speaking with 256 provider leaders—including 50 executives, 27 directors and 26 managers—in January. Here are excerpts from the report. 

1. Epic’s and Microsoft’s broad offerings lead to high AI adoption. 

A large portion of interviewed organizations tell KLAS they’re satisfied with Epic’s embedding of AI into various applications. These include cognitive computing for predictive modeling, augmented response technology for in-basket physician messaging and a tool for automated denial prioritization. Meanwhile: 

‘Microsoft’s AI tools are used by a high number of respondents, who often attribute the widespread adoption to their organization already using other Microsoft offerings.’ 

2. AI is most widely purchased by large acute care organizations.

These organizations are more able to invest in and adopt AI as they often have more available resources and the infrastructure needed for AI implementation, KLAS points out. “The exception to the trend is ambient speech, where ambulatory care organizations are the group most likely to report adoption,” the authors add. “The few payer respondents are almost evenly split between those who use AI and those who don’t, with most reporting operational use cases with large language models.”

‘Across organization types, respondents who use AI report that adoption is largely departmental, with solutions being implemented for a specific use case rather than across an entire organization.’

3. AI is most often used for operational efficiency at points of care.

Ambient speech documentation tools and clinical AI assistants are among the most widely implemented solutions, KLAS finds, noting that products in the category help streamline provider workflows, reduce administrative burden, and improve operational outcomes. “Documentation burden is also being eased by AI-enabled care coordination platforms, which help clinicians efficiently summarize patient histories.” More: 

‘AI [also] continues to play a large role in imaging and diagnostics … and organizations are adopting AI-enabled risk models to reduce readmission risk and provide financial forecasting.’ 

4. Investment in healthcare AI will continue.

AI will remain an important piece of healthcare organizations’ plans moving forward, the KLAS researchers report. “Many organizations are actively expanding their AI pilots and exploring solutions to enhance efficiencies across clinical, financial and administrative operations,” they add. More:

‘Many of the same vendors and tools are mentioned for future investment as are reported in current use, indicating that the focus for many organizations is refining and building on their current strategies rather than diverging into new territories.’ 

5. AI-enabled documentation will continue to be an area of high interest. 

Respondents report planned pilots or implementations of ambient speech AI tools from vendors such as Abridge and Microsoft, the authors write, adding that AI scribes and virtual assistants are also gaining traction in ambulatory and emergency care settings. More: 

‘Radiology is another continued area of interest for AI as organizations look to the future, with respondents pointing to AI-enhanced radiology solutions, such as Rad AI and Aidoc, for their ability to aid in diagnostic support.’

There’s more, and the full report is available for downloading

 

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Are You Prioritizing Clinician Well-Being?

In recognition of Health Workforce Well-Being Day, Nabla recently hosted a thought-provoking conversation on what it truly takes to foster a culture of clinician well-being.

From going beyond surface-level wellness initiatives to embedding well-being into organizational leadership and strategy, the discussion offered practical, actionable insights for healthcare leaders.

Read the key takeaways and watch the full recording: https://www.nabla.com/blog/webinar_clinician_well_being/

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Healthcare AI newswatch: Fail-fast AI skunk works, writerly doctors avoiding AI scribes, more

Buzzworthy developments of the past few days.

  • If only AI could help healthcare providers get paid faster, more accurately and with less hassle. Actually, it can. It just has to be prodded along by people working together at predictable sticking points in the revenue cycle. At times that means goosing cooperation between providers and payers. By working together, these stakeholders can ensure that AI tools are designed and implemented in a way that supports cash flow on both ends. Several subject matter experts with the nonprofit Council for Affordable Quality Healthcare flesh out the best-case scenario in the American Journal of Managed Care. “AI can be used to proactively identify services that require prior authorization, retrieve necessary documentation from electronic health records and submit it to health plans for adjudication,” Erin Weber and colleagues explain. “Such collaborative efforts can help providers realize the full potential of AI in improving efficiency and reducing costs.” 
     
  • Is trial and error any way for a sprawling health system to roll out AI? Duke Health’s CMIO, Eric Poon, MD, MPH, believes so. In fact he’s convinced that, looking back later, 150-site Duke will see that dollars won’t have been wasted on the errors—as long as people learned from them. And that’s whether even costly stumbles can be blamed on the AI products or the users themselves. “We know that not everything that we put our hands on or that comes our way is going to pan out,” Poon says in remarks made to HealthLeaders. “Our governance philosophy is that we need to fail often and fail fast so we [can] provide just-in-time advice.” An especially bold approach seeing as Duke Health is already using 80 or so separate AI tools. 
     
  • The dean of MIT’s computing college seconds that motion. “Machine learning is going to reinvent many areas of work,” Daniel Huttenlocher, PhD, told attendees of an MIT conference on AI this week. “If you don’t have skunk works projects, you’re going to be left behind.” 
     
  • Not every physician is thrilled to let AI scribes take the lead on note-taking duties. One who loves to write describes her misgivings over letting go of the pen in an opinion piece published by Stat. “As a doctor, an important way I sustain and deepen my relationships with my patients is by writing about them,” explains Christine Henneberg, MD, whose nonclinical writings include both fiction and nonfiction. “This is the very process that the AI scribe asks me—or forces me—to give up.” Read the rest
     
  • It’s not immediately apparent how AI would affect work for midwives and OB nurses. That doesn’t mean they have no cause for enthusiasm—or concern. Down Under, an officer with the Australian Nursing & Midwifery Federation lays out the pros and cons. On the plus side of the ledger are things like education and work augmentation. On the minus (or mixed-blessing) side: workplace surveillance, work intensification and liability. “AI can never truly replicate the complex and often physical aspects of care-based work, so nurses and midwives will not be replaced by AI,” the ANMF officer, Paul Yiallouros, reassures readers of Australian Nursing & Midwifery Journal. “Decision-making in healthcare requires accountability, which only registered professionals can provide.” 
     
  • When this teenager talks healthcare AI and consumer protection, her state’s legislature listens. The young person is Paisley Tuel, a student at Case Western Reserve University. The governing body is the Ohio House of Representatives. After writing a 50-page paper on the need for AI-specific laws to guardrail healthcare in the Buckeye State, Tuel was asked by a key House rep to help draft a bill covering much the same material. “We want AI tools to be tested and monitored for widespread use in Ohio hospitals because that has not happened yet,” the undergrad tells the Cincinnati Enquirer. “We want patients to know when AI in involved in their healthcare decisions.” 
     
  • Here’s another teen making news of interest to healthcare AI watchers. This one is only 18 and already wealthy after developing an AI app for tracking calorie intake. Zach Yadegari blasted into the headlines after he posted an essay on X describing his rejection by 15 prestigious colleges despite his real-world accomplishments. The post spurred heated bickering over the elusive “real reason” so many admissions boards gave the young man the cold shoulder. The kerfuffle went viral. And now many millions of people have heard the name Zack Yadegari. TechCrunch recounts the turn of events here, and there’s a good deal more coverage elsewhere
     
  • Recent research in the news:
     
  • Funding news of note:
     
  • From AIin.Healthcare’s news partners:
     

 

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