Latest / Best of LinkedIn: Digital Transformation & Tech / Best of LinkedIn: Health Tech CW 06/ 07

Transcript

Best of LinkedIn: Health Tech CW 06/ 07 · Best of LinkedIn: Digital Transformation & Tech

• 0:00
  Speaker 0: This episode is provided by Thomas Allgeier and Franis, based on the most relevant LinkedIn posts on health tech in CW six-and-seven.
• 0:08
  Speaker 0: Franus equips product and strategy teams with market and competitive intelligence to navigate the HealthTech landscape.
• 0:15
  Speaker 1: Welcome back to The Deep Dive!
• 0:16
  Speaker 1: We are looking at the Health Tech Landscape for Weeks Six & Seven of twenty-twenty-six
• 0:22
  Speaker 0: And I have say going through sources this time...the feeling was Different
• 0:26
  Speaker 1: different how
• 0:27
  Speaker 0: well.
• 0:28
  Speaker 0: usually there's a lot of you know science fiction Cool concepts that are maybe five ten years out right
• 0:34
  Speaker 1: the flying cars of health care
• 0:35
  Speaker 0: exactly, but this week It didn't feel like a science fair.
• 0:39
  Speaker 0: If felt more like a construction site
• 0:42
  Speaker 1: That's a perfect way to put it.
• 0:43
  Speaker 1: if there's one big takeaway is this The industry is moving from experimentation to scale the execution.
• 0:49
  Speaker 0: The sandbox phase is over?
• 0:50
  Speaker 1: It is!
• 0:51
  Speaker 1: We're not just seeing cool pilots, we are seeing regulatory-grade platforms actual reimbursement industrial maturity...the plumbing has been laid down
• 0:59
  Speaker 0: And that's what were here to unpack..we've grouped updates into well four big themes.
• 1:03
  Speaker 1: Were gonna talk about AI becoming agintic which was a term we definitely need to define.
• 1:08
  Speaker 0: Then will get in some uh literal superpowers and imaging diagnostics
• 1:13
  Speaker 1: New wave robotics.
• 1:14
  Speaker 1: then Big one The money question Digital therapeutics actually getting paid.
• 1:20
  Speaker 0: It's a packed agenda, so let's get right into it.
• 1:22
  Speaker 0: Let's
• 1:22
  Speaker 1: start with AI.
• 1:23
  Speaker 1: I mean we say AI is changing health care all the time.
• 1:26
  Speaker 1: That's almost a cliche
• 1:28
  Speaker 0: but opposed from Effie glow reporting from WA checks in Dubai She used to phrase that really stuck with me
• 1:35
  Speaker 1: was at.
• 1:35
  Speaker 0: she said AI is graduating from a chatbot to a co-worker.
• 1:39
  Speaker 1: And that is the critical shift, she was talking about agentic AI.
• 1:42
  Speaker 0: right and for anyone listening this is a real leap forward from the generative AI we've all gotten used.
• 1:48
  Speaker 1: so it's not just chat gpt for doctors.
• 1:50
  Speaker 1: no
• 1:50
  Speaker 0: i mean generative ai is passive.
• 1:52
  Speaker 0: you ask a question it gives you an answer?
• 1:54
  Speaker 0: It waits!
• 1:55
  Speaker 0: Agenic Ai has agency its designed to execute tasks
• 2:00
  Speaker 1: autonomously.
• 2:01
  Speaker 1: So does it summarize meeting notes
• 2:03
  Speaker 0: It schedules the follow-up, it updates the patient file.
• 2:06
  Speaker 0: It flags a prescription conflict all without you holding its
• 2:10
  Speaker 0: hand.".
• 2:11
  Speaker 1: And she gave that example from the UAE Ministry of Health.
• 2:14
  Speaker 1: they have projects where AI agents are handling what was it?
• 2:18
  Speaker 1: A third of the admin burden...
• 2:19
  Speaker 0: ...a third and think about what that really means.
• 2:21
  Speaker 0: this isn't a doctor checking the AI's work every few seconds.
• 2:25
  Speaker 1: No!
• 2:25
  Speaker 1: This is AI doing triage AI doing scheduling, its
• 2:29
  Speaker 0: infrastructure.
• 2:30
  Speaker 1: and Effie's point about geography was interesting too.
• 2:32
  Speaker 1: The health care lab for this.
• 2:35
  Speaker 1: It's not Silicon Valley anymore
• 2:37
  Speaker 0: No it's the GCC the Gulf region in China.
