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Best of LinkedIn: Health Tech CW 48/ 49 · Best of LinkedIn: Digital Transformation & Tech

• 0:00
  Speaker 1: This episode is provided by Thomas Allgeier and Frannis, based on the most relevant LinkedIn posts on health tech in CW-Forty-Eight and Forty-Nine.
• 0:09
  Speaker 1: Frannis equips product and strategy teams with market and competitive intelligence to navigate the health tech landscape.
• 0:15
  Speaker 1: Welcome back.
• 0:16
  Speaker 1: Today we are doing a deep dive into the health tech landscape, looking at the key strategic moves and the big breakthroughs from the last couple of weeks of LinkedIn posts.
• 0:25
  Speaker 1: And the signal we're picking up is, well, it's pretty clear.
• 0:29
  Speaker 0: It is.
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  Speaker 0: The industry is past the point of just casual experimentation.
• 0:33
  Speaker 1: Right.
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  Speaker 1: It's not about pilots anymore.
• 0:35
  Speaker 1: Exactly.
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  Speaker 0: I mean, if you had to boil it all down, the real story is this shift from pilots to actual operational rollout.
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  Speaker 0: The focus isn't just on what a technology can do in a lab.
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  Speaker 1: It's about how it works in the real
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  Speaker 0: world.
• 0:47
  Speaker 0: Yeah.
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  Speaker 0: How it integrates into a clinical workflow, how it connects to the data, and maybe most importantly, how you get paid for it.
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  Speaker 0: It has to be payment ready.
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  Speaker 1: So that financial and clinical loop is finally tightening.
• 0:57
  Speaker 1: Tech is being judged on its ability to scale, not just its novelty.
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  Speaker 0: Precisely.
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  Speaker 0: And to make sense of all this, we've grouped the insights into four main clusters.
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  Speaker 0: First, how AI strategy is maturing.
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  Speaker 0: Second, the massive shifts in diagnostics and imaging, especially with everything coming out of the RSNA conference.
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  Speaker 0: Okay.
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  Speaker 0: Third is the expansion of robotic surgery.
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  Speaker 0: And finally, the big strategic moves in digital care delivery and, you know, the whole ecosystem that ties it all together.
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  Speaker 1: Okay, let's unpack this.
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  Speaker 1: And I think we have to start with the biggest driver of change, right?
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  Speaker 1: Artificial intelligence.
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  Speaker 1: We've talked about pilots for years, but what does this new strategic phase actually look like?
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  Speaker 0: It looks like architecture.
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  Speaker 0: I mean, Bill Russell made a great point that too many health systems have something like forty AI tools and no architecture.
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  Speaker 1: That's not a strategy.
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  Speaker 1: That's just a shopping
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  Speaker 0: habit.
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  Speaker 0: It's a shopping habit that creates a ton of integration debt.
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  Speaker 0: He says the new leaders are becoming Renaissance architects.
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  Speaker 0: Renaissance
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  Speaker 1: architect.
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  Speaker 1: I like that.
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  Speaker 1: But what does it really mean?
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  Speaker 1: Is that just a fancy new name for a CIO?
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  Speaker 1: Well,
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  Speaker 0: not quite.
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  Speaker 0: The Renaissance part implies a total rethink of the foundation.
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  Speaker 0: A CIO manages IT.
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  Speaker 0: A Renaissance architect is building the blueprint for clinical transformation.
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  Speaker 0: They're not just buying another point solution.
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  Speaker 1: They're designing the whole system from the ground up to connect all the data and anticipate how the workflow is going to change.
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  Speaker 0: Exactly.
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  Speaker 0: and to prepare for those complex reimbursement pathways we just mentioned.
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  Speaker 1: That makes perfect sense because without that architecture you lose all the efficiencies everyone is so excited about.
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  Speaker 1: Sameer Saleem pointed out that professionals are, you know, thrilled about AI enhancing outcomes and reducing costs.
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  Speaker 0: But excitement doesn't fix a broken operational structure.
