Best of LinkedIn: Health Tech CW 48/ 49

00:00:00: 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.

00:00:09: Frannis equips product and strategy teams with market and competitive intelligence to navigate the health tech landscape.

00:00:15: Welcome back.

00:00:16: 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.

00:00:25: And the signal we're picking up is, well, it's pretty clear.

00:00:29: It is.

00:00:30: The industry is past the point of just casual experimentation.

00:00:33: Right.

00:00:33: It's not about pilots anymore.

00:00:35: Exactly.

00:00:35: I mean, if you had to boil it all down, the real story is this shift from pilots to actual operational rollout.

00:00:42: The focus isn't just on what a technology can do in a lab.

00:00:45: It's about how it works in the real

00:00:46: world.

00:00:47: Yeah.

00:00:47: How it integrates into a clinical workflow, how it connects to the data, and maybe most importantly, how you get paid for it.

00:00:52: It has to be payment ready.

00:00:54: So that financial and clinical loop is finally tightening.

00:00:57: Tech is being judged on its ability to scale, not just its novelty.

00:01:01: Precisely.

00:01:02: And to make sense of all this, we've grouped the insights into four main clusters.

00:01:07: First, how AI strategy is maturing.

00:01:10: Second, the massive shifts in diagnostics and imaging, especially with everything coming out of the RSNA conference.

00:01:16: Okay.

00:01:16: Third is the expansion of robotic surgery.

00:01:19: And finally, the big strategic moves in digital care delivery and, you know, the whole ecosystem that ties it all together.

00:01:26: Okay, let's unpack this.

00:01:27: And I think we have to start with the biggest driver of change, right?

00:01:31: Artificial intelligence.

00:01:32: We've talked about pilots for years, but what does this new strategic phase actually look like?

00:01:38: It looks like architecture.

00:01:40: I mean, Bill Russell made a great point that too many health systems have something like forty AI tools and no architecture.

00:01:45: That's not a strategy.

00:01:47: That's just a shopping

00:01:47: habit.

00:01:48: It's a shopping habit that creates a ton of integration debt.

00:01:51: He says the new leaders are becoming Renaissance architects.

00:01:54: Renaissance

00:01:55: architect.

00:01:55: I like that.

00:01:56: But what does it really mean?

00:01:57: Is that just a fancy new name for a CIO?

00:01:59: Well,

00:01:59: not quite.

00:02:00: The Renaissance part implies a total rethink of the foundation.

00:02:05: A CIO manages IT.

00:02:07: A Renaissance architect is building the blueprint for clinical transformation.

00:02:12: They're not just buying another point solution.

00:02:14: They're designing the whole system from the ground up to connect all the data and anticipate how the workflow is going to change.

00:02:21: Exactly.

00:02:22: and to prepare for those complex reimbursement pathways we just mentioned.

00:02:26: That makes perfect sense because without that architecture you lose all the efficiencies everyone is so excited about.

00:02:32: Sameer Saleem pointed out that professionals are, you know, thrilled about AI enhancing outcomes and reducing costs.

00:02:37: But excitement doesn't fix a broken operational structure.

00:02:40: No, it doesn't.

00:02:42: And that structure, it absolutely has to be clinician led.

00:02:46: Christa Calpe highlighted the AMA's launch of the Center for Digital Health and AI.

00:02:51: It's a bit of a defensive move, but it's necessary.

00:02:53: To make sure physicians are shaping the policy up front, not just dealing with the messy aftermath of a new tool.

00:02:59: Right.

00:02:59: You need it to fit the workflow seamlessly from day one.

00:03:02: And a huge signal of market maturity is when the regulators finally step up.

00:03:07: We saw that in the U.S.

00:03:08: with the proposed Health Tech Investment Act, which Christian Usman and John Cole mentioned.

00:03:14: It's designed to improve Medicare reimbursement for validated AI software.

00:03:18: Payment friction is the ultimate killer of scale.

