Best of LinkedIn: DMEA 2026

00:00:00: This episode is provided by Thomas Allgeier and Frennis, based on the most relevant LinkedIn posts DMEA-twenty twenty six.

00:00:07: Frenis equips health tech providers with a market intelligence to identify which hospitals to target And how to reach decision makers for hospital digitalization as result of the cranking house succumb sex assets.

00:00:18: You can find more info in the description.

00:00:20: You know, in just the last twelve months over a hundred million documents were uploaded to The Electronic Patient Record here in Germany.

00:00:27: Wait!

00:00:27: A hundred million?

00:00:28: Yeah,

00:00:28: a hundred billion I mean after a decade of pilot programs and political debates And deep industry skepticism that damn has finally broken.

00:00:39: That is massive.

00:00:41: Honestly, if you're building or buying health tech today that single metric basically changes your entire roadmap.

00:00:48: Oh totally it forces a complete rethink.

00:00:49: exactly so the mission of this deep dive Today is to well really cut through The massive noise coming out of DMEA twenty-twenty six.

00:00:56: in Berlin.

00:00:57: We're taking these raw on-the-ground insights curated from LinkedIn posts by industry leaders and we are unpacking what this shift Really means.

00:01:04: right because the shift is huge.

00:01:06: It's moving from these grand theoretical visions too hard clinical execution.

00:01:12: Yeah, and the context here is super critical for you listening.

00:01:15: DMEA twenty-twenty six was completely sold out.

00:01:18: I mean nine hundred exhibitors over twenty thousand visitors.

00:01:21: It's still Europe's undisputed leading digital health event.

00:01:24: no question but reading the dispatches from The people actually navigating to floor?

00:01:30: The tone Was well.

00:01:31: it was vastly different From previous years.

00:01:33: how so like less hype

00:01:34: exactly?

00:01:35: the market Is demanding proof.

00:01:36: now Buyers are essentially looking vendors in the eye and saying show me how this algorithm survives a chaotic Tuesday morning shift at a busy clinic.

00:01:44: Right,

00:01:45: there is just zero patients left for The art of the possible.

00:01:48: And that demand for tangible execution brings us Street to the most dominant force at the event which is obviously AI?

00:01:55: Obviously but AI Is no longer Just a future promise.

00:01:58: That conversation is completely pivoted.

00:02:00: Yeah technical capability like the raw computational power Of the model actually matters less right now than frontline adoption you know, workflow integration and absolute trust from the clinical staff.

00:02:10: You really saw this maturation directly in The Solutions being showcased.

00:02:15: Dr.

00:02:16: Gottfried Ludwig posted about the Deutsche Telekom One Health team And his core observation was how tangible their solutions have become Tangible?

00:02:24: In what way?

00:02:25: Well they weren't just running simulations on neural networks On a screen right.

00:02:28: They were demonstrating highly functional systems for data driven hospitals Specifically clinical control centers and robust cybersecurity frameworks.

00:02:38: Oh, Clinical Control Centers!

00:02:39: Let's unpack the mechanics of that for a second because that illustrates this shift perfectly.

00:02:43: Yeah

00:02:44: go for it.

00:02:44: Historically managing hospital flow involved charge nurses Making dozens of phone calls, updating physical whiteboards and manually trying to figure out which beds were open while emergency admissions stacked up in the hallways.

00:02:57: Just a completely fragmented reactive process exactly.

00:03:01: but A modern clinical control center changes that architecture entirely.

00:03:06: It continuously ingests live data streams from across the whole hospital

00:03:10: like patient monitoring devices electronic health records staff scheduling software all about

00:03:15: Right, and bed management systems.

00:03:17: The AI sits on top of that unified data layer analyzing the flow in real time to predict bottlenecks before they even happen.

00:03:24: so it might flag that based on current ER triage data the ICU is going be over capacity in four hours.

00:03:32: yeah which allows administrators to proactively reroute resources.

00:03:37: And that level of tangible operational utility Is exactly why the federal minister of health made a point to visit their booth.

00:03:45: They're focusing on the exact pain points where hospitals desperately need reliable support right now.

00:03:51: The standard for AI in health care has officially evolved.

00:03:54: It really is.

00:03:55: For years it was like a shiny concept car rotating slowly at an auto show Right,

00:04:01: that's great way to put it Yeah

00:04:02: and looked incredible with doors open vertically And promised to run alternative energy or whatever.

00:04:07: But DMEA twenty-twenty six proved that AI left the concept car phase.

00:04:11: It's now being scrutinized as a daily commuter vehicle.

00:04:14: It

00:04:14: has to actually start in the morning?

00:04:15: Exactly, it has to start reliably every single morning...it has to fit clinicians' existing driving habits and it has get patient safely from point A-point B without catastrophic breakdown.