• 2:39
  Speaker 0: They're just operationalizing this tech so much faster
• 2:42
  Speaker 1: which is a huge wake-up call.
• 2:43
  Speaker 1: I mean if you're only building for Western regulatory speeds You might be building for yesterday
• 2:48
  Speaker 0: And speaking of the UAE Said Al Hasan shared an update on Amal the
• 2:52
  Speaker 1: first AI physician assistant.
• 2:54
  Speaker 0: right And the language they use is key.
• 2:57
  Speaker 0: It's to augment decision-making,
• 2:59
  Speaker 1: Augment not replace
• 3:01
  Speaker 0: exactly.
• 3:01
  Speaker 0: it reduces the cognitive load But yeah and there's always a but when you move this fast
• 3:06
  Speaker 1: There are new risks
• 3:07
  Speaker 0: and This Is where we need To look at what's happening in Italy?
• 3:10
  Speaker 0: Chiara Galiz had A really sharp analysis on this.
• 3:13
  Speaker 0: On
• 3:13
  Speaker 1: The MIA system right correct?
• 3:15
  Speaker 0: so Italy deployed this generative AI tool mia into fifteen hundred family doctors offices.
• 3:22
  Speaker 1: Wow That is national scale.
• 3:23
  Speaker 0: It is and it uses something called RAG, Retrieval Augmented Generation.
• 3:28
  Speaker 1: Okay break that down for us.
• 3:30
  Speaker 1: what does that mean here?
• 3:31
  Speaker 1: So
• 3:31
  Speaker 0: instead of the AI just you know making things up from the internet, ROGI forces to look at a specific trusted library first
• 3:38
  Speaker 1: Medical guidelines in this case Right!
• 3:40
  Speaker 0: It retrieves correct data then generates answer
• 3:44
  Speaker 1: Which sounds much safer
• 3:46
  Speaker 0: It is, in theory.
• 3:47
  Speaker 0: But Chiara points out this very human problem... automation bias!
• 3:51
  Speaker 1: We trust the machine too much…
• 3:53
  Speaker 0: We do!
• 3:54
  Speaker 0: These systems sound so confident—perfect grammar.
• 3:57
  Speaker 0: A busy doctor asks for a diagnostic frame The AI gives a coherent answer And
• 4:02
  Speaker 1: the Doctor just accepts it.
• 4:03
  Speaker 0: and the AI becomes shadow co-author of that medical decision.
• 4:06
  Speaker 1: That's the scary part.
• 4:08
  Speaker 1: If the AI misses a nuance Who's responsible?
• 4:11
  Speaker 1: The doctor signed off but the shadow co author wrote
• 4:14
  Speaker 0: Confidence is not competence.
• 4:17
  Speaker 0: And that's why Tim Ruchenbaum's update from Oracle was so relevant,
• 4:20
  Speaker 1: he was talking about their new AI data platform?
• 4:23
  Speaker 0: Yes and his point was at this.
• 4:25
  Speaker 0: agentic intelligence needs deep clean clinical data.
• 4:29
  Speaker 0: you can't just slap a smart bot on top of a messy system.
• 4:33
  Speaker 0: it's
• 4:33
  Speaker 1: an infrastructure play Not Just An App.
• 4:35
  Speaker 1: You Download
• 4:36
  Speaker 0: It The Plumbing Of The Hospital.
• 4:38
  Speaker 1: Okay.
• 4:38
  Speaker 1: So That'S the Back End.
• 4:39
  Speaker 1: Let's Shift To The Front End The Eyes Of The Operation imaging and diagnostics.
• 4:44
  Speaker 0: And looking at the posts from Ryan Fukushima, Dr Daniel Stromer it really does feel like we're getting superpowers!
• 4:50
  Speaker 1: Let's start with Ryan's insight on page.
• 4:52
  Speaker 1: predict he used an analogy that just...it clicks
• 4:55
  Speaker 0: A compressed file.
• 4:56
  Speaker 1: Yes so think of a standard pathology slide The pink-and-purple tissue sample for cancer diagnosis.
• 5:01
  Speaker 1: Think if is as a compressed file.
• 5:02
  Speaker 0: For one hundred years pathologists have looked at this slide seeing cell shapes Morphology.
• 5:07
  Speaker 1: but the AI sees more.
• 5:09
  Speaker 0: So much more!
• 5:10
  Speaker 0: It looks at that same slide and see's molecular data, it decompresses the file.
