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Nelson Advisors referenced in a Copenhagen Business School paper ‘Health Analytics in Business Research’.Word Cloud of Health Analytics in Business ResearchThe above word cloud illustrates that topics in health analytics primarily encompass patients and healthcare delivery organizations. Scholars in other fields have proposed classification schemes from different research perspectives. As Dr. Niti Pall, a visionary global senior clinical leader, pointed out in her lessons (7), “The focus is on patient-facing technologies. Others are professional-facing and organization-facing technologies depending on their primary user and value in enhancing individual patient care or improving care systems. The electronic health record spans the entire system and serves as the foundation for many other applications”.Source: <a href="https://research-api.cbs.dk/ws/portalfiles/portal/102251411/quanchen_liu_et_al_health_analytics_in_business_research_acceptedversion.pdf" data-mce-href="https://research-api.cbs.dk/ws/portalfiles/portal/102251411/quanchen_liu_et_al_health_analytics_in_business_research_acceptedversion.pdf">https://research-api.cbs.dk/ws/portalfiles/portal/102251411/quanchen_liu_et_al_health_analytics_in_business_research_acceptedversion.pdf</a>(7) URL: <a href="https://www.healthcare.digital/single-post/2019/02/26/seven-key-lessons-learnt-from-digital-transformation-by-healthcare-providers-around-the-w">https://www.healthcare.digital/single-post/2019/02/26/seven-key-lessons-learnt-from-digital-transformation-by-healthcare-providers-around-the-w</a>

Nelson Advisors referenced in a Copenhagen Business School paper ‘Health Analytics in Business Research’

Nelson Advisors referenced in a Cornell University paper ‘The Rise of Small Language Models in Healthcare: A Comprehensive Survey’1. BackgroundThe global small language model (SLM) market is projected to reach USD 29.64 billion by 2032, with the healthcare industry anticipated to experience the fastest compound annual growth rate (CAGR) of 18.31% from 2024 to 20322. This growth is driven by the growing adoption of SLM in medical diagnosis, patient care, and administrative processes. The use of SLM in analyzing extensive medical literature and patient data provides clinicians with evidence-based interpretations to support clinical decision making (3)Source: <a href="https://arxiv.org/html/2504.17119v1">https://arxiv.org/html/2504.17119v1</a>(3) <a href="https://www.healthcare.digital/single-post/small-language-models-slms-have-the-potential-to-revolutionise-healthcare-ai-in-addition-to-llms">https://www.healthcare.digital/single-post/small-language-models-slms-have-the-potential-to-revolutionise-healthcare-ai-in-addition-to-llms</a>AbstractDespite substantial progress in healthcare applications driven by large language models (LLMs), growing concerns around data privacy, and limited resources; the small language models (SLMs) offer a scalable and clinically viable solution for efficient performance in resource-constrained environments for next-generation healthcare informatics. Our comprehensive survey presents a taxonomic framework to identify and categorize them for healthcare professionals and informaticians. The timeline of healthcare SLM contributions establishes a foundational framework for analyzing models across three dimensions: NLP tasks, stakeholder roles, and the continuum of care. We present a taxonomic framework to identify the architectural foundations for building models from scratch; adapting SLMs to clinical precision through prompting, instruction fine-tuning, and reasoning; and accessibility and sustainability through compression techniques. Our primary objective is to offer a comprehensive survey for healthcare professionals, introducing recent innovations in model optimization and equipping them with curated resources to support future research and development in the field. Aiming to showcase the groundbreaking advancements in SLMs for healthcare, we present a comprehensive compilation of experimental results across widely studied NLP tasks in healthcare to highlight the transformative potential of SLMs in healthcare. The updated repository is available at Github1.