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  Speaker 1: No, it doesn't.
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  Speaker 0: And that structure, it absolutely has to be clinician led.
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  Speaker 0: Christa Calpe highlighted the AMA's launch of the Center for Digital Health and AI.
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  Speaker 0: It's a bit of a defensive move, but it's necessary.
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  Speaker 1: To make sure physicians are shaping the policy up front, not just dealing with the messy aftermath of a new tool.
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  Speaker 0: Right.
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  Speaker 0: You need it to fit the workflow seamlessly from day one.
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  Speaker 1: And a huge signal of market maturity is when the regulators finally step up.
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  Speaker 1: We saw that in the U.S.
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  Speaker 1: with the proposed Health Tech Investment Act, which Christian Usman and John Cole mentioned.
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  Speaker 1: It's designed to improve Medicare reimbursement for validated AI software.
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  Speaker 0: Payment friction is the ultimate killer of scale.
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  Speaker 0: So tackling that unlocks everything.
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  Speaker 0: And while the U.S.
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  Speaker 0: system is playing catch up on payment, consumers are already way ahead.
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  Speaker 0: A survey in Germany from Privgo's Dr.
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  Speaker 0: Michael Quinton showed that twenty-five percent of citizens are already using AI tools.
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  Speaker 1: Twenty-five percent?
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  Speaker 0: Wow.
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  Speaker 0: Yeah.
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  Speaker 0: Things like symptom checkers for health questions.
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  Speaker 1: That's a huge uptake.
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  Speaker 1: Which puts immediate pressure on ethics and governance, I'd imagine.
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  Speaker 0: It does.
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  Speaker 0: And a systematic review from Jan Beger found a really critical gap here.
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  Speaker 0: Hospital-based AI research talks a lot about ethics, but it almost never operationalizes those principles.
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  Speaker 1: What do you mean by that?
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  Speaker 0: Well, most worryingly, only six percent of the studies he looked at even addressed sustainability or the environmental costs of training these huge models.
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  Speaker 1: Wow, so they're completely ignoring the data's carbon footprint.
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  Speaker 0: Exactly.
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  Speaker 0: And when you ignore these things, you get resistance.
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  Speaker 0: Sigrid Bergen and Assim Khan really reinforced this.
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  Speaker 0: They said AI strategy fails without early, inclusive co-creation.
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  Speaker 1: So bring everyone to the table from day one.
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  Speaker 0: Or else clinicians show a fight-or-flight response.
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  Speaker 0: which leads to the low adoption we see all the time.
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  Speaker 1: And while hospitals are sorting out governance, Big Pharma is just sprinting ahead on R&D.
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  Speaker 1: Wolfgang Schleifer highlighted NVIDIA's partnerships with companies like Eli Lilly.
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  Speaker 0: Oh yeah, they're building a full-on AI factory to train models.
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  Speaker 1: It's not just a tool for them anymore.
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  Speaker 1: It's a complete transformation of their R&D pipeline to, you know, drastically cut drug discovery timelines.
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  Speaker 0: Let's pivot now to that second cluster, diagnostics, imaging, and radiology.
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  Speaker 0: The recent RSNA conference proved that imaging is probably the fastest runway for scalable AI adoption right now.
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  Speaker 1: And it's not just about image quality, is it?
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  Speaker 1: It's about resilience.
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  Speaker 1: Resilience,
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  Speaker 0: yes.
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  Speaker 0: And that starts with solving a massive geopolitical and supply chain headache.
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  Speaker 1: Healing.
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  Speaker 1: Healing.
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  Speaker 0: Rakesh Kumar and others, we're all talking about Phillips unveiling of the three Tesla Blue Seal MRI.
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  Speaker 0: It's a near zero helium system.
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  Speaker 1: Near zero.
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  Speaker 1: Okay.
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  Speaker 1: Why is that specific detail such a huge breakthrough?
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  Speaker 0: because a typical MRI scanner needs about fifteen hundred liters of liquid helium to stay cool.