• 5:14
  Speaker 1: He said AI can now predict a hundred twenty-three biomarkers across sixteen cancer types
• 5:20
  Speaker 0: From a single slide.
• 5:21
  Speaker 0: That
• 5:21
  Speaker 1: is just wild.
• 5:23
  Speaker 1: Usually you'd need what?
• 5:23
  Speaker 1: Expensive genetic sequencing for that
• 5:25
  Speaker 0: Exactly More tissue, more time A lot more money.
• 5:29
  Speaker 0: This means You could get that same date Adjust by running code on an image you already have.
• 5:33
  Speaker 1: It democratizes precision oncology.
• 5:36
  Speaker 0: But speed is also a superpower, especially in the ER.
• 5:39
  Speaker 0: And that brings us to The Photon Friday Case.
• 5:42
  Speaker 1: Cheered by Dr.
• 5:43
  Speaker 1: Daniel Strowmer This one really hits home.
• 5:45
  Speaker 1: Chest pain, racing heart, emergency room... The
• 5:48
  Speaker 0: triple rule out!
• 5:50
  Speaker 0: This has huge leap into CT tech Usually scanning hearts beating fast as well.
• 5:55
  Speaker 0: It's a nightmare.
• 5:56
  Speaker 1: The image gets blurry Right…the
• 5:58
  Speaker 0: scanner like camera.
• 6:00
  Speaker 0: If the heart is moving fast, the picture's useless.
• 6:02
  Speaker 1: But Dr.
• 6:03
  Speaker 1: Schromer was talking about the semen's naeotom alpha dot prime of photon counting CT Right
• 6:08
  Speaker 0: and without getting too deep into physics.
• 6:11
  Speaker 0: these detectors are incredibly fast.
• 6:12
  Speaker 0: They count individual photons so they can freeze motion
• 6:15
  Speaker 1: And results.
• 6:16
  Speaker 1: in this case
• 6:17
  Speaker 0: One scan one breath hold and diagnosed.
• 6:19
  Speaker 0: pulmonary embolism aortic dissection coronary artery disease
• 6:23
  Speaker 1: Three deadly conditions at once.
• 6:25
  Speaker 0: That difference between innovation and execution.
• 6:28
  Speaker 0: Execution We saved this person's life in five minutes and the ER.
• 6:32
  Speaker 1: Incredible, but the tech is only half of battle.
• 6:35
  Speaker 1: Andrei Hartung added another layer to it
• 6:37
  Speaker 0: The unified cockpit.
• 6:38
  Speaker 1: This about human factor.
• 6:40
  Speaker 1: we're drowning radiologists data.
• 6:42
  Speaker 0: Right.
• 6:43
  Speaker 0: if you give them better images with a harder workflow they burn out.
• 6:46
  Speaker 0: Andre was talking how AI needs reduce scan times put all that data into one clean view
• 6:52
  Speaker 1: Producing cognitive load
• 6:53
  Speaker 0: Just as important image resolution.
• 6:56
  Speaker 0: And Mark Stoffels from Phillips mentioned their acquisition of Spectrowave, which is about combining imaging and AI inside the veins.
• 7:04
  Speaker 1: So you can decide guide-and-treat all in one.
• 7:06
  Speaker 1: go closing The Loop?
• 7:08
  Speaker 0: Exactly!
• 7:09
  Speaker 0: Okay so speaking of closing A Loop let's talk about robotics when the code meets the physical
• 7:14
  Speaker 1: world.
• 7:15
  Speaker 1: We have to start with this story shared by Dr Martha Buchenfeld About a man named Tucker
• 7:20
  Speaker 0: Moore.
• 7:20
  Speaker 0: Such a powerful story.
• 7:21
  Speaker 0: it grounds All This Tech In Reality.
• 7:24
  Speaker 1: So Tucker's a marathon runner.
• 7:25
  Speaker 1: He has a freak accident, falls downstairs loses a hand-prit sized piece of his skull
• 7:30
  Speaker 0: and suddenly His life is on hold wearing a helmet everywhere.
• 7:34
  Speaker 1: And the standard solution?
• 7:35
  Speaker 1: A custom titanium implant costs what twenty thousand dollars or
• 7:39
  Speaker 0: more.
• 7:39
  Speaker 0: for a lot Of people that's just out of reach.
• 7:41
  Speaker 1: but dr.
• 7:42
  Speaker 1: Bokenfeld highlighted The shift to three d printing.
• 7:45
  Speaker 1: they used a peak implant.
