EU Introduces New Framework for Health Tech Assessments

In the fast paced world of health AI, this PHTI report may already be an oldie, but a goodie nonetheless, and worthy of reposting. As someone who's been in the innovation field in clinical research and healthcare for a hot minute (13 years), I think a lot about the adoption journey for new tech or processes. Ambient Digital Scribes serve as a fascinating case-study on adoption. For something new to be adopted in short order, you need two things: (1) A problem that inflicts palpable pain on the adopting individual. Not the organization. Not society. On the individual. (2) A solution that brings the individual immediate and palpable relief. It need not be evidence-based (i.e., studied robustly and published in a peer-reviewed journal). It works because I feel it worked. And so goes the case for Ambient Digital Scribes: keeping up with the EMR and the note-writing treadmill inflicted palpable pain on clinicians. ADS offered immediate relief: a cleared “in bin” at the end of the day, faster and easier notetaking, and a listening ear in the exam room to ensure nothing was missed. Clinics and health systems felt the acute pain of provider attrition and understaffing; ADS was a small thing that made clinicians happier and therefore more willing to return to work the next day. The message to the innovation community is this: understand what your customers’ most painful problem is; pursue fast acting solutions. And adoption will follow. On the other hand, focus on lofty problems that, whether solved or unsolved, do not impact the individual user; address problems with lofty solutions that may only bring relief in the long term, for the next generation, or cause other unintended consequences, and the path to adoption will be much longer and harder. https://lnkd.in/gyxB-SwE

AI is set to reshape healthcare in 2025—but clinician burnout and patient trust gaps are blocking true transformation. 👇 The latest FHI report exposes urgent areas healthcare leaders must address before unlocking real value: - - In half of surveyed countries, specialist wait times exceed 2 months; in Canada and Spain, it’s 4+ months. - - 31% of cardiac patients are hospitalized before seeing a specialist—a clear signal for process redesign. - - 75% of frontline clinicians lose clinical time to data overload—costing organizations nearly 3 weeks per clinician, per year. - - 46% of professionals fear missed early diagnosis opportunities without effective AI integration. - - A third of patients experience worsening health from delays; a quarter end up hospitalized. AI can drive breakthrough efficiency and outcomes—but only if deployed with purpose. We can’t just “add AI” and expect instant change. Healthcare executives must focus on human-centric integration, address workflow and data pain points, and actively build trust within care teams and patient populations. The path forward: unlock AI’s true strategic value by fixing foundational issues first. Those who lead this charge will shape the future of intelligent health systems. ---

A great idea may not always be the best Investment. Healthcare innovation requires more than creativity; it demands strategic evaluation of value, scalability, and long-term impact. During a recent presentation by Todd Couts in my Health System and Health IT Applied Analysis Immersion class, I learned about Precision Behavioral Health models that leverage digital therapeutics and AI-driven analytics to personalize care. Patients are referred and guided based on their results, receiving targeted programs designed to support their behavioral health journey. While this model can expand access and reduce costs, it also highlights some critical challenges. Digital therapeutics may not always be FDA-approved, behavioral health risk is often carved out, and lower unit costs can sometimes lead to overutilization. This made me reflect on how healthcare IT and AI can support more integrated, data-driven solutions like collaborative care models, which consider both medical and behavioral risks at the provider level. When thoughtfully applied, technology can move beyond innovation for innovation’s sake and truly enhance care delivery. It’s fascinating to see how data, ethics, and innovation intersect in shaping the future of healthcare. #HealthcareInnovation #HealthIT #AIinHealthcare #BehavioralHealth #DigitalTherapeutics #CollaborativeCare

Explore how AI is driving measurable improvements in healthcare efficiency, patient care, drug discovery, and population health analytics, backed by NHS trial results and emerging innovations. #AIHealth #AIDiagnostics #Healthcare #HealthTech

The views expressed here are my own and do not reflect those of my employer. This post is meant for information and professional commentary. Healthcare policy in the United States has long struggled with cost, access, and quality, but AI offers a path forward. While opinions on initiatives by HHS may vary, innovation is urgently needed to address systemic inefficiencies. Here are three ways on how AI can improve healthcare: 1. Predictive Resource Allocation: AI forecasts patient needs to optimize staffing, beds, and supplies, which reduces waste and improves access. 2. Personalized Care Plans: Machine learning tailors treatments to patients' genetic and medical histories, which minimizes unnecessary procedures and hospitalizations. 3. Policy Decision Support: AI models predict the impact of policies on costs, and assess their effectiveness in supporting evidence-based decision-making. Efforts to incorporate AI into healthcare policy, such as those by the current administration, represent promising steps toward a more responsive, sustainable, and patient-centered system.