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  Speaker 0: And helium is scarce, it's non-renewable, and the supply chain is incredibly volatile.
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  Speaker 1: So if your helium runs out, your multi-million dollar scanner is basically a paperweight for weeks.
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  Speaker 0: Or months, yeah.
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  Speaker 0: Removing that dependence just fundamentally changes the entire operational life cycle for an MRI system.
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  Speaker 0: It means more uptime, lower cost, and one less massive headache for the hospital.
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  Speaker 1: That's a fantastic example of hardware and material science solving a core operational problem.
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  Speaker 1: And beyond the hardware, AI is improving the images themselves.
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  Speaker 0: Precisely.
• 5:59
  Speaker 0: Killian Salty noted how deep learning reconstruction, specifically ARREC and DL, is dramatically improving the quality of arterial pancreas MRIs.
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  Speaker 0: You get sharper images, better lesion detection.
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  Speaker 0: All
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  Speaker 1: while keeping the patient's breath hold really short.
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  Speaker 0: Around twenty-two seconds.
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  Speaker 0: Okay.
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  Speaker 0: Which is great for patient throughput and of course clinical confidence.
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  Speaker 1: So if AI is handling more of the processing and analysis, the radiologist's role has to be changing pretty profoundly.
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  Speaker 0: It is.
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  Speaker 0: Matthias Goyen put it very clearly.
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  Speaker 0: The future is human-led collaboration with AI.
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  Speaker 0: Radiologists are shifting from just being image readers to becoming orchestrators.
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  Speaker 1: Turning all that data into actual wisdom.
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  Speaker 0: Exactly.
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  Speaker 0: And you see that backed up by tools like GE Healthcare's Imaging Three Sixty, which Simon Philip Ross detailed.
• 6:43
  Speaker 0: It uses AI to automate analysis and optimize things like scheduling and device use.
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  Speaker 1: And here's where it gets really interesting.
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  Speaker 1: Connecting this back to that macro trend of longevity and early detection, especially in cardiology.
• 6:54
  Speaker 0: Right.
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  Speaker 0: Longevity demands you shift the diagnostic timeline way earlier.
• 6:59
  Speaker 0: Kirk Sanford detailed a non-invasive tool called CADScore.
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  Speaker 0: It uses acoustic AI to listen for subtle turbulence in blood flow.
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  Speaker 1: To detect plaque buildup without any radiation.
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  Speaker 0: And it delivers over ninety-six percent diagnostic certainty.
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  Speaker 1: That kind of certainty from a non-invasive tool is a profound game changer for preventative medicine.
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  Speaker 0: And the validation is accelerating.
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  Speaker 0: Campbell Rogers confirmed that heart flow plaque analysis is now the most clinically validated framework for CAD risk stratification.
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  Speaker 0: Dr.
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  Speaker 0: Emery Urturk even predicted that by twenty thirty, AI-enhanced multimodal imaging combining ECHO, CMR, and CT will probably be the new diagnostic standard.
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  Speaker 1: It's all about that AI-driven convergence.
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  Speaker 0: Let's move into the operating theater now.
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  Speaker 0: And that third cluster of robotic surgery and interventional tech.
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  Speaker 0: If we can see better with AI, the goal is now to make the intervention less invasive and crucially more accessible.
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  Speaker 1: That accessibility part is key, isn't it?
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  Speaker 0: It is.
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  Speaker 0: Ilani Dalinon highlighted CMR surgicals versus system.
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  Speaker 0: It's modular, it's miniaturized, a truly digital native robot.
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  Speaker 0: The whole design is about lowering the typical barriers to entry for minimally invasive surgery.
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  Speaker 1: Like the huge cost.
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  Speaker 1: the space it takes up and the steep learning curve of older systems.
• 8:13
  Speaker 1: Exactly.
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  Speaker 0: This is what helps push adoption globally.
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  Speaker 0: Meanwhile, the big established players are expanding into new clinical areas.