• 7:47
  Speaker 0: peak Is a high performance polymer.
• 7:49
  Speaker 0: it's biocompatible.
• 7:51
  Speaker 0: its light.
• 7:52
  Speaker 0: This is the crucial part.
• 7:53
  Speaker 0: It can be three d printed very cheaply.
• 7:55
  Speaker 1: how cheaply
• 7:56
  Speaker 0: she said.
• 7:56
  Speaker 0: in some pilots They're doing it for as low as six hundred dollars
• 7:59
  Speaker 1: from twenty thousand to six hundred.
• 8:01
  Speaker 0: that Is democratization and The end of the story.
• 8:05
  Speaker 0: Tucker ran the nyc marathon just months later.
• 8:08
  Speaker 0: That's
• 8:08
  Speaker 1: what scaled execution looks like,
• 8:11
  Speaker 0: but the big players are moving here too.
• 8:13
  Speaker 0: we saw updates From Medtronic Raji Kamal on the Hugo system, Jeff Martha on Stealth XIS.
• 8:20
  Speaker 1: And the trend there seems to be ecosystem?
• 8:22
  Speaker 0: It is!
• 8:23
  Speaker 0: Medtronic isn't just selling a robot arm — they're unifying planning navigation and robotics into one workflow...
• 8:29
  Speaker 1: ...and real-time data's coming in that work flow now too….
• 8:32
  Speaker 1: Yes
• 8:33
  Speaker 0: Alice Warden from GE Health Cow posted about integrating their ultrasound directly into robotic surgery
• 8:39
  Speaker 1: Which is huge because the surgeon is at a console ten feet away.
• 8:42
  Speaker 1: They lose that sense of touch.
• 8:44
  Speaker 0: They're flying by vision alone, but adding ultrasound lets you see inside the organ before you cut.
• 8:49
  Speaker 0: it's like having x-ray vision during operation
• 8:52
  Speaker 1: and looking ahead.
• 8:53
  Speaker 1: bird van mirrors from Phillips mentioned this seismic consortium.
• 8:56
  Speaker 0: over twenty three million euros in EU funding.
• 8:59
  Speaker 0: This is focused on the brain on minimally invasive treatments.
• 9:03
  Speaker 0: It's the final frontier for this kind of tech.
• 9:05
  Speaker 1: Okay so we have smart agents with supervision We have robots But none if matters If no one pays.
• 9:11
  Speaker 0: which brings us to theme four, digital therapeutics and virtual care.
• 9:15
  Speaker 0: And we have a major reimbursement milestone.
• 9:19
  Speaker 1: Lucy Jones shared the news about OvevaDirect in Germany.
• 9:22
  Speaker 0: This is huge, it's Germany first reimbursed.
• 9:25
  Speaker 0: digital therapy a digae for both hypertension and weight management
• 9:29
  Speaker 1: Reimbursed that's the magic word
• 9:31
  Speaker 0: It is.
• 9:31
  Speaker 0: there are thousands of wellness apps but oveva showed the data an eleven millimeter hg drop in systolic blood pressure over four percent weight loss.
• 9:40
  Speaker 1: So because they have hard clinical data The German health system says okay we'll pay for this like a pill.
• 9:45
  Speaker 0: Exactly, but the regulation around this is tricky.
• 9:48
  Speaker 0: Asincon analyzed the FDA's twenty-twenty six guidance and it looks like they're opening a side door
• 9:54
  Speaker 1: for general wellness devices.
• 9:56
  Speaker 0: right your smartwatches your rings Devices that measure BP's PO to glucose.
• 10:01
  Speaker 1: So what does the shift?
• 10:02
  Speaker 0: The FDA saying if you stay in that wellness lane And you don't claim to diagnose or treat a disease You can bypass the strict five-ten K clearance.
• 10:12
  Speaker 1: So faster market access for manufacturers?
• 10:14
  Speaker 0: Much faster, but they have to be so careful with marketing if they cross the line into diagnosis there in big trouble and
• 10:20
  Speaker 1: when you combine that with gamification.
• 10:22
  Speaker 1: what Mengcha shared about loony health in Singapore is fascinating.
• 10:27
  Speaker 0: my favorite example of prevention as infrastructure a partnership between Apple and the Singaporean government
• 10:32
  Speaker 1: And this wasn't a small pilot
• 10:33
  Speaker 0: no.
• 10:37
  Speaker 0: and by gamifying, health-closing your rings or any points they saw sustained activity gains.