At the 𝐉𝐀𝐌𝐀 𝟐𝟎𝟐𝟓 𝐒𝐮𝐦𝐦𝐢𝐭 𝐨𝐧 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐢𝐧 𝐇𝐞𝐚𝐥𝐭𝐡 𝐚𝐧𝐝 𝐇𝐞𝐚𝐥𝐭𝐡 𝐂𝐚𝐫𝐞, leaders from medicine, technology, and policy explored how to change how care is delivered, documented, and experienced across the health system, while making that change both responsible and equitable.   More than 𝟏,𝟐𝟎𝟎 𝐀𝐈 𝐜𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐭𝐨𝐨𝐥𝐬 𝐡𝐚𝐯𝐞 𝐅𝐃𝐀 𝐜𝐥𝐞𝐚𝐫𝐚𝐧𝐜𝐞. Nearly 𝟗𝟎% 𝐨𝐟 𝐔.𝐒. 𝐡𝐞𝐚𝐥𝐭𝐡 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 already use AI for imaging, workflow, or documentation. Yet only a small fraction have been evaluated for their real impact on patient outcomes.   The Summit identified four priorities that every healthcare organization should pay attention to: • 𝐄𝐧𝐠𝐚𝐠𝐞 𝐚𝐥𝐥 𝐬𝐭𝐚𝐤𝐞𝐡𝐨𝐥𝐝𝐞𝐫𝐬 𝐞𝐚𝐫𝐥y – clinicians, patients, developers, and regulators. • 𝐂𝐫𝐞𝐚𝐭𝐞 𝐦𝐞𝐚𝐧𝐢𝐧𝐠𝐟𝐮𝐥 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 𝐦𝐞𝐭𝐡𝐨𝐝𝐬 – measure safety, effectiveness, and real-world value. • 𝐈𝐧𝐯𝐞𝐬𝐭 𝐢𝐧 𝐬𝐡𝐚𝐫𝐞𝐝 𝐝𝐚𝐭𝐚 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 – enable consistent learning across care settings. • 𝐀𝐥𝐢𝐠𝐧 𝐢𝐧𝐜𝐞𝐧𝐭𝐢𝐯𝐞𝐬 – reward innovation that improves health, not just efficiency.   AI’s future in healthcare depends on more than technical progress. It depends on trust, collaboration, and transparency.   Read the original article in JAMA: https://lnkd.in/dtvcbPan   The next step is not to adopt more AI tools, but to make sure they truly work for patients, clinicians, and communities.   👉 Follow xCures Wake up to Clinical Clarity Read our LinkedIn Newsletter:  https://lnkd.in/dnNJV2ti https://xcures.com/ 👀

Explore the UK’s strategic digital healthcare initiatives, including NHS Online virtual hospital and AI-ready health data platforms, shaping the future of AI in healthcare. #AIHealth #AIDiagnostics #Healthcare #HealthTech

3 Key Themes across the European HealthTech sector this week: 1) AI and Data-Driven Health: There is continued focus on leveraging AI in healthcare, including discussions at the ongoing BioTechX Europe 2025 conference (October 6-8 in Basel) which features tracks on AI in drug development, clinical trials and data analytics. 2) European Policy and Funding: The European Commission is pushing its digital ambitions, with an amendment to the Digital Europe (DIGITAL) Work Programme 2025-2027 announced (Oct 6th), which will now contribute to the AI Gigafactories initiative to accelerate the development of European AI models. 3) Health System Modernisation (EPRs): Numerous NHS Trusts in the UK, such as East Suffolk and North Essex NHS FT, and Queen Victoria Hospital, are continuing with their rollout and implementation of Electronic Patient Record (EPR) systems. What Key Themes are you seeing this week?