Faces of Digital Health

Episodes

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  "No hope for AI - yet" - Jordi Piera Jimenez on interoperability and open platform 06.11.2026 33m

  In 2017, the Catalan Health Service launched one of Europe’s most ambitious health digitalisation strategies. After two decades of building links between separate regional systems, Catalonia would move to a single common data layer, structured with openEHR, and place every application on top of it. The aim was data that is consistently structured, and therefore usable beyond the system that first recorded it. Jordi Piera Jiménez, now Director of the Digital Health Strategy Office at the Catalan Health Service, led the strategy. Nine years on, it is still being implemented, and he says he would write it exactly the same way today. At the end of October, I moderated a fireside chat with Jordi at the Campus Clínic Innova Summit 2026 in Barcelona. We discussed the right approach to healthcare data in 2026, the state of interoperability in Europe and what AI changes. We also asked a more basic question: does the sector know what to do with its data at all, when so much of it is unreliable? According to HIMSS’s 2026 AI and digital transformation landscape report for North America, only 47% of leaders are confident their data is accurate, and only 21% say it is fully leveraged for clinical and operational decision-making. HAT THE CONVERSATION COVERS • Who does what: openEHR, SNOMED CT, LOINC and HL7 FHIR • Why AI models don't transfer between hospitals: semantics, not only populations • Catalonia's infrastructure-first digital health strategy and the open platform in healthcare • The platform economy analogy: iOS and Android versus BlackBerry • Patient identifiers, patient matching and the longitudinal health record • EHR data quality: copy-paste clinical notes, 400–600 data silos, unused data • "Right data, right time": why more clinical data is not the goal • AI scribes, patient-generated data and parallel health records • The 17-year adoption gap in healthcare and pressure from the consumer market • Clinicians using LLMs as "Dr Google 2.0", answer consistency and guardrails for CIOs • Digital health training in medical and nursing education • Vibe-coded clinician apps, regulation and owning your digital infrastructure • The WHO/ITU reference architecture for digital public infrastructure for health • Vendor lock-in versus a common data layer: Norway, Sweden, Finland and Asklepios CHAPTERS 03:00 Back from Sydney: standards bodies find common ground 04:40 "No hope for AI yet": openEHR, SNOMED, LOINC and FHIR explained 06:45 Infrastructure first: Catalonia's strategy and the COVID algorithm that couldn't travel 08:10 The open platform in healthcare: lessons from iOS, Android and BlackBerry 10:55 Would the strategy change today? Data silos and patient identifiers 12:05 EHR data quality: copy-paste notes, 400–600 silos, unused data 15:30 Do clinicians need all the data? Right data, right time 17:05 AI scribes, patient-generated data and the 17-year adoption gap 20:10 LLMs as "Dr Google 2.0": consistency, risk and guardrails 22:25 Training clinicians for digital health 24:35 Vibe-coded apps, vendor lock-in and owning your infrastructure 27:35 The WHO/ITU reference architecture for digital public infrastructure for health 28:40 The North Star: Nordic regions, Asklepios and the platform economy FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #openEHR #interoperability #HL7FHIR #SNOMEDCT #digitalhealth #healthdata #Catalonia #healthcareAI #vendorlockin #digitalpublicinfrastructure #FacesOfDigitalHealth
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  Malta's primary care after the EPR: data governance, AI and the EHDS (Stefan Buttigieg) 30.10.2026 35m

  Malta's health centres settled the digitisation question years ago. The harder work, Dr Stefan Buttigieg argues, starts now. Malta's public primary care has run on an electronic patient record since its rollout began in late 2019. With the European Health Data Space now moving from regulation to implementation, the question in Maltese health centres is no longer whether to digitise but what a mature record should do next. Dr Stefan Buttigieg, who first joined Faces of Digital Health in 2019 to discuss Malta as a gateway to the European market, returns after moving from national eHealth work into Primary HealthCare. He sets out why data governance has to come before AI, why AI implementation depends on hardware and care pathways as much as software, and why he would rather build tools clinicians never need to be trained on. Guest Dr Stefan Buttigieg – Specialist in Public Health Medicine, Ministry for Health and Active Ageing, Malta (Primary HealthCare); creator of the EHDS Explorer Host Tjaša Zajc – Founder, Faces of Digital Health What the conversation covers • EHDS implementation in primary care: from national policy to the clinic • Malta's electronic patient record for primary care, seven years on • MyHealth@EU and cross-border patient summaries since 2019 • Setting up a national contact point for eHealth: the small-state advantage • The EHDS Explorer: an independent, vibe-coded guide to the regulation and member-state implementation tracking • Digital health authorities and health data access bodies ahead of March 2027 • Health data governance and data quality as the precondition for AI • AI in breast screening, ophthalmology and diabetes care • Why AI implementation depends on hardware, integration and the care pathway • Malta's AI for All programme and Copilot across government • AI literacy for clinicians, and the case for AI that needs no training • Clinical documentation for care: Europe and the US compared • The 2027 goal: restoring clinicians' joy in documentation Chapters 03:00 Malta as a European test bed, revisited 03:36 From national EHDS policy to EHDS on the ground 05:49 Primary care seven years after the electronic patient record 08:57 MyHealth@EU and cross-border patient summaries 13:28 Building a national contact point: lessons from a small state 16:35 Vibe-coding the EHDS Explorer and tracking implementation 19:41 Primary care priorities: data governance before AI 22:47 AI already in use: Copilot and Malta's AI for All 26:22 Why AI implementation is a hardware and care-pathway problem 30:19 The 2027 goal: joy in clinical documentation 32:19 Documentation for care: Europe and the US compared 33:59 AI literacy for clinicians, or AI that needs no training Listen and subscribe: Podcast (Spotify): https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Website: https://www.facesofdigitalhealth.com Youtube: https://www.youtube.com/@facesofdigitalhealth #EHDS #EuropeanHealthDataSpace #PrimaryCare #ClinicalAI #DigitalHealth #Malta #FacesOfDigitalHealth
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  Agentic Patient 12: Early Diagnosis of Ovarian Cancer due to a Chatbot Use 23.10.2026 46m