• 10:42
  Speaker 1: Gains that could actually reduce mortality risk
• 10:44
  Speaker 0: By three to thirteen percent.
• 10:45
  Speaker 0: it proves.
• 10:46
  Speaker 0: if you design the incentives right at a national scale You can change the health profile of country
• 10:51
  Speaker 1: And its not just general wellness.
• 10:54
  Speaker 1: Sina Esimiri reported on dental monitoring securing a hundred million dollars for
• 10:59
  Speaker 0: remote orthodontic care.
• 11:00
  Speaker 0: It just proves the model works.
• 11:01
  Speaker 0: You don't need to go to the dentist every two weeks if an AI can check your selfie video.
• 11:05
  Speaker 0: Okay,
• 11:05
  Speaker 1: so let's zoom out.
• 11:06
  Speaker 1: we have the tech We have the scanners we even have some reimbursement
• 11:10
  Speaker 0: but you have to play Dell's advocate.
• 11:12
  Speaker 1: I do.
• 11:13
  Speaker 1: If this stuff is so good Why isn't it everywhere?
• 11:16
  Speaker 1: why am i still faxing things to my doctor?
• 11:19
  Speaker 0: That's the multi-billion dollar question.
• 11:22
  Speaker 0: And it brings us to our final theme, strategy and the.
• 11:25
  Speaker 0: so what?
• 11:26
  Speaker 1: Vladislav Puzhankov had a brilliant take on this.
• 11:29
  Speaker 1: Demand fulfillment versus demand creation.
• 11:33
  Speaker 0: Every health tech founder needs to hear this.
• 11:35
  Speaker 0: he argues that innovation fails if you just try to fulfill demand like answering a hospital's RFP
• 11:40
  Speaker 1: because The Hospital Just asked for A faster horse slightly better version of What they already have.
• 11:45
  Speaker 0: precisely Puzonkov used intuitive surgical as an example.
• 11:49
  Speaker 0: They didn't sell a robot, they created the category of robotic surgery.
• 11:52
  Speaker 1: They had to build the demand from zero.
• 11:54
  Speaker 0: If they'd waited for a tender or surgical robot then you would be gone.
• 11:58
  Speaker 0: You have teach them why it needs your solution.
• 12:01
  Speaker 1: But even when that demand is there Adoption is still uneven.
• 12:05
  Speaker 1: That report Jan Beger shared on US hospitals was... A bit of reality check.
• 12:10
  Speaker 0: It was only forty.
• 12:12
  Speaker 0: nine percent use predictive AI Less than half.
• 12:16
  Speaker 1: And it's clustered in wealthy urban areas with cold spots, in rural areas.
• 12:20
  Speaker 0: So the places that need efficiency most are least likely to have it.
• 12:23
  Speaker 0: The infrastructure gap is real
• 12:25
  Speaker 1: Which brings us a final point from Simon Philip Ross at GE Healthcare.
• 12:30
  Speaker 1: He basically said... No!
• 12:34
  Speaker 0: The barrier is status quo.
• 12:36
  Speaker 0: It's our willingness to redesign how we partner and govern these systems.
• 12:40
  Speaker 1: We had to stop running Pylis
• 12:41
  Speaker 0: ...and start redesigning this system.
• 12:43
  Speaker 0: The tech is ready, the question is are we ready to change how we work?
• 12:46
  Speaker 0: To fit the technology.
• 12:48
  Speaker 1: That's a challenge isn't it?
• 12:49
  Speaker 1: moving from the wow phase...to the How Phase and the How Is Messy!
• 12:53
  Speaker 0: It is but as we saw with the three-D printed skull or the triple rule out scan when We get the HOW RIGHT THE IMPACT IS IT'S IMMEDIATE IT'S PROFOUND
• 13:02
  Speaker 1: absolutely.
• 13:03
  Speaker 1: the hard Work of Execution is just beginning.
• 13:05
  Speaker 0: indeed if you
• 13:06
  Speaker 1: enjoyed this episode new episodes drop every two weeks.
• 13:10
  Speaker 1: Also, check out our other editions on ICT and Tech Insights.
• 13:12
  Speaker 1: DefenseTech Cloud Digital Products & Services Artificial Intelligence And Sustainability in Green ICT.
• 13:20
  Speaker 0: Thanks for listening!
• 13:21
  Speaker 0: Don't forget to subscribe so you don't miss the next deep dive.
• 13:24
  Speaker 1: See ya next time.