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  Speaker 0: Medtronic's Hugo-RES system is a perfect example.
• 8:23
  Speaker 0: It just got FDA clearance for urologic procedures, showing real precision and prostatectomy.
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  Speaker 0: Bob Reddy and Dr.
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  Speaker 0: James Porter emphasized that its modular arms improve flexibility and ergonomics for the surgeon.
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  Speaker 1: And they can operate from an open workstation, which improves communication with the whole team.
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  Speaker 1: A
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  Speaker 0: huge deal for human factors in the OR.
• 8:43
  Speaker 0: And we're seeing robotics move outside the operating room entirely.
• 8:47
  Speaker 0: Petra Teglis shared news about a rice-sized, magnetically guided robot.
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  Speaker 0: Tiny
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  Speaker 1: little
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  Speaker 0: bot.
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  Speaker 0: Designed to break apart kidney stones without surgery.
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  Speaker 0: It really points to a future of safer, less invasive, interventional platforms.
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  Speaker 1: And speaking of blurring boundaries, Austin Chiang called up the artificial boundary between surgery and endoscopy.
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  Speaker 1: He's advocating for more collaboration.
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  Speaker 0: Because the turf war is just slowdown innovation and hurt patients.
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  Speaker 0: He argues patients benefit most from convergence, like with endoluminal robotics.
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  Speaker 0: But the medical training models just haven't kept up.
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  Speaker 0: It
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  Speaker 1: seems like a solvable problem, though.
• 9:23
  Speaker 0: It is.
• 9:24
  Speaker 0: Dr.
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  Speaker 0: Quinlan D. Buchlak noted a similar kind of strategic complexity with TVI.
• 9:29
  Speaker 0: Post-TVI coronary access is becoming a critical issue.
• 9:32
  Speaker 1: Okay, hold on.
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  Speaker 1: For those who don't follow cardiology that closely, can you quickly break down what TVI is and why access afterwards is a problem?
• 9:40
  Speaker 1: Sure.
• 9:40
  Speaker 0: TVI is transcatheter aortic valve implantation, a minimally invasive way to replace the aortic valve.
• 9:47
  Speaker 0: The issue Dr.
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  Speaker 0: Booklack raised is that as the tech gets better, it's being used in younger, healthier patients.
• 9:53
  Speaker 1: So they'll live longer and need more procedures down the road.
• 9:55
  Speaker 1: Exactly.
• 9:56
  Speaker 0: If you get a Pavi-i in your sixties, you'll likely need future coronary work.
• 10:00
  Speaker 0: But that TBI valve can make it surgically much harder to access the coronary arteries later on.
• 10:05
  Speaker 0: It's a huge, long-term strategic consideration.
• 10:08
  Speaker 1: Integration complexity in action.
• 10:10
  Speaker 1: Okay, let's hit our final cluster.
• 10:12
  Speaker 1: digital care delivery strategy and the ecosystem because all these breakthroughs need a way to scale and that means solving access and delivery.
• 10:20
  Speaker 0: Absolutely.
• 10:21
  Speaker 0: Sima Verma talking about Oracle's commitment detailed a plan to use AI and even lower earth orbit satellites to revolutionize rural health care in the US.
• 10:29
  Speaker 1: A direct technological response to provider shortages and hospital closures.
• 10:34
  Speaker 0: But scaling digital health also requires excellence in the back office.
• 10:38
  Speaker 0: It's not all about the clinical evidence.
• 10:41
  Speaker 0: Josefa Dahud showed this perfectly with PhysiTrack, a digital rehab platform.
• 10:46
  Speaker 1: They used NetSuite to manage their finances across five different countries.
• 10:50
  Speaker 0: Right.
• 10:51
  Speaker 0: It proves that streamlined operations and automation are just as vital to success as the core technology itself.
• 10:57
  Speaker 1: That efficiency is what enables those big reimbursement milestones, too.