  Her relative said it was nothing. Two weeks of symptom history in ChatGPT said get checked. She was diagnosed at stage one. In early 2023, Alvina Nadeem was 36, a mother of two young boys, and tired in a way she put down to burnout or perimenopause. She was already a heavy ChatGPT user through her work in change management, so she tried something she had never done: she described her symptoms to it. When the model refused to answer first-person health questions, she reframed herself as a clinical case for a medical resident and asked it to explain its reasoning. Ovarian cancer appeared as one of four possibilities. What followed — a post-it note of symptoms to present together, a GP who ordered imaging, a stage one diagnosis — is the starting point for a wider conversation about how patients actually use AI: to navigate the health system, to filter misinformation, and to carry their own story between specialists who cannot see each other's notes. This episode describes one patient's experience and is not medical advice. If you have persistent symptoms, speak to a clinician. GUEST Alvina Nadeem — Professional engineer (P.Eng.), change management advisor and leadership coach; Board member, Ovarian Cancer Canada; Co-director, Cancer and Work; Coalition Priorité Cancer au Québec Host: Tjaša Zajc THE AGENTIC PATIENT A Faces of Digital Health series on how patients and caregivers actually use AI — which tools, which prompts, which guardrails — and what that does to the relationship with clinicians. Series hub: https://www.facesofdigitalhealth.com/agentic-patient WHAT THE CONVERSATION COVERS • "No-lution": why dismissing patient AI use hides how people already use it • Shadow AI in healthcare: patients were using ChatGPT long before health systems noticed • Using ChatGPT for health questions in 2023, when the model refused first-person medical queries • Role-play prompting: presenting yourself as a clinical case and asking the model to show its reasoning • Prompting for possibilities rather than confirmation — and why that limits sycophancy • Ovarian cancer symptoms: bloating, early satiety, fatigue, cramping and abnormal bleeding as a constellation • Why ovarian cancer is diagnosed late, and why age 36 put her outside anyone's differential • How to describe symptoms to your doctor so they lead to the right tests • CA-125 testing and the routine pelvic pain workup • Sharing health data with ChatGPT: privacy, identifiers and the risk-reward of a crisis • AI as a health system navigation tool: which specialist, which questions, is this wait normal • The worried well, wellness misinformation and AI as a filter • Practical advice: approach the model as a tester, and end every session with questions for your doctor • Emergency versus chronic illness: where general chatbots lose context • Patient-built AI tools for specific conditions • Continuity of care: the patient as the relay between family doctor and oncologist CHAPTERS 03:00 The Agentic Patient: how patients use AI in their care 04:14 "No-lution" and the shadow AI already inside healthcare 07:38 ChatGPT in early 2023: a cautious, restricted tool 10:10 Learning to prompt: role, context and the role-play workaround 16:54 Challenging the model: sycophancy then and now 19:36 Presenting a symptom constellation to get the right tests 25:09 The post-it note, the pelvic exam and the imaging referral 27:49 CA-125 and the routine pelvic pain workup 29:00 What patients use AI for: health system navigation 33:31 The worried well, misinformation and AI as a filter 37:21 Practical advice: test the tool, end with questions for your doctor 39:45 Emergency versus chronic: where general chatbots fall short 46:28 AI as the keeper of a patient's story between specialists MENTIONED Ovarian Cancer Canada • Cancer and Work • Coalition Priorité Cancer au Québec • CA-125 (cancer antigen 125) test • ChatGPT Discussion with Russ Read Barrow: https://podcasts.apple.com/us/podcast/the-agentic-patient-2-one-tool-one-job-cancer/id1194284040?i=1000764804039 FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #TheAgenticPatient #OvarianCancer #PatientAI #ChatGPT #healthAI #patientnavigation #earlydiagnosis #digitalhealth #patientempowerment #cancercare
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  How to get hospital AI from pilot to scale (Eyal ZImlichman, Sheba Medical Centre) 16.10.2026 37m

  Three in ten AI pilots at Sheba Medical Center never scale. Eyal Zimlichman on why, and what Europe's regulation holds back. Nine years after his first Faces of Digital Health interview, when ARC was still being built inside Sheba Medical Center, Eyal Zimlichman returns with the numbers. He explains how Sheba measures the return on AI (clinical outcomes, cost and clinician burnout), why its chief quality officer rather than its AI officer signs off every deployment, and why about 30% of pilots are discontinued. We discuss what ambient scribes change for patient safety, documentation and malpractice, why hospitals still treat start-ups as a nuisance, why no European hospital belongs to Mayo Clinic Platform's federated data network, and how ARC plans to grow tenfold in 2027. GUEST Prof. Eyal Zimlichman — Chief Transformation, Innovation and AI Officer, Sheba Medical Center, Israel; founder and director, ARC Innovation Host: Tjaša Zajc WHAT THE CONVERSATION COVERS - What has changed at Sheba Medical Center and ARC since 2017 - How a hospital measures AI return on investment: outcomes, cost, access and burnout - Aidoc and AI triage for intracranial haemorrhage: the Sheba mortality study - AI governance in hospitals: why the chief quality officer approves AI deployments - Time-limited AI approvals: 3–12 month reviews based on risk - Ambient scribes: accuracy differences between vendors and medication-name errors - Ambient documentation, billing and the case for fewer malpractice claims - Why 30% of hospital AI pilots fail to scale, including an internally built discharge alert - Open innovation: why healthcare systems distrust start-ups - Procurement, tenders and the barriers to bringing in new technology - Europe as a "regulation superpower": unclear rules, cautious lawyers and the Charité ARC centre - Mayo Clinic Platform and federated health data sharing without European partners - Hospitals as economic engines: ARC start-ups, jobs and KPIs - China, AI regulation and the speed of adoption - ARC Global in 2027: tenfold scale-up and AI-native hospitals by 2030 CHAPTERS 02:43 Nine years on: Sheba, ARC and AI since 2017 06:52 How to measure AI return on investment in a hospital 10:58 Patient safety and ambient scribes: who approves AI 15:51 Ambient documentation, billing and malpractice 18:06 The pilots that didn't scale, and why 21:47 Open innovation: why hospitals distrust start-ups 26:35 Europe as a "regulation superpower" 30:43 A hospital as an economic engine: start-ups and jobs 36:13 China, AI regulation and speed 39:27 ARC in 2027: tenfold growth and AI-native hospitals MENTIONED ARC Innovation at Sheba Medical Center • ARC Global • Charité BIH ARC Innovation Center (Berlin) Aidoc • Mayo Clinic Platform • ARC Summit, Tel Aviv, 22 October 2026 Orion et al., International Journal of Emergency Medicine (2023) — AI triage for intracranial haemorrhage Earlier FoDH episode: Eyal Zimlichman, 2017 [LINK] FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #healthcareAI #digitalhealth #hospitalinnovation #ambientAI #AIgovernance #patientsafety #ShebaMedicalCenter #healthtech #openinnovation #healthpolicy #AIregulation #FacesOfDigitalHealth
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  Should prevention be treated as capital investment? (Joanna Lane) 07.10.2026 36m

  When prevention works, nothing happens. That's why it gets cut. Joanna Lane on financing prevention as long-term investment. Health systems in Europe spend a small fraction of their budgets on prevention, and that fraction is renewed annually and cut first when treatment costs rise. Joanna Lane has spent decades working on health and regional development across Europe, and argues that prevention should be reclassified from expenditure to capital investment, financed the way we finance energy grids, transport and pensions. In this conversation she explains what the Horizon Europe project Invest4Health learned from eight regional testbeds, why Public Health Wales disinvested around £10m to reinvest it, how health systems' own procurement and hiring can improve the determinants of health, and what finance ministers need to hear before they will treat prevention as an investment. We also discuss wearables and the longevity trend, where personal responsibility ends and public policy begins, and a three-layer model for funding prevention at scale. GUEST Joanna Lane — Managing Director, Stichting Health ClusterNET; Chair, FH Europe Foundation; Invest4Health (Horizon Europe) Host: Tjaša Zajc WHAT THE CONVERSATION COVERS - Why the benefits of prevention stay invisible in health budgets - Why local prevention and health promotion budgets are the first to be cut - Invest4Health: eight regional testbeds for financing health promotion and disease prevention - Smart capacitating investment and the EU high-level task force on social infrastructure - Why a single financing template didn't work across regions - Financing toolkits and competence building for regional health authorities - Reclassifying prevention as capital investment and soft infrastructure - Public Health Wales: disinvesting from health promotion to reinvest around £10m - Prevention spending during and after COVID, and the pull back to acute care - Defence, energy and climate competing for health budgets - The ripple effect of health spending: local procurement, inclusive employment and NEETs - How to make the investment case for prevention to a finance minister - Local Multiplier 3 (LM3) and the return on local procurement - 20-minute neighbourhoods and multi-use community hubs for older people - Remote monitoring for independent living: the SMILE project - Wearables, longevity and the retention problem in consumer digital health - Personal responsibility vs public policy: school food, screening and familial hypercholesterolaemia - Three layers of prevention finance: protected budgets, social outcome funds and patient capital - Metrics for treating prevention as investment in national statistics CHAPTERS 2:00 The Finance Minister Anecdote 3:18 Welcome & 40 Years in Prevention 3:54 The Invisible Challenge of Prevention 6:12 The Invest for Health Project 10:47 Financing Toolkit & Training for Regions 12:02 Prevention as Capital Investment 13:03 Bold Examples: Disinvest to Reinvest 16:44 COVID's Regression in Prevention 18:04 Healthcare's Ripple Effect on Local Economies 20:50 Engaging Finance Ministries 23:25 Evidence for Return on Investment 25:07 Community Design for Prevention 27:34 Longevity & Digital Health Solutions 33:11 Personal Responsibility vs. Systemic Prevention 36:11 A Three-Layer Financing Model for Prevention MENTIONED Invest4Health — Horizon Europe project on financing health promotion and disease prevention High-Level Task Force on Investing in Social Infrastructure in Europe (report, January 2018) Syreon Research Institute, Budapest • Public Health Wales • Local Multiplier 3 (LM3) SMILE project (Innlandet Hospital Trust, Norway) • FH Europe Foundation • EU Safe Hearts Plan Earlier FoDH episodes: Herko Coomans on interoperability as an infrastructure funding problem [LINK] • Henrique Martins on twenty years of EU health data projects [LINK] FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #prevention #publichealth #healthfinancing #healthpromotion #diseaseprevention #Invest4Health #healthpolicy #healtheconomics #socialinfrastructure #healthinvestment #digitalhealth #FacesOfDigitalHealth
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  €200m and 20 years: What EU health data projects built, and what EHDS needs next (Henrique Martins) 01.10.2026 43m