00:04:27: And build reliable commuter vehicles.

00:04:29: you need pristine manufacturing process.

00:04:32: Philip Thiele's update regarding the official launch of the CGM ARR brand highlighted exactly how companies are approaching this.

00:04:39: They're focusing heavily on establishing a sovereign real-world data foundation, right?

00:04:44: Yes!

00:04:44: Data sovereignty It is crucial concept here especially in European context.

00:04:49: it means ensuring that vast amounts sensitive health data required to train these AI models remain under strict localized control

00:04:57: instead being fed into opaque offshore cloud environments.

00:05:00: Exactly CGMRA is using that sovereign foundation to build transparent, trustworthy AI models focused on evidence-based healthcare.

00:05:09: Fabula Harteng-Lintz noted this focus was really echoed by M&M software and SQL as well.

00:05:14: What did they bring the table?

00:05:15: They

00:05:16: brought ten real world MedTech AI use cases for their booth And not theoretical pitches either.

00:05:23: actual deployable use case ranging from automated regulatory documentation to predictive maintenance.

00:05:31: Oh, Predictive Maintenance is a brilliant example of hidden ROI in health tech.

00:05:35: It really is!

00:05:36: I mean think about modern MRI machine.

00:05:38: it's essentially massive IoT device.

00:05:40: Right...it

00:05:41: generates continuous telemetry data regarding its own operating state vibrations temperature fluctuations power consumption

00:05:47: and instead waiting for critical component to just snap causing the machine go offline enforcing cancellation weeks worth vital patient scans.

00:05:57: The AI analyzes that telemetry.

00:05:59: It detects

00:06:00: the microscopic anomalies indicating a part is going to fail in three weeks, allowing technicians to replace it during a scheduled maintenance window

00:06:07: which saves hospitals tens of thousands of euros and lost operational time.

00:06:11: but you know... That commuter car analogy we used earlier reveals massive elephant-in-the-room A highly reliable AI driven commuter cars completely useless if there are no paved roads to drive on.

00:06:21: So true!

00:06:22: And In hospital ecosystem those roads Are data pipelines.

00:06:27: Right.

00:06:27: If the telemetry data from the MRI machine or live updates on bed capacity can't flow freely between different software environments, The AI is effectively stranded in the driveway.

00:06:38: Which is exactly why interoperability fundamentally took over the conversation at DMEA.

00:06:43: Yeah,

00:06:43: for a long time interoperable felt like this dry secondary policy issue Like a headache reserved exclusively For hospital IT department.

00:06:51: But consensus on floor was that Interoperability Is the absolute core condition for scaling any digital service.

00:06:58: Udo Lengen recapped the future health day, which kicked off the DMEA week and he highlighted a framing from Stefan Andriada of Cineja IT that perfectly captures this tension.

00:07:09: Oh I saw that quote.

00:07:09: it's brilliant.

00:07:10: Yeah Andriata said data doesn't want to be alone.

00:07:13: Data wants to be secure.

00:07:14: The industry is finally recognizing that isolated data silos are actively harming patient pair.

00:07:20: You need modern data infrastructures to see any measurable benefits in everyday clinical practice.

00:07:25: Right,

00:07:25: during a panel discussion at that same event Peter Koop pointed out the industry is facing a connectivity problem not technology problems.

00:07:33: We have computation power to analyze the data.

00:07:35: The hurdle of getting legacy on-premise lab system from two thousand five.

00:07:40: successfully talk with the modern cloud based diagnostic platform.

00:07:43: Marvin Abert of Remy Health provided painfully funny observation.

00:07:49: He dubbed the interfaces and development as The most German of all sentences.

00:07:54: Oh

00:07:54: man, if you work in this space You have heard that excuse a thousand times

00:07:57: haven't we y'all?

00:07:58: But Abra didn't just point out the problem.

00:08:00: He proved that HL-Seven and FHIR integrations between labs, platforms ,and digital health care providers are entirely possible today.

00:08:09: You know assuming the institutional will is there.

00:08:12: Let's

00:08:12: do a quick translation on those terms for anyone outside of the deepest layers of Health IT.

00:08:16: HL seven at its modern successor FHRR.

00:08:19: fast healthcare interoperability resources Are essentially the universal translator languages.

00:08:24: They provide a standardized architectural framework for how healthcare data is packaged and transmitted.

00:08:29: Right, it ensures that blood pressure reading generated by system A is instantly recognized as a blood pressure read by an entirely different system B.

00:08:39: When you saw the foundational connectivity The entire conversation around AI shifts.

00:08:44: As Ebert noted You stop asking whether AI can be integrated And start asking where exactly does it create real diagnostic value?