• 11:01
  Speaker 1: Martin Kirchberger shared some great news from Switzerland.
• 11:04
  Speaker 1: A
• 11:04
  Speaker 0: huge policy step.
• 11:05
  Speaker 1: Yeah, their health authorities have cleared the way for mandatory insurance reimbursement for digital health apps, they call them DGA, for cognitive behavioral therapy, starting in July, twenty twenty six.
• 11:16
  Speaker 0: That's the key to unlocking scale for digital therapeutics in Europe.
• 11:20
  Speaker 0: But that scale requires data to flow freely.
• 11:23
  Speaker 0: We're seeing progress with things like the Lumio RHIS and the Azores Digital Health Project, which Thomas Shabetzberger highlighted.
• 11:29
  Speaker 0: Building
• 11:30
  Speaker 1: those bridges for deity exchange between organizations.
• 11:33
  Speaker 0: But even with a great EMR, you still hear about end user burnout.
• 11:37
  Speaker 1: All the time.
• 11:37
  Speaker 0: Vivek Arora explained why.
• 11:40
  Speaker 0: EMR success depends on collaboration between four teams.
• 11:43
  Speaker 0: Implementation, application management, infrastructure, and client operations.
• 11:48
  Speaker 0: If they don't work together, the end users, the doctors, and nurses feel unsupported.
• 11:53
  Speaker 0: It's an operational failure, not a tech failure.
• 11:55
  Speaker 1: And finally, there's a profound moral and financial case to be made here.
• 12:00
  Speaker 1: Lisa Gurry brought up the urgent need for genomic newborn screening.
• 12:04
  Speaker 0: This really ties it all together.
• 12:06
  Speaker 0: We have the science right now to diagnose rare diseases at birth instead of making families wait five years for symptoms to show up.
• 12:13
  Speaker 0: And the cost of not doing it is staggering and estimated one trillion dollars a year in the U.S.
• 12:19
  Speaker 0: alone.
• 12:20
  Speaker 1: A trillion dollars.
• 12:21
  Speaker 1: It makes early data driven intervention not just a moral obligation but a clear financial imperative.
• 12:27
  Speaker 0: So when you synthesize all this AI driving strategy, resilient imaging, solving real-world problems, robotics getting more accessible, and digital platforms focusing on operational efficiency, the big picture is one of deep integration.
• 12:39
  Speaker 1: It's moving beyond just isolated devices.
• 12:41
  Speaker 0: Exactly.
• 12:42
  Speaker 0: We're seeing massive collaborations like Mayo Clinic and GE Healthcare, and new workflow.
• 12:47
  Speaker 0: AI startups, as Blake Tindall noted, are acting as the glue to connect devices, diagnostics, and care.
• 12:53
  Speaker 0: And
• 12:54
  Speaker 1: that structural shift is driving the big macro trend, Mark Sluigas pointed out, the transition from disease care to well care.
• 13:00
  Speaker 1: This shift, with an estimated eight hundred and fifty billion dollar annual market, means everyone has to start integrating prevention and longevity into their core strategy.
• 13:08
  Speaker 0: Indeed.
• 13:09
  Speaker 0: If all these technologies are successful, the whole industry's purpose changes from just reacting to sickness to proactively maximizing well-being.
• 13:17
  Speaker 1: Which brings us to our final provocative thought for you to consider.
• 13:21
  Speaker 1: If the future of health tech is truly pivoting toward maximizing wellness and optimizing prevention, what does your product roadmap look like?
• 13:29
  Speaker 1: Is data-driven prevention baked in from the start, or is it still just an afterthought?
• 13:34
  Speaker 1: If you enjoyed this deep dive, new episodes drop every two weeks.
• 13:37
  Speaker 1: Also, check out our other editions on ICT and tech insights, defense tech, cloud, digital products and services, artificial intelligence, and sustainability, and green ICT.
• 13:46
  Speaker 1: Thank you for joining us for this analysis of the HealthTech landscape and make sure you subscribe so you don't miss the next one.