  Nearly €200m, twenty years of EU health data projects. Henrique Martins on what they built and what EHDS needs next. Before the European Health Data Space became law, the EU had already funded two decades of cross-border interoperability work: epSOS, EXPAND, Trillium Bridge, JAseHN, eHAction and more. Henrique Martins has worked on most of them. In this conversation he explains how those projects became MyHealth@EU, why the European EHR exchange format matters for every hospital and IT vendor, what digital health authorities and health data access bodies will do from 2027, and how far patient control of health data can realistically go. He also argues that Europe is not behind on cross-border exchange, that slow national progress is ultimately a political choice made by voters, and that 2027 will show whether the EHDS implementing acts can actually be applied. GUEST Henrique Martins — Associate Professor, ISCTE – University Institute of Lisbon; coordinator, i2X (Intelligent Implementations of the European EHR Exchange Format); former President of SPMS, Portugal's national digital health agency; former Member States co-chair, EU eHealth Network Host: Tjaša Zajc WHAT THE CONVERSATION COVERS What nearly €200m in EU interoperability funding bought over twenty years How epSOS, EXPAND and OpenNCP became MyHealth@EU Cross-border ePrescription and patient summary: who exchanges data today The European EHR exchange format (EEHRxF) and why discharge reports still don't travel Transformation layers: wrapping HL7 v2 messages in FHIR AI and natural language processing to structure clinical data at the point of care Trillium Bridge: EU–US patient data exchange, and why it couldn't be funded today Xt-EHR and how joint actions shape the EHDS implementing acts Digital health authorities vs health data access bodies: why one versus many Patient rights under EHDS: access, download, correction and upload Health data activism and patient health literacy The xShare Yellow Button, MyHealth@MyHands and the EU Digital Identity Wallet i2X: 35 pilots, 12 member states and 3 million citizens — and everyone else Is Europe slow? Cross-border exchange compared with North America The EHDS test for 2027: implementing acts and demonstration sites CHAPTERS 03:00 Fifteen years of European interoperability projects 03:36 €200m over twenty years: what EU funding built 06:38 FHIR, implementation guides and the European exchange format 10:10 From drop-down menus to AI: structuring health data 10:48 epSOS, eHAction and the projects that shaped EU digital health 14:02 Trillium Bridge: when the EU and US exchanged health data 15:58 Xt-EHR and why joint actions shape the implementing acts 18:58 Digital health authorities and health data access bodies explained 23:13 Patients and EHDS: access, correction and health data activism 29:04 Is Europe too slow? 3 million in pilots, 400 million waiting 39:08 The best case for 2027: implementing acts that work Recent FODH episodes on interoperability and EHDS: Herko Coomans on interoperability [   • Interoperability Isn't Failing — It's Unde...  ] • Nils Hellrung on openEHR and EHDS [   • Just Connecting systems isn't interoperabi...  ] • Karlien Hollanders, The Agentic Patient [   • "I stopped letting AI read my daughter's m...  ] FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn:   / faces-of-digital-health   Spotify: https://open.spotify.com/show/4cElKJH... Apple Podcasts: https://podcasts.apple.com/gb/podcast...#EHDS #EuropeanHealthDataSpace #interoperability #digitalhealth #healthdata #MyHealthEU #FHIR #ePrescription #healthpolicy #EEHRxF #patientdata #FacesOfDigitalHealth
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  What is NVIDIA actually doing in healthcare? (David Niewolny) 25.09.2026 53m

  One ultrasound tech, four scanning rooms. NVIDIA's David Niewolny on what "augmented autonomy" asks of clinicians. NVIDIA is best known for GPUs, but its healthcare strategy is a full stack: compute to train models, compute to run them at the point of care, and simulation to generate the data that medical robotics lacks. In this interview, David Niewolny explains how that stack underpins autonomous X-ray and ultrasound with GE HealthCare, surgical robotics simulation with Johnson & Johnson MedTech, and the Open-H surgical robotics dataset. He argues that open models are a regulatory necessity in healthcare, that software-defined medical devices will shrink innovation cycles from years to months, and that the path to autonomy in surgery will follow the one taken by autonomous vehicles, one level at a time. We also press on the parts that remain unsettled: whether AI efficiency turns into clinician burnout, whether synthetic data reflects real patient populations, and what could still stall adoption. GUEST David Niewolny — Senior Director and Global Head of Business Development, Healthcare & Medical, NVIDIA Host: Tjaša Zajc WHAT THE CONVERSATION COVERS - NVIDIA's healthcare strategy: training, simulation and edge deployment for medical AI - Why open models and open datasets matter in regulated healthcare - Autonomous X-ray and ultrasound with GE HealthCare: one technician, multiple rooms - "Augmented autonomy": keeping a clinician in the loop - AI efficiency, cognitive load and the risk of a new wave of clinician burnout - Ambient clinical documentation as the clearest efficiency case - Surgical robotics and the autonomous-vehicle model of stepwise autonomy - Why robotics costs are falling, and what it means for hospital ROI - Synthetic data for healthcare robotics: Cosmos-H, Isaac for Healthcare and the Open-H dataset - Can simulated data reflect a local patient population? - Model drift, verification and validation, and governance of AI agents in healthcare - Is healthcare worried about superintelligence? - Software-defined medical devices and the FDA's predetermined change control plan (PCCP) - How regulators are adapting to AI-enabled devices - Change management and ROI as the real barriers to adoption CHAPTERS 02:00 NVIDIA in healthcare: more than GPUs 03:03 The full stack: training, simulation and edge deployment 08:46 Why open models matter in regulated healthcare 10:51 Autonomous X-ray and ultrasound: one technician, four rooms 14:49 AI augmentation and clinician burnout 18:16 What NVIDIA looks for in a partner, and the surgical robotics bet 23:38 Cheaper robots, more competition, clearer ROI 27:37 Synthetic data, Cosmos-H and the Open-H surgical dataset 31:43 Does simulated data reflect the real world? 34:37 Model drift and governing AI agents in healthcare 38:03 Superintelligence, change management and the autonomous-vehicle analogy 43:10 Software-defined medical devices, the FDA's PCCP and regulators 49:54 A golden age for medtech? What could still slow it down MENTIONED NVIDIA Isaac for Healthcare • Cosmos-H • Open-H-Embodiment dataset • NVIDIA Nemotron • BioNeMo Agent Toolkit GE HealthCare • Johnson & Johnson MedTech (MONARCH platform) • Abridge • Aidoc • OpenEvidence • Sword Health FDA Predetermined Change Control Plan (PCCP) FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #NVIDIA #healthcareAI #medtech #surgicalrobotics #physicalAI #digitalhealth #medicalimaging #syntheticdata #openmodels #FDA #medicaldevices #healthcarerobotics
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  Epic or open platforms? The choice facing European hospitals (Nils Hellrung) 16.09.2026 46m