00:08:52: The focus moves to deploying large language models for automated clinical reporting or embedding clinical decision support directly at the point of care.

00:09:00: Inga Bergen shared a phenomenal example of this ecosystem logic working in the real world, EPICLARA.

00:09:06: Oh!

00:09:06: EPICLRARA that's the integrated solution born from a partnership between DocDoc.Health and eHex right?

00:09:12: Exactly it perfectly demonstrates the shift away from isolated points solutions toward embedded plays inside existing national systems.

00:09:19: The mechanism behind it is a perfect case study in structuring data because hospitals generate a staggering amount of unstructured data, I mean scan PDFs with referrals handwritten position notes faxed lab results.

00:09:32: It's a mess.

00:09:33: but Epichlera uses an AI end-to-end system to automatically read those documents extract the relevant medical information, structure it into machine-readable formats and integrate it directly in to the telematics infrastructure.

00:09:47: And the Telematics Infrastructure or TI is essentially this secure federal highway system for health data in Germany.

00:09:54: By structuring that data... ...and pushing it into the TI The system ensures that electronic patient record, the EPA actually becomes a useful tool for care rather than just digital dumping ground for unsearchable PDF

00:10:07: files.

00:10:08: This brings us full circle to the ultimate test of all this digital plumbing.

00:10:12: We are building incredibly complex architectures, FHIR integrations cross sector data flows but aren't we actually turning on water?

00:10:20: The ultimate proof point is adoption of EPA and digital identities.

00:10:24: The narrative around the EPA evolved dramatically at year's event.

00:10:27: it transitioned from a highly bureaucratic rollout topic into practical anchor theme judged entirely in its everyday usability.

00:10:35: Rudiger-Scharf captured this momentum perfectly in his observations from the Dakkasun height panel.

00:10:40: DAX CEO Andreas Storm made this staggering statement that digitalization progressed more in the last twelve months than it did over ten years.

00:10:49: Which

00:10:49: is wild to think about!

00:10:50: It IS, and C.D.

00:10:52: O'Hemmick Gerhardt provided a concrete metric we discussed earlier—a hundred million document uploads for the EPA in just twelve months.

00:10:59: That volume of data flowing into the system is massive signal that the EPA will finally arrive at everyday lives of insured individuals.

00:11:08: But the transformation isn't limited to clinical records either.

00:11:12: The administrative side of a hospital is undergoing a radical overhaul.

00:11:15: Janina Buchholz from the Bundesstreicher, I demonstrated this right?

00:11:18: Yes!

00:11:19: She showed how digital firsts are becoming incredibly concrete pointing out that purely digital clinic registration via EUDI Wallet could be reality by twenty-twenty seven.

00:11:29: The

00:11:29: EUDI wallet...the European Digital Identity Wallet.

00:11:33: It introduces fascinating cryptographic mechanics to hospital workflows Because currently, checking into a clinic involves presenting a physical insurance card filling out clipboards of paper forms.

00:11:45: And then reteption staff manually re-entering that data in to the hospital information system.

00:11:50: It is slow error prone bottleneck.

00:11:53: But EUDI wallet replaces entire process with smartphone.

00:11:57: The patient walks in, scans a secure QR code at the reception desk and authenticates their identity via a biometric pin or face side.

00:12:06: And through secure public key infrastructure they're verified identity.

00:12:10: insurance details are instantly and securely transmitted directly into hospital's admission software.

00:12:15: Buchholz pointed out the dual benefits of this architecture.

00:12:18: For the patient, no more clipboards.

00:12:20: for the practice it saves up to fifteen minutes administrative time per admission

00:12:24: plus significantly increases data quality because information is coming directly from a verified cryptographic source rather than manual data entry.

00:12:32: think about business impact.

00:12:34: Saving fifteen minutes per admission in a busy, high-volume clinic fundamentally alters their operational capacity.

00:12:41: Absolutely!

00:12:41: But this level of reliance on the smartphone introduces serious demographic challenge.

00:12:47: We're building an incredibly streamlined digital pipeline but how does that purely digital infrastructure handle the eighty year old patient who arrives without his smart phone?

00:12:58: Or the individual with lower digit literacy just isn't comfortable managing health identity via an app.

00:13:04: Exactly, are we risking leaving them behind?

00:13:07: The ecosystem has to maintain secure highly efficient physical fallbacks.

00:13:12: it cannot afford leave anyone behind trusted identities and cybersecurity or being positioned not just as defensive hygiene against ransomware but is the fundamental enablers of entire transformation.

00:13:24: if staff in patients don't trust security data flow automation fails which brings us to a highly uncomfortable reality.

00:13:31: Yeah, if the goal of all this transformation is a seamlessly connected ecosystem we have to look closely at who was currently being excluded from the conversation.