00:03:21: So tackling that unlocks everything.

00:03:24: And while the U.S.

00:03:24: system is playing catch up on payment, consumers are already way ahead.

00:03:28: A survey in Germany from Privgo's Dr.

00:03:31: Michael Quinton showed that twenty-five percent of citizens are already using AI tools.

00:03:36: Twenty-five percent?

00:03:37: Wow.

00:03:37: Yeah.

00:03:38: Things like symptom checkers for health questions.

00:03:40: That's a huge uptake.

00:03:41: Which puts immediate pressure on ethics and governance, I'd imagine.

00:03:44: It does.

00:03:45: And a systematic review from Jan Beger found a really critical gap here.

00:03:49: Hospital-based AI research talks a lot about ethics, but it almost never operationalizes those principles.

00:03:55: What do you mean by that?

00:03:56: Well, most worryingly, only six percent of the studies he looked at even addressed sustainability or the environmental costs of training these huge models.

00:04:03: Wow, so they're completely ignoring the data's carbon footprint.

00:04:06: Exactly.

00:04:07: And when you ignore these things, you get resistance.

00:04:10: Sigrid Bergen and Assim Khan really reinforced this.

00:04:13: They said AI strategy fails without early, inclusive co-creation.

00:04:18: So bring everyone to the table from day one.

00:04:21: Or else clinicians show a fight-or-flight response.

00:04:24: which leads to the low adoption we see all the time.

00:04:27: And while hospitals are sorting out governance, Big Pharma is just sprinting ahead on R&D.

00:04:32: Wolfgang Schleifer highlighted NVIDIA's partnerships with companies like Eli Lilly.

00:04:37: Oh yeah, they're building a full-on AI factory to train models.

00:04:40: It's not just a tool for them anymore.

00:04:41: It's a complete transformation of their R&D pipeline to, you know, drastically cut drug discovery timelines.

00:04:48: Let's pivot now to that second cluster, diagnostics, imaging, and radiology.

00:04:53: The recent RSNA conference proved that imaging is probably the fastest runway for scalable AI adoption right now.

00:05:00: And it's not just about image quality, is it?

00:05:01: It's about resilience.

00:05:02: Resilience,

00:05:03: yes.

00:05:04: And that starts with solving a massive geopolitical and supply chain headache.

00:05:08: Healing.

00:05:08: Healing.

00:05:09: Rakesh Kumar and others, we're all talking about Phillips unveiling of the three Tesla Blue Seal MRI.

00:05:15: It's a near zero helium system.

00:05:17: Near zero.

00:05:17: Okay.

00:05:18: Why is that specific detail such a huge breakthrough?

00:05:21: because a typical MRI scanner needs about fifteen hundred liters of liquid helium to stay cool.

00:05:28: And helium is scarce, it's non-renewable, and the supply chain is incredibly volatile.

00:05:33: So if your helium runs out, your multi-million dollar scanner is basically a paperweight for weeks.

00:05:38: Or months, yeah.

00:05:39: Removing that dependence just fundamentally changes the entire operational life cycle for an MRI system.

00:05:45: It means more uptime, lower cost, and one less massive headache for the hospital.

00:05:49: That's a fantastic example of hardware and material science solving a core operational problem.

00:05:54: And beyond the hardware, AI is improving the images themselves.

00:05:58: Precisely.

00:05:59: Killian Salty noted how deep learning reconstruction, specifically ARREC and DL, is dramatically improving the quality of arterial pancreas MRIs.

00:06:07: You get sharper images, better lesion detection.

00:06:09: All

00:06:10: while keeping the patient's breath hold really short.

00:06:12: Around twenty-two seconds.

00:06:13: Okay.

00:06:13: Which is great for patient throughput and of course clinical confidence.

00:06:16: So if AI is handling more of the processing and analysis, the radiologist's role has to be changing pretty profoundly.

00:06:23: It is.

00:06:23: Matthias Goyen put it very clearly.