  Most interoperability debates focus on exchange formats. In this discussion with Dr Nils Hellrung, medical informatician and CEO Strategy & Operations at vitagroup, Nils focuses on the need for shaping hospital IT with governance and financing. Linking proprietary systems through standards, he says, will always lose meaning, which is why he backs openEHR as a vendor-neutral clinical data core, with FHIR used for exchange. vitagroup in providing the data platform for Catalonia, and just signed a contract with a large hospital group in France. The discussion touches different market approaches to interoperability and challenges of markets such as Germany, where each federal state has its own authority to regulate and implement as they please. Tjasa Zajc and Nils Hellrung talk about what "AI-native" data integration means in practice, why 95% accuracy of AI is not good enough in healthcare, and whether Europe ends up with monolithic US EHRs or open platforms. This episode is supported by vitagroup. GUEST Dr Nils Hellrung — CEO Strategy & Operations, vitagroup; medical informatician; co-author, "Health Information Systems: Architectures and Strategies" Host: Tjaša Zajc WHAT THE CONVERSATION COVERS Why hospital IT architecture reflects governance, trust and financing: three professors, three PACS Billing versus therapy: why German hospital and ambulatory systems don't talk to each other AI in healthcare: the widening gap between what is possible and what happens in practice Why Europe doesn't have to be slower than the US in digital health Data availability as the main barrier to digital health implementation openEHR vs FHIR: clinical data repository vs communication standard FHIR version changes and national profiles: the semantic interoperability problem Is European Health Data Space (EHDS) interoperability achievable, or only for a core data set? Catalonia's single patient record on openEHR: 18 months to go-live and the next step to an open health platform Why Catalonia's single health system makes adoption easier Germany: 16 federal states, 17 data protection authorities, and a 20-year-old electronic patient record (ePA) programme Alliance SIH in France: competitors agreeing on a shared health data layer AI as a translator between clinical data and clinicians AI-native vs AI-enabled software, and why data pipelines must stay deterministic Deskilling risk: clinicians who stop thinking because AI seems to have the answer Epic at Charité, monolithic EHRs vs open platforms, and European digital sovereignty in healthcare Europe's health IT ecosystem in 2036: best, worst and realistic scenarios CHAPTERS 02:30 From textbook to practice: 15 years of health information systems 03:00 Why hospital IT looks the way it does: three professors, three PACS 06:50 Is AI speeding up healthcare? The gap between possible and real 10:39 EHDS and data availability: the biggest barrier to digital health 14:00 openEHR vs FHIR: how health data normalisation works in practice 16:40 Is European interoperability achievable? The semantic problem 20:00 Catalonia: why a single health system makes adoption possible 26:48 Germany: 16 states, 17 data protection authorities 30:45 France: Alliance SIH and a shared data layer 32:14 The data layer as Europe's AI advantage 35:38 AI in data integration: why "convincing" is dangerous 41:48 Agentic AI, guardrails and the risk of deskilling 45:00 Europe in 2036: Epic, open platforms and a "very nineties decision" FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com Spotify: https://open.spotify.com/show/4cElKJH... Apple Podcasts: https://podcasts.apple.com/gb/podcast... LinkedIn:   / faces-of-digital-health  #openEHR #EHDS #interoperability #digitalhealth #healthdata #FHIR #healthIT #healthcareAI #EuropeanHealthDataSpace #Catalonia #vitagroup #FacesOfDigitalHealth
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  Agentic Patient 11: ""I stopped letting AI read my daughter's medical records" (Karlien Hollanders) 09.09.2026 55m

  She has 408 of her daughter's medical documents. She stopped letting AI read them — here's why. Karlien Hollanders is a pharmacist who became her daughter's medical record. When her firstborn went into complete renal failure at two months old and was diagnosed with primary hyperoxaluria type 1, she spent three years moving between Belgian specialist hospitals that could not exchange data with each other. Eleven years later, 408 documents sit on a national platform that can be filtered by doctor, hospital and date — and nothing else. This episode of The Agentic Patient is about what happens when you actually try to put AI to work on a real, fragmented, non-anonymised medical history: what it organised, what it got wrong, and the reason she has stopped. GUEST Karlien Hollanders — Patient expert and caregiver; consultant to the Belgian federal health service; pharmacist by training Host: Tjaša Zajc THE AGENTIC PATIENT A Faces of Digital Health series on how patients and caregivers actually use AI — which tools, which prompts, which guardrails — and what that does to the clinical relationship. Series hub: https://www.facesofdigitalhealth.com/agentic-patient WHAT THE CONVERSATION COVERS - Being your child's "walking medical record" across five specialist hospitals - Why case management exists for cancer and diabetes but not for rare disease - 408 PDFs, three filters: the missing-metadata problem in national health data platforms - Federated health data explained — and why you still download your records one click at a time - What AI document tools did well: organising records by organ and producing specialty-specific summaries - The timeline AI could not build, and why copy-pasted clinical letters break text-layer summarisation - Why internists and orthopaedic surgeons need the same records and completely different queries - The 15-minute consultation and the unprepared specialist - Local bulk de-identification: the tool that does not exist, and the vendors who could not supply it - A child's medical data on third-party AI platforms, twenty years forward - Patient summaries and cross-border care: what an emergency room in another country actually needs - EHDS versus AI extraction — structuring data at the point of documentation instead of after it - SNOMED CT and structured entry that clinicians do not know they are doing - ZAS Antwerp's AI-generated patient-friendly discharge letters, already in production - Why a shared medication scheme can be five years out of date in a country with electronic prescribing - Personal health vaults, EU wallets and itsme: identity is not the same as data portability - Practical advice: how to assemble your own records before letting AI near them CHAPTERS 03:00 A caregiver's view of patients using AI 04:28 Renal failure at two months: primary hyperoxaluria type 1 10:43 Ten years on: what has changed in Belgian health data sharing 13:04 408 documents, three filters: the metadata problem 15:03 Downloading a federated health record one PDF at a time 17:20 What AI document tools organised — and the timeline they couldn't build 22:27 Same records, different questions: internists vs orthopaedic surgeons 26:38 Not a technology problem: incentives and the missing business case 30:18 AI as a better Google — and where that gets dangerous 32:30 The anonymisation gap: why she stopped feeding AI real data 36:10 Patient summaries, EHDS and structuring data at the source 41:46 ZAS Antwerp's AI-written patient letters, already in production 47:49 Preparing for a specialist visit when your records are scattered MENTIONED European Health Data Space (EHDS) — Regulation (EU) 2025/327 ZAS (Ziekenhuis aan de Stroom), Antwerp — AI-generated patient-friendly letters FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #TheAgenticPatient #digitalhealth #healthdata #EHDS #patientdata #caregiver #healthAI #rarediseases #interoperability #healthtech #patientempowerment #medicalrecords
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  Interoperability Isn't Failing — It's Underfunded (Herko Coomans) 27.08.2026 1h 1m

