Look for AI, 5G and big data analytics to lead all other emerging technologies in reshaping U.S. healthcare over the next several years.

That’s the collective view of more than 200 chiefs of clinical and clinical IT operations at large and medium-size provider institutions. The field was surveyed by market researcher IDC for sponsor Redox, which mainly sought to supply tech vendors with insights into hospitals’ plans and priorities around technology purchasing.

The anticipation of big things to come from the leading three technologies reflects a key “macro” finding of the research: The cohort places enterprise-wide digital transformation at or near the very top of tech-centric objectives for the near and long-term future. Importantly, most respondents consider this big-picture aim distinct from the micro digitization of traditional care delivery.

More highlights:

• Lagging behind digital transformation—named by 53% of the field—were cost reduction (35%), improving care quality (31%), improving patient safety (31%) and using data as a strategic asset (30%). In the middle of the pack were increasing staff retention, meeting regulatory compliance criteria and improving access to care, all at 25%. Lower down the list: expanding care-anywhere initiatives, delivering price transparency, improving health equity, seven others.
• 88% expect to increase spending on third-party technologies, not including EHR investments. This is so even though 40% already feel challenged to keep up with middleware and infrastructure demands.
• 85% expect increased organization-wide spending on technologies (e.g., IT operations and system infrastructure) and health IT solutions this year and next. Asked to name the top three areas this spending will likely go toward, the leaders came back with telemedicine/remote patient monitoring (41%), cloud computing (33%), AI for clinical applications (28%) and IT operations (28%).

The authors’ top three tips for healthcare tech vendors:

1. Tie your solutions to the pursuit of digital transformation, showing how their innovative functionality elevates patient outcomes.
2. Focus on championing cost containment, explaining how your technologies and solutions contribute to operational efficiency and patient-centered care.
3. Emphasize how your solutions put data to strategic use, empowering evidence-based decision-making and orchestrating personalized care.

And their advice for healthcare providers:

1. Trust the third-party advantage by investing in reliable, cost-effective third-party technologies where vendors demonstrate expertise, timely deployment and data reliability.
2. Act on the rise of automation, AI and mobility to optimize clinical operations, elevate patient experience, and infuse next-generational capabilities like streamlined documentation, self-guided screening and app-based patient engagement.
3. Embrace emerging tech frontiers by staying ahead of the curve and exploring 5G, AI, and machine learning to realize a competitive edge in the dynamic healthcare industry.

There’s quite a lot more. Read the whole thing.

Buzzworthy developments of the past few days.

• No sooner did seven major AI players individually pledge to promote safety, security and trust than four of them huddled up to do it their way—together. Calling their initiative the Frontier Model Forum, Microsoft, Anthropic, Google and OpenAI unveiled the plan July 26. The founding members define frontier models as large-scale machine-learning models that “exceed the capabilities currently present in the most advanced existing models and [that] can perform a wide variety of tasks.” They welcome other companies and organizations to join. Details posted by Microsoft here.
   
• Both Google and Microsoft reported revenue growth and profitability for the second quarter. The robust results probably had nothing to do with AI. However, as noted in The Wall Street Journal July 25, the companies’ ever-expanding health and wealth show why these two Big Tech titans “are the best suited to build on a technology that requires massive computing resources—and equally massive pocketbooks.” Tech and biz reporter Dan Gallagher says Microsoft expects dollars from AI services to start arriving by the end of this fiscal year.
   
• Beware of model collapse. That’s what they call it when AI models are repeatedly trained on AI-generated data. The eventual effect is akin to a copy of a copy of a copy generated by the office Xerox machine. And it’s just one pitfall AI adopters in healthcare and elsewhere need to avoid unless they want to imperil data privacy, IP loss, security and “a host of other issues lying in wait for unsuspecting organizations pushed by their boards and C-suites not to miss the AI boat.” The warning is from Felix Van de Maele, CEO of data intelligence cloud platformer Collibra. He offers a brief on model collapse and other risks of footloose AI governance in a piece published July 25 in Fast Company.
   
• And then there are the legal risks unique to AI adopters in healthcare. Attorney Neville Bilimoria, a partner with the Duane Morris practice, takes a quick look at potential points of exposure that can arise from, in particular, providers’ reliance on vendors bearing AI-equipped products. Likely vulnerabilities include patient privacy, intellectual property and indemnity provisions. McKnights Long-Term Care News has the item.
   
• Researchers are using AI to detect biochemical patterns across massive datasets that may have little in common with one another. Each dataset contains unmined info on how antibodies interact with one or more viruses or other immune-system challengers. The scientists hope the work will yield new or improved vaccines, drugs and/or cancer treatments. Lay explanation from the LaJolla Institute for Immunology here, scientific paper here.
   
• Eye-catching investments in healthcare AI:
   
  • Hippocratic AI raises $15M and more digital health fundings
  • GenHealth.AI Accelerates into healthcare AI market with $13M in new funding
  • Sanguina Raises $2.8M in Series A Funding to Drive Innovation in Home-Based Testing and Wellness Management
     
• From AIin.Healthcare’s news partners:
   
  • Cardiovascular Business: The rise of AI and other key takeaways for sonographers at ASE 2023
  • Health Imaging: Deep learning detects precancerous changes on mammograms
  • Radiology Business: AI boosts value of CT lung cancer screening by helping predict death from other diseases