00:13:40: despite The massive wins with interoperability and EPA adoption.

00:13:44: several key professionals took to LinkedIn To point out glaring blind spots at DMEA

00:13:48: like Marcus C Mueller.

00:13:50: right

00:13:50: yeah He offered a very sharp critique regarding exactly Who's missing?

00:13:54: From the room.

00:13:56: he did acknowledge a keynote by politician Nina workin which offered a necessary paradigm shift, arguing that the healthcare system needs to focus on saving money through digitalization rather than saving money on digitalization.

00:14:08: That's

00:14:08: a crucial distinction!

00:14:09: But

00:14:10: Mueller's primary concern was almost complete invisibility of the nursing sector at this event.

00:14:15: He called it out brilliantly by highlighting the absurdity of scheduling The leading elderly care trade fair taking place simultaneously over in Essen.

00:14:24: You literally had people building the digital hospital of a future gathering in Berlin, while nursing professionals who actually run the floor and deliver patient care were siloed off an entirely different city.

00:14:36: Mueller's take away was profound – Digital health for all or not at all?

00:14:41: As long as industry treats Nursing & Digital Health to two completely separate branches true transformation is impossible!

00:14:49: Building a state-of-the art AI command center is useless if the nursing staff are still forced to manage their daily workflows on physical whiteboards because tech wasn't designed with operational input.

00:15:00: For you listening, especially for health tech founder or product manager this critique points to massive untapped blue ocean market.

00:15:07: The industry is currently hyper fixated on physician facing diagnostic AI and administrative automation.

00:15:14: Meanwhile, the nursing sector is practically begging for digital tools that relieve their documentation burden and streamline task shifting.

00:15:22: Whoever successfully bridges that gap is going to capture immense value.

00:15:25: Marvin

00:15:26: Abbott also identified another significant blind spot prevention...

00:15:29: Right!

00:15:30: He asked an incredibly uncomfortable question about the current strategic framework.

00:15:35: The prevailing logic in Digital Health falls a path of digital before outpatient, Before inpatient.

00:15:42: Abbott challenged that sequence, asking where preventive before digital actually fits into the model.

00:15:47: Our current architectural model is entirely reactive.

00:15:51: We're engineering incredible AI models to diagnose diseases faster and more accurately But we only deploy those models once someone is already sick enough To enter the hospital system.

00:16:01: Abert praised a keynote by Nina Rouge on longevity calling it perhaps The quietest yet most impactful impulse of the entire trade fair.

00:16:09: Shifting from a reactive sick care model to a proactive health-care model requires connecting early stage consumer health data like wearables and continuous glucose monitors.

00:16:18: To the clinical infrastructure long before a catastrophic health event occurs,

00:16:22: but integrating prevention requires an entirely different approach to how we pay for healthcare.

00:16:26: Dorothy Stam tied a lot of these frustrations together by emphasizing that actually bring digital med tech innovations into real patient care.

00:16:34: The foundational frameworks must be rethought

00:16:36: Like the reimbursement structures?

00:16:38: Exactly.

00:16:38: You can engineer the most brilliant FHIR compliant AI diagnostic tool on the market, but if the national reimbursement structure don't have a mechanism to pay for preventive algorithmic analysis hospitals simply won't adopt it.

00:16:52: Stams stressed that continuous exchange with representatives from politics providers and industry is absolutely central to fixing those frameworks.

00:17:01: The technology is vastly outpacing.

00:17:06: So when you look at these blind spots, the current state of the industry becomes very clear.

00:17:11: We're building a state-of-the art interoperable digital hospitals complete with AI command centers and automated EUDI wallet admissions but we forgot to invite the nurses who run the floor for design meetings

00:17:23: And our reimbursement models are completely ignoring healthy people outside trying not get admitted in first place.

00:17:29: It requires holistic view that industry is still struggling fully embrace.

00:17:33: As we wrap up this deep dive, I want to leave you with a thought inspired by Martin Blasch's reflection on the future

00:17:53: of acting more like a giant class reunion.

00:17:57: Right, the sheer diversity of the event makes it difficult to drive significant structural change in any one specific topic.

00:18:04: So ponder this Will this physical change of scenery to Munich next year be the exact catalyst that industry needs?

00:18:10: Could new location provide shock for the system required finally break down those remaining silos between medtech innovators, nursing professionals and preventive care models?

00:18:20: some would think about

00:18:21: If you enjoyed this episode, new episodes drop every two weeks.

00:18:24: Also check out our other editions on ICT and Tech Insights, DefenseTech Cloud Digital Products & Services Artificial Intelligence and Sustainability in Green ICT.

00:18:34: Thank You so much for joining us And don't forget to subscribe.

00:18:36: Keep asking the hard questions.