  35 views Aug 24, 2026 In-person video interviews"Interoperability isn't failing — it's underfunded." Herko Coomans on standards as public infrastructure. Most interoperability conversations start with what's technically broken. This one starts by rejecting that framing. Herko Coomans argues that health data exchange is a wicked problem rather than an unsolved engineering task, that the real constraint is infrastructure funding and governance, and that the moment governments mandated standards, they took on a public accountability they haven't yet resourced. We cover the closing post-COVID funding window, what EHDS implementation actually looks like inside a country that has no national health data authority, why the EU started its data union with health, and where AI genuinely helps interoperability — and where it quietly doesn't. GUEST Herko Coomans — International Digital Health Coordinator, Ministry of Health, Welfare and Sport (VWS), the Netherlands; interoperability lead, Global Digital Health Partnership (GDHP) Host: Tjaša Zajc WHAT THE CONVERSATION COVERS Why interoperability is a "wicked problem," not a failure — and why it was never all-or-nothing Interoperability as an infrastructure funding crisis rather than a technical one The closing post-pandemic window for digital health investment Why healthcare executives are asking the ministry to be MORE directive on standards What changes when standards become law: parliamentary questions about SNOMED CT and nursing terminology Who funds SNOMED CT, HL7 FHIR and IHE for the next 20–50 years The national FHIR profile problem: why a Dutch profile may not work in Germany From product implementation to integration: national platforms as an emerging concept GDHP explained: 44 countries, 40%+ of the world's population, no legal existence by design The global stewardship gap after US and Argentine withdrawal from the WHO The International Patient Summary in practice — Canada, Brazil, and QR-code patient summaries at the Hajj EHDS implementation reality check: 2027, 2029, 2031 deadlines and national health data access bodies Why the EU chose health as the first pillar of its data union — and what Brexit had to do with it AI and interoperability: ambient scribes, ontology reasoning, and why a plausible SNOMED code isn't a correct one The OECD's interoperability valuation: 2.7–6.6% of annual health expenditure Shifting from project funding to sustainable public infrastructure funding for standards CHAPTERS 00:00 Interoperability in 2026: what are we still not getting? 01:06 The pushback: a wicked problem, not a failure 05:50 Why interoperability is an infrastructure funding problem 10:25 Who owns integration? From product rollout to national platforms 16:32 When standards become law: parliament, nurses and SNOMED CT 19:01 National FHIR profiles and the interoperability they don't deliver 25:49 GDHP: 44 countries, 40% of the world, no legal existence 30:52 The Dutch chairmanship and the handover to Portugal 35:35 The International Patient Summary in Canada, Brazil and Mecca 39:52 EHDS reality check: European excitement, national scrambling 47:41 Why the EU started its data union with health 50:58 AI and interoperability: "not the magic, but the magician" 1:00:06 The OECD number: what interoperability is actually worth MENTIONED OECD, "Interoperability in healthcare: Towards an interconnected future" (Health Working Paper No. 197, July 2026) International Patient Summary (IPS) — HL7 FHIR, CDA, ISO, SNOMED Global Patient Set, IHE European Health Data Space (EHDS) • 21st Century Cures Act • My Health Record legislation (Australia) • Ayushman Bharat Digital Mission (India) FACES OF DIGITAL HEALTH Podcast: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn:   / faces-of-digital-health   Apple Podcasts: https://podcasts.apple.com/us/podcast...#interoperability #EHDS #digitalhealth #healthdata #FHIR #SNOMEDCT #healthpolicy #healthIT #GDHP #healthcareAI #europeanhealthdataspace #InternationalPatientSummaryInteroperability Isn't Failing — It's Underfunded (Herko Coomans)
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  Agentic Patient 9: She built an AI companion for breast cancer patients - and won't upload her records to ChatGPT 18.08.2026 49m

  "I am actually quite wildly uncomfortable with patients using LLMs." She built an AI companion for breast cancer patients — and she means it. Ellyn Winters-Robinson was diagnosed with breast cancer in March 2022, months before ChatGPT launched. She wrote a book about it on her iPhone during chemotherapy. That book became AskEllyn, an AI companion used across a hundred countries. In this episode of The Agentic Patient — a Faces of Digital Health series on how patients actually use AI, which prompts, which guardrails — she talks to Tjasa Zajc about what an AI companion can hold that a clinician cannot, and why she still worries about where patient data goes. Guest: Ellyn Winters-Robinson, CEO of The Lyndall Project and AskEllyn, author of "Flat Please Hold the Shame" What the conversation covers: - Building an AI companion from a book written on an iPhone during chemotherapy - Why she keeps AskEllyn strictly non-medical, and how that guardrail held up under health-insurer review - Whether one woman's lived experience can support patients with different cancers, cultures and languages - Why traditional cancer support groups can become "places of collective trauma" - Scanxiety, and what happened when she used her own chatbot during a CT scare - Why she is uncomfortable with patients uploading medical records to ChatGPT or Claude - Patient data rights, desperation, and the risk of being "victimized again" by AI tools - The Canadian Cancer Society-funded study now testing whether AI companions actually help - "The patient is the workflow" — lived experience as an untapped resource in health system design - How clinicians can coach patients to use AI safely instead of pretending they aren't Chapters: 00:00 Intro: why The Agentic Patient series exists 04:00 Meeting Ellyn Winters-Robinson 05:26 Diagnosed in 2022, before ChatGPT existed 07:36 From a book written on an iPhone to an AI companion 08:53 Why nurses and social workers started recommending it 09:54 Can one woman's story support every patient? 12:21 Shame, language, and cultures where breast cancer isn't discussed 13:25 Scanxiety — and taking a pep talk from your own chatbot 15:57 How AskEllyn is built on top of the LLMs 18:19 The non-medical guardrail, and how it held up under insurer review 21:51 Why patient AI use is outpacing the system 29:25 "The patient is the workflow": lived experience as untapped data 34:05 Inside the Canadian Cancer Society study 41:03 Why she's uncomfortable with patients uploading records to LLMs 45:54 The trauma healthcare never sees 6 tips on using AI as a patient: https://youtu.be/DGGVXxB4ygI?si=7m7HqCLKow51KSlQ Faces of Digital Health: Website: https://www.facesofdigitalhealth.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 Newsletter: https://fodh.substack.com The Agentic Patient series: https://www.facesofdigitalhealth.com/agentic-patient AskEllyn: https://askellyn.ai #DigitalHealth #AIinHealthcare #BreastCancer #PatientAdvocacy #CancerSurvivorship #HealthTech #TheAgenticPatient
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  Agentic Patient 8: Why an AI Founder Won't Trust Chatbots With Her Own Health 04.08.2026 40m

  In this episode of The Agentic Patient, a Faces of Digital Health series on how patients are using AI to find answers the healthcare system didn't give them, Tjasa Zajc talks to Elena Ikonomovska, CEO and Co-Founder of Diadia Health. She stopped trusting chatbots with her own health data — after building an AI company on the problem they create. Elena talks about her two-and-a-half-year journey that followed her mother's death and her own dismissed symptoms — and the causal-reasoning AI she built in response. Guest: Elena Ikonomovska, CEO, Co-Founder & Chief AI Officer, Diadia Health What the conversation covers: - Why Ikonomovska calls generative AI's confident wrong answers "faithful hallucinations" - Building a causal-reasoning engine instead of using large language models for clinical decisions - Why lab "normal" ranges differ by genetics — and what that means for your bloodwork - Her own dismissed thyroid and pre-diabetes symptoms, and what a two-and-a-half-year diagnosis journey actually looks like - The risk of self-diagnosing from ChatGPT-style tools, and what to ask any AI health platform about your data - Why she believes AI should strengthen, not replace, the doctor-patient relationship - Early clinical results: agreement rates with physician judgment and reductions in diagnostic trial-and-error - The equity risk in AI-driven healthcare — who gets access to validated tools, and who doesn't Chapters: 00:00 Intro: why The Agentic Patient series exists 02:30 Meet Elena Ikonomovska and the case for causal AI 03:35 From two decades in machine learning to health AI 07:07 What the model needs: blood panels, genetics, and interactions 09:45 Elena's own diagnosis journey — two and a half years to answers 11:32 Why she wouldn't trust chatbots with her health today 12:40 "Faithful hallucinations": the hidden risk in generative AI 15:04 Inside a causal-reasoning engine built without generative AI 17:32 What happens when clinicians outsource reasoning to chatbots 21:06 Redefining "normal": genetics and personalized lab ranges 27:08 Women's health data gaps and the DTC testing boom 28:13 Strengthening, not replacing, the doctor-patient relationship 31:42 Chatbot safety advice: what patients should never share 38:07 Clinical validation, agreement rates, and what's next Faces of Digital Health: Website: https://www.facesofdigitalhealth.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 Newsletter: https://fodh.substack.com The Agentic Patient series hub: https://www.facesofdigitalhealth.com/agentic-patient-blog #DigitalHealth #AIinHealthcare #PatientAdvocacy #WomensHealth #HealthTech #ClinicalAI #TheAgenticPatient
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  Will robots help us age at home? A historian who lives with one says not yet (Emily Kate Genatowski) 31.07.2026 37m