00:06:25: The future is human-led collaboration with AI.

00:06:29: Radiologists are shifting from just being image readers to becoming orchestrators.

00:06:33: Turning all that data into actual wisdom.

00:06:35: Exactly.

00:06:36: And you see that backed up by tools like GE Healthcare's Imaging Three Sixty, which Simon Philip Ross detailed.

00:06:43: It uses AI to automate analysis and optimize things like scheduling and device use.

00:06:47: And here's where it gets really interesting.

00:06:49: Connecting this back to that macro trend of longevity and early detection, especially in cardiology.

00:06:54: Right.

00:06:54: Longevity demands you shift the diagnostic timeline way earlier.

00:06:59: Kirk Sanford detailed a non-invasive tool called CADScore.

00:07:02: It uses acoustic AI to listen for subtle turbulence in blood flow.

00:07:06: To detect plaque buildup without any radiation.

00:07:09: And it delivers over ninety-six percent diagnostic certainty.

00:07:12: That kind of certainty from a non-invasive tool is a profound game changer for preventative medicine.

00:07:18: And the validation is accelerating.

00:07:21: Campbell Rogers confirmed that heart flow plaque analysis is now the most clinically validated framework for CAD risk stratification.

00:07:28: Dr.

00:07:29: Emery Urturk even predicted that by twenty thirty, AI-enhanced multimodal imaging combining ECHO, CMR, and CT will probably be the new diagnostic standard.

00:07:38: It's all about that AI-driven convergence.

00:07:41: Let's move into the operating theater now.

00:07:43: And that third cluster of robotic surgery and interventional tech.

00:07:46: If we can see better with AI, the goal is now to make the intervention less invasive and crucially more accessible.

00:07:53: That accessibility part is key, isn't it?

00:07:55: It is.

00:07:56: Ilani Dalinon highlighted CMR surgicals versus system.

00:07:59: It's modular, it's miniaturized, a truly digital native robot.

00:08:04: The whole design is about lowering the typical barriers to entry for minimally invasive surgery.

00:08:08: Like the huge cost.

00:08:10: the space it takes up and the steep learning curve of older systems.

00:08:13: Exactly.

00:08:14: This is what helps push adoption globally.

00:08:16: Meanwhile, the big established players are expanding into new clinical areas.

00:08:19: Medtronic's Hugo-RES system is a perfect example.

00:08:23: It just got FDA clearance for urologic procedures, showing real precision and prostatectomy.

00:08:29: Bob Reddy and Dr.

00:08:30: James Porter emphasized that its modular arms improve flexibility and ergonomics for the surgeon.

00:08:36: And they can operate from an open workstation, which improves communication with the whole team.

00:08:40: A

00:08:41: huge deal for human factors in the OR.

00:08:43: And we're seeing robotics move outside the operating room entirely.

00:08:47: Petra Teglis shared news about a rice-sized, magnetically guided robot.

00:08:51: Tiny

00:08:52: little

00:08:52: bot.

00:08:53: Designed to break apart kidney stones without surgery.

00:08:56: It really points to a future of safer, less invasive, interventional platforms.

00:09:00: And speaking of blurring boundaries, Austin Chiang called up the artificial boundary between surgery and endoscopy.

00:09:07: He's advocating for more collaboration.

00:09:10: Because the turf war is just slowdown innovation and hurt patients.

00:09:14: He argues patients benefit most from convergence, like with endoluminal robotics.

00:09:19: But the medical training models just haven't kept up.

00:09:21: It

00:09:21: seems like a solvable problem, though.

00:09:23: It is.

00:09:24: Dr.

00:09:24: Quinlan D. Buchlak noted a similar kind of strategic complexity with TVI.

00:09:29: Post-TVI coronary access is becoming a critical issue.

00:09:32: Okay, hold on.

00:09:32: For those who don't follow cardiology that closely, can you quickly break down what TVI is and why access afterwards is a problem?