Nelson Advisors referenced in a Cornell University paper ‘The Rise of Small Language Models in Healthcare: A Comprehensive Survey’

Nelson Advisors referenced in the Official Journal of the European Union paper ‘Opinion of the European Economic and Social Committee: AI, Big Data and rare diseases’.Opinion of the European Economic and Social CommitteeAI, Big Data and rare diseases(exploratory opinion requested by the Danish Presidency of the Council of the EU)(C/2026/24)4. &nbsp; Key challenges and risks&nbsp; &nbsp;&nbsp; 4.1. Despite its promise, the application of AI and Big Data in rare disease research raises serious concerns about control by humans, data quality, data privacy, algorithmic bias, affordability and accessibility. An overreliance on AI may lead us to neglect a holistic approach to treatment strategies, and ethical considerations. AI may lead to rational decisions that are inappropriate for the patient’s situation as not all parameters are included in the AI models. The final decision must remain with the healthcare and medical profession. &nbsp; &nbsp;&nbsp; 4.2. Ensuring equal access to AI-driven healthcare innovations: &nbsp; &nbsp;&nbsp; 4.2.1. The EU Pharmaceutical Strategy for Europe emphasises the need to foster innovation in rare disease treatments and AI-driven drug discovery, especially for rare diseases that lack commercial incentives for research. These treatments are excessively priced and weigh heavily on health budgets. &nbsp; &nbsp;&nbsp; 4.2.2. Rare disease data in Europe is scarce and fragmented, limiting large-scale AI analysis. Without standardised high-quality data, AI may only benefit well-represented diseases or wealthy populations. Access to AI tools is uneven, with rural-urban divides, digital health infrastructure gaps between countries and high treatment costs deepening inequalities. Ensuring access to quality data is essential for effective AI-driven treatments. &nbsp; &nbsp;&nbsp; 4.3. Bias and gender disparities in AI models: &nbsp; &nbsp;&nbsp; 4.3.1. Women are disproportionately affected by autoimmune and chronic rare diseases and wait an average of four years longer to receive a diagnosis for the same disease as men (18). Most preclinical studies use data from European-descent males (19), leading AI models trained on these datasets to misdiagnose women more frequently (20). An unfortunate trend in abusing women’s health data is also seen (21). AI-based health monitoring apps often track and store sensitive reproductive health data, raising privacy concerns (22).Source: <a href="https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=OJ:C_202600024" data-mce-href="https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=OJ:C_202600024">https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=OJ:C_202600024</a>(20) &nbsp; Are AI tools failing women’s health?.<a href="https://www.healthcare.digital/single-post/are-ai-tools-failing-women-s-health">https://www.healthcare.digital/single-post/are-ai-tools-failing-women-s-health</a>

Nelson Advisors referenced in the Official Journal of the European Union paper ‘Opinion of the European Economic and Social Committee: AI, Big Data and rare diseases’