  The viral robot videos are choreography, not capability. A historian who has lived with a humanoid robot for a year explains what they still can't do. Emily Kate Genatowski is a historian and AI domestic robotics researcher who bought a humanoid robot, lived with it for over a year, and turned the experience into a TED talk. In this episode of Faces of Digital Health, she separates the demo-reel hype of 2026 from what home robots can actually deliver — and what that means for aging populations, caregiver shortages, and healthcare systems hoping robots will help people stay independent at home. She explains why companion robots and chore robots are still entirely separate machines, why her robot cannot get into a car, why retirees are often more enthusiastic about robots than younger workers — and why she believes we are living through a "digital Engels pause," where productivity rises faster than the mechanisms that distribute its benefits. Guest: Emily Kate Genatowski, historian and AI domestic robotics researcher Her TED talk: https://www.youtube.com/watch?v=rIg-Zt7bFHY What the conversation covers: - Humanoid robot hype in 2026 vs real-world capability - Living with a humanoid robot: logistics, frustration, and transport - Robots for elderly care and aging in place - Companion robots vs domestic chore robots — why they're separate devices - The "digital Engels pause": AI productivity without shared gains - US, China, and EU approaches to AI and robotics regulation - Emotional attachment to robots and robot design - Dual-use risks: humanoid robots and drones in warfare - "One soul, many bodies": the future architecture of home robots CHAPTERS CHAPTERS: 00:00 Intro 02:25 Welcome: a historian who lives with a humanoid robot 03:40 2026 robot hype: why the viral videos are choreography 05:45 Why buy a robot? How the year-long experiment began 07:28 From board games to policy: what the project became 08:57 Robots for aging in place — and who's actually optimistic 09:53 Companion robots vs chore robots: two separate machines 13:55 The digital Engels pause: productivity without shared gains 20:09 US, China, Europe: three regulatory cultures for AI and robotics 25:55 Why the robot travels in a box — and can't get into a car 29:58 Robot guilt: emotional attachment without eyes 33:14 Policy, not technology, as the bottleneck for elderly care robots 35:02 Dual use: drones, warfare, and where robotics could go wrong 37:25 One soul, many bodies: the bifurcated future of home robots FOLLOW FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #DigitalHealth #Robotics #HumanoidRobots #AgingInPlace #HealthTech #AI
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  Data challenges with AI: Omissions, bloated problem lists and unnecessary token burn 22.07.2026 39m

  Hallucination is not the biggest risk in clinical AI. Omission is — and it is far harder to detect. John Laursen, SVP at IMO Health, has spent his career on the layer of healthcare AI that gets the least attention: clinical terminology and the semantic data infrastructure underneath every model deployed in a hospital. IMO Health's terminology has been built and curated since 1994 and now sits behind roughly 12 billion terminology search transactions a year across US provider organisations and every major EHR. In this interview with Tjaša Zajc, Laursen makes the case that structured data was necessary but is no longer sufficient. AI reasoning across a thirty-year patient chart needs semantic continuity — an understanding that clinical language recorded in the 1990s and language recorded today can mean the same thing. Without it, health systems are investing in models that cannot reliably interpret their own records. The conversation also covers what happens when ambient AI scribes get it wrong, why accumulated clinical data has become a computational cost rather than an asset, and why clinician trust is the constraint that determines how fast clinical AI can move. Guest: John Laursen — Senior Vice President, IMO Health (Chicago, US) Host: Tjaša Zajc — Faces of Digital Health What the conversation covers: - Why omissions, not hallucinations, are the underrated risk in clinical AI - What a semantic layer does that structured data alone cannot - How clinical terminology maps to SNOMED CT and ICD-10 — and why those code sets were built for different purposes - Ambient AI scribes: what happens when a model mishears or over-infers a diagnosis - The billing and clinical consequences of an error entering the patient record - Why problem lists hundreds of entries long now cost money in token burn - Patient-generated and AI-generated content entering the EHR, and why health systems resist it - Translating lay language into clinical terminology without losing specificity - Ambient documentation, billing intensity and friction with payers - How data quality expectations differ between the US, the NHS, the Gulf states and Singapore - Who governs clinical data as coding complexity increases - Why AI performance breaks down on rare disease and the difficult 20% of cases - Knowledge graphs as a grounding source for clinical AI models - What health systems should require from AI vendors before clinical deployment Chapters: 02:20 Why the data layer decides what clinical AI can do 03:27 Inside IMO Health: 12 billion terminology searches a year 05:36 Keeping terminology current: SNOMED, ICD-10 and clinical governance 07:35 The semantic bridge: why structured data alone is not enough 10:17 Patient language versus clinical language in the record 12:23 When an ambient scribe mishears: clinical and billing consequences 14:53 Omissions, bloated problem lists and unnecessary token burn 19:12 Outside the US: the NHS, the Gulf, Singapore and coding complexity 20:46 Who governs clinical data as complexity increases 23:35 Patient-side AI recorders and resistance to external data 26:08 Ambient documentation, billing intensity and payer friction 29:21 The last 20%: rare disease, model limits and AI governance 33:38 Grounding, clinician trust and the cost of misfiring Faces of Digital Health: Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 LinkedIn: https://www.linkedin.com/company/faces-of-digital-health #digitalhealth #healthcareAI #clinicalinformatics #EHR #ambientAI #interoperability #healthdata #SNOMED #healthIT #medicalcoding
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  Who Fills The Gap After OpenEvidence Left Europe (Philippe Habets, EvidenceHunt) 17.07.2026 43m

  OpenEvidence didn't leave Europe because of regulation alone — its ad-and-data business model never fit the European market. When OpenEvidence, the $12B clinical AI search platform used daily by over 40% of US physicians, withdrew from the EU and UK in April 2026 citing the EU AI Act, European clinicians lost a tool many had quietly adopted. In this episode, Philippe Habets — physician-scientist and CEO of Amsterdam-based EvidenceHunt — argues the story is as much about business models as regulation: ad-funded clinical search and selling clinician search behaviour to pharma don't transfer to Europe, where clinicians distrust anything that looks commercial. We also examine what AI evidence search is measurably doing inside hospitals: more uniform knowledge across teams, fewer junior-to-senior consultations, faster decisions — and the open question of whether that convergence improves care or narrows clinical thinking. Guest: Philippe Habets, MD PhD, CEO & co-founder, EvidenceHunt (Amsterdam) What the conversation covers: - Why OpenEvidence left Europe: EU AI Act vs the ad-based and data-selling business model - What hospitals did after OpenEvidence's exit — governance, procurement, shadow AI use - How AI literature search changes clinical decision making and medical hierarchies - Automation bias, tunnel vision and who is liable when AI is wrong - Guardrails in practice: PII stripping, refusing clinical advice, reformulating case questions into research questions - Why LLM answers differ between tools — and the omission problem in complex patients - Living guidelines: automating systematic literature reviews and guideline updates (some protocols are 17 years old) - Should patients have access to the same evidence tools as clinicians? - EvidenceHunt vs OpenEvidence: data sources, GDPR, medical device regulation - What won't change in healthcare AI in the next three years Previous episode with Philippe Habets (2023): https://www.youtube.com/watch?v=F8tC0B4NvpM CHAPTERS 00:00 Introduction 03:11 OpenEvidence leaves Europe: what it meant for a European competitor 04:31 No user spike — but hospitals started asking questions 06:54 What EvidenceHunt is: from PubMed frustration to systematic reviews 11:35 How clinicians actually adopt AI evidence tools 13:46 Uniform knowledge, fewer senior consultations: measured effects on clinical thinking 16:24 Tunnel vision, automation bias and the liability question 18:04 Guardrails in practice: PII stripping and refusing clinical advice 20:31 The omission problem: evidence is group statistics, patients are N of 1 23:26 The real reason OpenEvidence left: ads, data-selling and European distrust 29:03 Should patients have the same evidence tools as clinicians? 31:51 Why disclaimers aren't enough — safeguards must be enforced in the product 33:43 Living guidelines: automating updates for protocols up to 17 years old 40:00 The biggest product challenge: too many features, one clean interface 41:40 What won't change in healthcare AI in the next three years FACES OF DIGITAL HEALTH Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 #digitalhealth #healthcareAI #OpenEvidence #EUAIAct #clinicaldecisionsupport #evidencebasedmedicine #healthtech
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  The AI Model Race Is Over. The Data Race in Healthcare Is Just Starting (Robert Tovornik, Better) 14.07.2026 34m