00:09:40: Sure.

00:09:40: TVI is transcatheter aortic valve implantation, a minimally invasive way to replace the aortic valve.

00:09:47: The issue Dr.

00:09:48: Booklack raised is that as the tech gets better, it's being used in younger, healthier patients.

00:09:53: So they'll live longer and need more procedures down the road.

00:09:55: Exactly.

00:09:56: If you get a Pavi-i in your sixties, you'll likely need future coronary work.

00:10:00: But that TBI valve can make it surgically much harder to access the coronary arteries later on.

00:10:05: It's a huge, long-term strategic consideration.

00:10:08: Integration complexity in action.

00:10:10: Okay, let's hit our final cluster.

00:10:12: digital care delivery strategy and the ecosystem because all these breakthroughs need a way to scale and that means solving access and delivery.

00:10:20: Absolutely.

00:10:21: 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.

00:10:29: A direct technological response to provider shortages and hospital closures.

00:10:34: But scaling digital health also requires excellence in the back office.

00:10:38: It's not all about the clinical evidence.

00:10:41: Josefa Dahud showed this perfectly with PhysiTrack, a digital rehab platform.

00:10:46: They used NetSuite to manage their finances across five different countries.

00:10:50: Right.

00:10:51: It proves that streamlined operations and automation are just as vital to success as the core technology itself.

00:10:57: That efficiency is what enables those big reimbursement milestones, too.

00:11:01: Martin Kirchberger shared some great news from Switzerland.

00:11:04: A

00:11:04: huge policy step.

00:11:05: 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.

00:11:16: That's the key to unlocking scale for digital therapeutics in Europe.

00:11:20: But that scale requires data to flow freely.

00:11:23: We're seeing progress with things like the Lumio RHIS and the Azores Digital Health Project, which Thomas Shabetzberger highlighted.

00:11:29: Building

00:11:30: those bridges for deity exchange between organizations.

00:11:33: But even with a great EMR, you still hear about end user burnout.

00:11:37: All the time.

00:11:37: Vivek Arora explained why.

00:11:40: EMR success depends on collaboration between four teams.

00:11:43: Implementation, application management, infrastructure, and client operations.

00:11:48: If they don't work together, the end users, the doctors, and nurses feel unsupported.

00:11:53: It's an operational failure, not a tech failure.

00:11:55: And finally, there's a profound moral and financial case to be made here.

00:12:00: Lisa Gurry brought up the urgent need for genomic newborn screening.

00:12:04: This really ties it all together.

00:12:06: We have the science right now to diagnose rare diseases at birth instead of making families wait five years for symptoms to show up.

00:12:13: And the cost of not doing it is staggering and estimated one trillion dollars a year in the U.S.

00:12:19: alone.

00:12:20: A trillion dollars.

00:12:21: It makes early data driven intervention not just a moral obligation but a clear financial imperative.

00:12:27: 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.

00:12:39: It's moving beyond just isolated devices.

00:12:41: Exactly.

00:12:42: We're seeing massive collaborations like Mayo Clinic and GE Healthcare, and new workflow.

00:12:47: AI startups, as Blake Tindall noted, are acting as the glue to connect devices, diagnostics, and care.

00:12:53: And

00:12:54: that structural shift is driving the big macro trend, Mark Sluigas pointed out, the transition from disease care to well care.

00:13:00: 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.

00:13:08: Indeed.

00:13:09: If all these technologies are successful, the whole industry's purpose changes from just reacting to sickness to proactively maximizing well-being.

00:13:17: Which brings us to our final provocative thought for you to consider.

00:13:21: If the future of health tech is truly pivoting toward maximizing wellness and optimizing prevention, what does your product roadmap look like?

00:13:29: Is data-driven prevention baked in from the start, or is it still just an afterthought?

00:13:34: If you enjoyed this deep dive, new episodes drop every two weeks.

00:13:37: 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.

00:13:46: 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.