OpenClaw is being used as an agent framework on top of OpenAI’s models to automate both clinical and operational workflows, with the earliest real deployments clustering around documentation, triage, radiology-driven care pathways, and hospital flow.What OpenClaw actually is OpenClaw (formerly Moltbot/Clawdbot) is an open-source, agentic orchestration layer that plugs GPT‑5.x–class models into messaging channels and hospital systems so that AI can take actions, not just answer prompts.​ It provides a Gateway for WhatsApp/Signal/Slack-style interfaces, an Agent reasoning core, a Skills layer for tools/EMR actions, and a scheduler (“Heartbeat Engine”) for proactive tasks.​First concrete healthcare use cases Early adopter sites and pilots in 2025–26 are using OpenClaw-style agents with OpenAI. models for four main classes of work.Ambient scribing and documentationED and outpatient: always‑on agents join consults (voice or chat), generate structured notes, code suggestions, and discharge summaries into the EMR. Vendors like Abridge/Ambience are doing this via OpenAI’s healthcare API; OpenClaw-like agents are the glue to run these 24/7 and push outputs into clinical systems.​ Asynchronous triage and care coordinationGateway integrations let patients or staff message an agent on WhatsApp/Slack; the agent triages symptoms, collects history, and routes to the right human or service.​ The same stack coordinates care teams, chasing consults, summarizing long message threads, and creating task lists for nurses and junior doctors. Radiology driven pathways (UK examples)Within NHS stroke and chest‑imaging networks, AI models identify 124 abnormalities on chest X‑ray and flag critical findings; OpenClaw-style agents then push alerts and structured summaries to on‑call clinicians.​ In stroke, agents watch for new CT/CTA reports overnight, surface suspected LVOs, and recommend transfer decisions to hyper‑acute centers.​ Hospital operations and discharge planningThe “Heartbeat Engine” runs scheduled jobs: scanning lab queues, bed status, and task backlogs to propose bed moves and discharge candidates before morning handover.​ The “Moltbook” concept is an agent‑only network where multiple OpenClaw agents negotiate beds, theater slots, and transport, then post a consolidated plan to human bed managers.​ Relationship to OpenAI’s own healthcare push OpenAI for Healthcare (Jan 2026) formalizes clinical‑grade access to GPT‑5.x (BAA/HIPAA, logging, guardrails), while OpenClaw supplies the agent layer around it. Real deployments combine the two: OpenAI models handle reasoning and language, OpenClaw handles long‑horizon orchestration, proactive monitoring, and multi‑system integration.Early “agentic” clinical reasoning use Beyond workflow automation, OpenAI’s o1/o1‑preview and later reasoning models are already being benchmarked on:Complex differential diagnosis and rare disease work‑ups Multimorbidity care planning (e.g., diabetes plus CV disease) Genomics and variant interpretation as a virtual consultant for MDTs Research is still pre‑regulatory, but these are the first serious “AI doctor” style uses feeding into agentic stacks like OpenClaw.To discuss how Nelson Advisors can help your HealthTech, MedTech, Health AI or Digital Health company, please email <a href="mailto:lloyd@nelsonadvisors.co.uk">lloyd@nelsonadvisors.co.uk</a>