  AI models are "eager to please" — and in healthcare, that's a liability. So what should LLMs never be allowed to do in clinical software? Three years after GPT-3 reached the public, frontier models have largely converged in capability. In this episode, Robert Tovornik, Innovation Lead at Better — the healthcare IT company building on openEHR — explains why the real differentiator in healthcare AI is no longer the model but the data layer underneath it. He makes the case for keeping clinical coding and terminology in deterministic systems, confining LLMs to retrieval and orchestration, and validating AI the way you'd come to trust a colleague: through experience, not certification. Guest: Robert Tovornik, Innovation Lead, Better What the conversation covers: - Why frontier LLMs are converging — and why context now matters more than model capability - What AI should never do in clinical software: inference vs retrieval - Why ICD-10 and SNOMED coding should stay in deterministic systems, not ChatGPT - How to validate non-deterministic AI systems when unit tests no longer work - Automation bias: what happens when users stop checking AI outputs - Conversational EHRs — solving the "missing button" problem in clinical interfaces - Vibe coding vs regulated clinical software: why one iterates in hours and the other in years - An ambient AI scribe built in two weeks — deployed in India, stalled in Europe - EU AI Act, data residency laws, and the cost of compliance - Digital twins, ambient AI, and what hospitals should invest in before deploying AI Faces of Digital Health explores how healthcare systems around the world adopt digital technologies and AI. 🔗 Website: https://www.facesofdigitalhealth.com 🎧 Spotify: https://open.spotify.com/show/4cElKJHrauyP6QJQaCkvdY 🎧 Apple Podcasts: https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 📰 Newsletter: https://fodh.substack.com 💼 LinkedIn: https://www.linkedin.com/company/faces-of-digital-health #healthcareAI #openEHR #digitalhealth #healthIT #EHR #clinicalAI #healthcareinnovation 02:20 Three years of GPT: from model capability back to data and context 04:26 How AI changed software development inside an openEHR vendor 06:13 Clients now arrive with AI-informed (and misinformed) requirements 09:05 Why clinical coding belongs in deterministic systems, not ChatGPT 11:27 "Eager to please": why LLMs shouldn't be trusted with inference 14:03 Validating non-deterministic AI when unit tests no longer work 16:50 How do you trust AI? The same way you trust a colleague 18:03 Regulation, compliance costs, and the automation bias problem 20:09 Conversational EHRs and the missing-button problem 23:02 Vibe coding vs iterating regulated clinical software 25:23 Users are building AI experience faster than health systems 27:50 An ambient scribe built in two weeks — adopted in India, stalled in Europe 29:16 Data quality as the differentiator between good and bad AI systems 31:10 Ambient AI, operation prep, and the digital twin horizon
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  Agentic Patient 7: How to Use AI as a Caregiver — Without Letting It Diagnose | Pratik Desai 19.06.2026 46m

  AI couldn't cure his mother's stage 4 cancer. It caught three near-fatal errors, found a same-day appointment, and helped her leave on her own terms. When Pratik Desai's mother was diagnosed with stage four duodenal adenocarcinoma — a rare cancer with roughly 3,000 US cases a year — she was nearly discharged without an oncology appointment. Over the next 76 days, Desai used AI at her bedside, from 5am to 10pm, to understand each report, prepare for every appointment, and push a stretched health system to move at the pace her diagnosis demanded. This is a frank account of where AI helped, where it didn't, and the line he refuses to cross. This is a 1:1 interview in The Agentic Patient — a Faces of Digital Health series on how patients and caregivers actually use AI: which tools, which prompts, and which guardrails. GUEST Pratik Desai — New Jersey-based AI practitioner; caregiver and builder of a free, local AI tool for patients HOST Tjaša Zajc — Founder & host, Faces of Digital Health / The Agentic Patient WHAT THE CONVERSATION COVERS - Using AI to interpret a biopsy report and push for a same-day "stat" CT scan - Why AI and the doctors agreed on the care — and clashed on the speed - Finding a same-day oncology appointment through an AI-assisted network search - An error-riddled CT report the AI refused to read — and what it did to trust - Running three Claude "personas" as built-in second and third opinions - A local, open-source AI tool that keeps medical data off the cloud - How to prompt as a patient or caregiver: awareness, knowledge, advocacy — not diagnosis - Where AI failed him: prognosis, and the rule he broke under pressure - Defining quality of life when the outcome is already known CHAPTERS 0:00 How patients use AI — and the guardrails 1:20 Day one: a healthy mother, a diagnosis no one would name 3:34 The first prompt, and pushing for a stat CT scan 7:43 Using AI in the open: agreement on care, friction on speed 9:35 The counterfactual: 76 days with AI at the bedside 12:40 Finding a same-day appointment through a network search 13:40 The CT report the AI refused to read 15:50 When trust erodes: good faith, not competence 18:41 Why switching hospitals wasn't an option 21:54 Defining quality of life: her three goals 28:27 Three Claude personas, and a local private tool 35:12 How to prompt: awareness, knowledge, advocacy — not diagnosis 37:54 Where AI fell short, and the closing asks THE AGENTIC PATIENT SERIES New to the series? Start here → [PASTE PREVIOUS AGENTIC PATIENT EPISODE LINK] All episodes → https://www.facesofdigitalhealth.com/agentic-patient-blog MORE FROM FACES OF DIGITAL HEALTH 🌐 Website: https://www.facesofdigitalhealth.com 📨 Newsletter: https://fodh.substack.com 🎙 Podcast (Apple): https://podcasts.apple.com/gb/podcast/faces-of-digital-health/id1194284040 💼 LinkedIn: https://www.linkedin.com/company/faces-of-digital-health Pratik's tool Regana: https://github.com/RaganaCorp/openhealth-prototype-1 #DigitalHealth #HealthAI #AgenticPatient #PatientAdvocacy #AIinHealthcare #CancerCare #Caregiving #FacesOfDigitalHealth
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  We're Overestimating Medical AI — and Underestimating the Harm (Jessica Morley, Yale) 09.06.2026 58m

  AI ethicist Jess Morley: these chatbots are giving medical advice — so regulate them as medical devices. Part of The Agentic Patient, a Faces of Digital Health series on how patients actually use AI — which tools, which prompts, which safeguards. In this episode, host Tjaša Zajc sits down with Dr Jess Morley, Associate Research Scientist at the Yale Digital Ethics Center and a former AI subject-matter expert at the UK Department of Health and Social Care, for a clear-eyed account of where health AI is going wrong — and how to use it well anyway. Morley argues we systematically overestimate what these tools can do and underestimate the harm. She makes the case for "skeptical optimism," explains why bioethics principles built for one-to-one care break down against many-to-many AI harms, and reframes ambient scribes as inference engines rather than transcription services — with real consequences for coding, billing and patient records. Then she gets practical: the guardrails, prompts and habits patients (and clinicians) can use today. Guest: Dr Jessica Morley — Associate Research Scientist, Yale Digital Ethics Center; formerly UK Department of Health and Social Care and the Bennett Institute, University of Oxford. What the conversation covers: - Why "skeptically optimistic" is the honest position on health AI - AI adoption as "a hammer looking for nails" — and what needs-led design would look like instead - OpenEvidence, EU rules and the question of regulatory capture - The DeepMind–Royal Free case and why law alone isn't enough - Beneficence, non-maleficence, autonomy, justice — and where they fail for AI - Ambient AI scribes, miscoding, billing inflation and phantom tests - Paid vs free models and the widening access gap - The "ask why" rule and knowing when to walk away from a chatbot - Red-teaming your own assumptions and playing models off each other - Building a personal "harness" with skills so AI works from your history - The last-mile problem and the case for regulating LLMs as medical devices - Whether AI is narrowing how clinicians think Chapters: 02:50 — Intro: The Agentic Patient and the case for skeptical optimism 05:52 — "A hammer looking for nails": adoption pressure without a plan 07:25 — OpenEvidence, EU rules and regulatory capture 09:42 — The DeepMind–Royal Free lesson: why law needs ethics 13:29 — The bioethics principles and what they were built to do 19:40 — Autonomy, consent and the ambient-scribe problem 21:49 — Scribes as inference engines: miscoding, fraud and phantom tests 29:06 — Paid vs free models and the access gap 33:25 — Using AI safely: the "ask why" rule 37:38 — Knowing when to walk away: engagement design and degradation 44:58 — Red-teaming and playing models off each other 49:00 — Harnesses and skills: making the model work for you 51:38 — The last-mile problem and regulating AI as a medical device 58:00 — Does AI narrow the clinician's mind? The Agentic Patient series: https://www.facesofdigitalhealth.com/agentic-patient-blog Website: https://www.facesofdigitalhealth.com Newsletter: https://fodh.substack.com LinkedIn: https://www.linkedin.com/company/faces-of-digital-health
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  Healthcare AI Policy in 2026: Only 7 of 38 OECD Countries Have an AI Strategy 03.06.2026 13m

  98% of patients welcome AI in their care — and still want a human in charge. That tension ran through the OECD and Spanish Ministry of Health conference on scaling AI in health (Madrid, late May 2026), and it frames this episode of Faces of Digital Health. Out of 38 OECD countries, only seven have a formal AI strategy and just over a tenth run workforce upskilling programmes — the ambition is outrunning the institutions meant to govern it. Host Tjaša Zajc brings together voices from across the conference to ask what actually has to change: regulation, trust, who gets a seat at the table, and the parts of the agenda nobody is funding. Featuring: - Eric Sutherland — Senior Economist, OECD - Aferdita Bytyqi — Executive Director & Founding Partner, Digital Transformations for Health Lab (DTH-Lab) - Erza Selmani — Research Fellow, DTH-Lab - Valentina Strammiello — Executive Director, European Patients Forum (EPF) - Dr Ricardo Baptista Leite — CEO, HealthAI (the Global Agency for Responsible AI in Health) - Dr Persephone Doupi — Senior Medical Officer, Finnish Institute for Health and Welfare; President, European Federation for Medical Informatics (EFMI) What the conversation covers: - Why trust — not capability — is the binding constraint on health AI adoption - The OECD readiness gap: AI strategies, HTA frameworks and workforce upskilling - How patients really feel about AI: consent forms, transparency, and keeping clinicians central - Why youth health and wellbeing keep getting left out of AI governance frameworks - Five recommendations to make the EU AI Act work for health and competitiveness - Coordinating the EU AI Act, MDR/IVDR and the European Health Data Space - Health technology assessment and reimbursement as the real barriers to scale - AI literacy and prevention: the most underweighted lever in the room Chapters: 0:10 — Welcome: AI in Health & the 2026 OECD Conference in Madrid 0:25 — Key Stats: Only 7 of 38 OECD Countries Have a Formal AI Strategy 2:10 — Eric Sutherland (OECD): We're Not Using Data as Effectively as We Could 3:11 — Afrodita & Erza (DTH Lab): Youth Health Is Missing from AI Governance Frameworks 5:12 — Valentina Stramello (EPF): 98% of Patients Are Positive About AI, But Trust Requires Transparency 7:14 — Dr. Ricardo Baptista Leite (Health AI): 5 Recommendations to Fix EU AI Policy for Health 10:53 — Persephone Doupi (EFMI): We Must Prioritize AI Literacy and Shift Healthcare Toward Prevention — 🎧 Listen: https://www.facesofdigitalhealth.com 📩 Newsletter (incl. written OECD conference summary): https://fodh.substack.com 💼 LinkedIn:https://www.linkedin.com/company/12594967/ 🌐 Site: https://www.facesofdigitalhealth.com #DigitalHealth #HealthAI #AIinHealthcare #HealthPolicy #EUAIAct #EHDS #ResponsibleAI #PatientVoice #HealthTechAssessment #HealthTech
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  Doctors are using ChatGPT in clinic and not all care about privacy (Health.Tech 2026) 26.05.2026 42m

  Doctors are using ChatGPT in clinic right now — and some of them don't care about privacy. Three operators on what that means for healthcare AI. Recorded live at health.tech in Basel, this panel from Faces of Digital Health unpacks the convergence reshaping clinical software: ambient AI scribes, agentic AI in healthcare, on-device LLMs, and the regulatory drag (MDR, EU AI Act, EHDS) that is widening the gap between what clinicians actually use and what hospitals are allowed to buy. Host Tjaša Zajc is joined by: Jonathan Bringas — CEO & Founder, Lapsi Health (Kaiku: FDA-cleared AI stethoscope, ambient scribe and clinical assistant in one device) Blaž Triglav — CEO, Mediately (drug information platform, 1M+ HCPs across Europe) Amanda Herbrand — Clinical data modelling consultant, formerly University Hospital Basel What the conversation covers: — Why EHR data fragmentation is the precondition AI hasn't solved — Shadow AI: why clinicians trust ChatGPT more than enterprise tools (and the agency hypothesis behind it) — The convergence of stethoscopes, scribes, drug information and decision support into one workflow layer — ROI in healthcare AI: financial, time, clinical accuracy — and Herbrand's fourth dimension, user satisfaction — "Doctors were the original vibe coders": the 2,000 Excel spreadsheets running European hospitals — Why FDA-cleared beats MDR in 2026 sales cycles, and what Chile's regulatory minimalism tells us — The asymmetry that will break European medtech: applicants using AI to build, regulators forbidden from using AI to assess — On-device AI, ambient computing, AGI in clinical workflows — and the de-skilling risk no one wants to discuss ⏱ Chapters 00:00 — Opening: AI agents, vibe coding, and what doctors actually want 01:30 — Data fragmentation: the precondition AI hasn't solved (Amanda Herbrand) 02:30 — Keiku: collapsing stethoscope, scribe and assistant into one device 05:15 — The convergence reshaping healthcare AI — and the shadow AI in clinic 07:30 — Why doctors trust ChatGPT more than enterprise tools: the agency hypothesis 10:30 — ROI: financial, time, clinical accuracy — and Herbrand's fourth dimension 15:30 — Choosing solutions: modular requirements and FDA-cleared moats 19:30 — EHDS and the missing connector in European standardisation 21:00 — "Doctors were the original vibe coders": the 2,000 spreadsheet problem 24:30 — The two-speed world: regulated medicine vs the Wild West 28:00 — Why Chile's regulatory minimalism beats Europe's MDR 30:30 — Agentic AI vs regulators: the asymmetry that will break European medtech 33:30 — On-device AI, AGI, and the deskilling no one wants to discuss 🎧 View the video podcast: https://www.youtube.com/watch?v=fciFwMmIfRc&t=174s 📩 Newsletter: https://fodh.substack.com 🔗 LinkedIn:   / dashboard   🌐 facesofdigitalhealth.com #HealthcareAI #DigitalHealth #AmbientAI #AgenticAI #ClinicalAI #EHR #EHDS #MedTech #HealthTech