First use cases of OpenClaw by OpenAI in healthcare

European HealthTech this week is dominated by EU‑level regulatory moves around MDR/IVDR and AI, plus a clear pivot of digital health from “experiments” to scaled implementation and validation funding.EU regulatory and policy moves The Commission has advanced a 2026 Health Package revising MDR/IVDR to ease bottlenecks: more predictable conformity assessment, codified “Helsinki procedure” for borderline products, and risk‑based (rather than fixed 5‑year) certificate validity.​ Cybersecurity is being hard‑wired into MDR/IVDR, with obligations to report actively exploited vulnerabilities and severe cyber incidents in medical devices within 30 days, aligning with broader EU cyber rules.​ Digitalisation provisions will allow EU declarations of conformity and some IFUs in digital‑only form and require fully electronic submissions into EUDAMED; four core EUDAMED modules went live in late 2025, triggering a transition to mandatory use from May 2026.​ EU machinery for joint clinical assessments under the HTA Regulation is now live, with more MedTech expected to enter the pipeline during 2026, raising the bar for clinical evidence in market access dossiers.​ AI Act, SaMD and medical AI Work is ongoing to integrate AI Act “high‑risk” obligations with MDR/IVDR so high‑risk medical AI can go through a single sectoral conformity route, avoiding duplicated certification; core AI Act obligations are expected to apply from around August 2026.​ Recent analysis and events (e.g. EUCROF’s focus on SaMD and AI) highlight that MDR and the upcoming AI Act are reshaping compliance and commercialization strategies for software as a medical device, including real‑world examples such as Healthentia. Industry and policy fora this week (e.g. “Masters of Digital 2026”, MWC/4YFN “AI in Healthcare: Hype or Hope?”) are centering on AI governance in care delivery and diagnostics rather than just technical capabilities. Market environment, exits and consolidation EU data show sustained pressure on MedTech innovation portfolios, with reduced pipelines, cancelled launches and some manufacturers exiting EU markets due to MDR/IVDR cost and complexity, which is pushing resource re‑allocation and go/no‑go decisions.​ Analysts expect consolidation driven by regulatory complexity, with larger hardware incumbents and big tech acquiring software/data innovators to secure “compliance moats” and data sovereignty under the evolving EU regulatory stack.​ At CES 2026, European AI‑driven MedTech companies were already positioning offerings for US reimbursement and institutional contracting, underlining continued internationalisation despite home‑market frictions.​ Funding, grants and validation capital Global Health EDCTP3 has opened 2026 calls with up to €147m across six topics (TB, LRTIs, HIV/co‑morbidities, climate‑linked infectious disease), explicitly supporting digital/clinical innovation and data‑/AI‑heavy platforms.​ Within the Horizon Europe 2026–27 work programme, a substantial part of a €14bn R&amp;I envelope is earmarked for health and digital technologies, reinforcing medium‑term grant support for AI, data and platform‑driven health innovation. EIT Health just launched its 2026 Innovation Validation Call, funding up to 50% of project budgets (max €850k) to accelerate clinical validation, regulatory approval and market launch for late‑stage digital, data and AI‑driven healthcare innovations.​ Ecosystem, infrastructure and events Analysis this week frames European digital health as entering a “proof through exits” phase, with investor focus shifting from round size to scalability, regulatory readiness and clear paths to liquidity. health.tech 2026 in Basel and European Digital HealthTech‑linked events are emphasizing implementation: deploying AI in workflows, prevention systems, and aligning with EHDS, SaMD/AI regulation, and procurement rules. There is renewed emphasis on EHR maturity and interoperability as prerequisites for scaling teleconsultations and virtual care; WHO experts underline that robust EHR infrastructure is essential for digital health service expansion.To discuss how Nelson Advisors can help your HealthTech, MedTech, Health AI or Digital Health company, please email <a href="mailto:lloyd@nelsonadvisors.co.uk" data-mce-href="mailto:lloyd@nelsonadvisors.co.uk">lloyd@nelsonadvisors.co.uk</a>&gt;&gt;&gt;&gt;European MedTech this week is centred on the EU “Health Package” (MDR/IVDR reset plus biotech/clinical trials tweaks), upcoming Commission discussions on devices, and a continued narrative of consolidation and “compliance‑driven” strategy.MDR/IVDR “regulatory reset” The Commission has proposed targeted amendments to MDR and IVDR to simplify requirements, reduce administrative burden and improve notified body predictability, responding to evidence of reduced pipelines, cancelled launches and exits from the EU market. Key elements include more proportionate, risk‑based rules (e.g. updated classification such as a refined Rule 11 for software), removal of fixed certificate validity in favour of validity limited only when risk justifies it, and priority review paths for breakthrough or orphan devices. Manufacturers would benefit from clearer rules on post‑certification changes, structured dialogue with notified bodies, digital Declarations of Conformity and eIFUs, and reduced PSUR frequency, with fee reductions and support measures for micro and small enterprises.​ Timelines and stakeholder input The legislative proposal is at EU co‑decision stage; it must be adopted by Parliament and Council and may be amended during the process.​ An eight‑week feedback window is open into mid‑March 2026 for stakeholders to comment on the MDR/IVDR changes, with submissions shared with EU legislators.​ In parallel, AI Act implementation work continues, with plans to allow high‑risk medical AI to use a single MDR/IVDR‑anchored conformity route rather than duplicative AI Act certification when obligations overlap.​ Innovation, safety and procurement agenda On 16 March 2026, the Commission will host a high‑level conference in Brussels on “Medical Devices: Innovation and Patient Safety,” covering predictability of conformity assessment, the role of expert panels in clinical evidence, and guidance for breakthrough technologies. New EU proposals are also set to reshape procurement for MedTech and diagnostics, which could materially affect pricing, value‑based criteria and access for both incumbents and innovators.​ The EU HTA Regulation machinery is now operational, and more MedTech is expected to enter joint clinical assessments in 2026, raising the evidentiary bar for pan‑EU market access.​ Market structure, M&amp;A and capital Analysts highlight ongoing pressure on MedTech innovation portfolios from MDR/IVDR‑driven costs and complexity, prompting portfolio pruning and re‑prioritisation of launches. A distinct “compliance‑driven M&amp;A” theme is emerging, with strategics acquiring targets partly to secure regulatory “compliance moats” and de‑risk EU market access, while PE pursues buy‑and‑build strategies in fragmented segments. Transatlantic capital flows remain strong, with US corporate and growth funds active in European robotics and AI‑driven MedTech, helping to bridge the historical Series B+ gap and allowing companies to scale further before exit. Internationalisation and AI‑driven MedTech European AI‑driven MedTech players are increasingly designing offerings around US reimbursement and institutional contracting, as showcased at CES 2026, reflecting a push to scale outside Europe while regulatory reforms work through at home. Upcoming European events (e.g. Athens Digital Health Week, European Digital HealthTech Conference) are being used as coordination points on EHDS implementation and SaMD/AI adoption in routine care, which directly impacts device‑plus‑software business models.To discuss how Nelson Advisors can help your HealthTech, MedTech, Health AI or Digital Health company, please email <a href="mailto:lloyd@nelsonadvisors.co.uk">lloyd@nelsonadvisors.co.uk</a>

This Week in European MedTech and HealthTech: 13th March 2026

UCL Global Business School for HealthThe UCL Global Business School for Health is the world's first business school dedicated to health. We unravel health challenges from a business perspective.Established in 2021, the UCL Global Business School for Health (GBSH) was created in response to an undeniable global truth: health systems must evolve. The pandemic highlighted the profound impact of health on society, exposing critical system flaws and the need for better management, innovation, and leadership.UCL GBSH’s one-of-a-kind offering of undergraduate, postgraduate and Executive Education courses address these issues head-on, providing management and business skills to students from across the world. From focusing on public health engagement to harnessing the power of technology and digitisation, we are preparing our students to lead health transformation globally.Health Executives in Residence Being leaders in their respective fields and industries, our Health Executives in Residence are not only here to help you reimagine healthcare for the future but are also here to ensure you graduate from the Global Business School for Health with experiences that mirror the real work of health. We believe that the interactions you have with our Health Executives in Residence will challenge and shape your aspirations and career paths.&nbsp;UCL Health Executives in Residence include a wide range of industry leaders and innovators including:Michael Allen - Partner and Head of Health &amp; Human Services, KPMGDr Dominique Allwood - Chief Executive, Imperial College Health PartnersMinal Bakhai - National Director of Primary Care and Community Transformation and Improvement, NHSDr Jonathan Broomberg - Group Deputy CEO, VitalityChris Gibbons - Director of Digital Health &amp; Technology Transformation, KPMGDr Joanne Hackett - Vice President Health System Services, IQVIAAndreas Haimböck-Tichy - Managing Director, Healthcare Accenture UKJohanna Moss - Director of Strategy, University College London Hospitals (UCLH)Ben Osborn - President, International Commercial Office, PfizerLloyd Price - Founder and Partner, Nelson AdvisorsSara Siegel - Global Health Sector Leader and Lead Partner for Healthcare, DeloitteAdrian Stevensen - CEO, Independent CareMing Tang - Chief Data and Analytics Officer, NHS EnglandDr Susan Thomas - Director, Google for Health, EMEASource: <a href="https://www.ucl.ac.uk/population-health-sciences/global-business-school-health/people" data-mce-href="https://www.ucl.ac.uk/population-health-sciences/global-business-school-health/people">https://www.ucl.ac.uk/population-health-sciences/global-business-school-health/people</a>

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Nelson Advisors referenced in a Copenhagen Business Schoo...

Nelson Advisors referenced in a Cornell University paper ...

Nelson Advisors referenced in the Official Journal of the...

First use cases of OpenClaw by OpenAI in healthcare

This Week in European MedTech and HealthTech: 13th March ...

Nelson Advisors invited to UCL GBSH Health Executives in ...