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AI systems competing on health outcomes would shift incentives away from selling software volume and towards verifiable improvements in morbidity, mortality, cost and equity, but it would require new contracting, measurement and governance to avoid gaming and exacerbating disparities.​Core idea If AI vendors were paid primarily for outcomes (e.g., fewer readmissions, lower HbA1c, earlier cancer stage at diagnosis), they would be incentivized to build tools that measurably improve population health rather than just workflow or billing metrics. This is essentially extending value-based care logic from providers to the AI supply chain, aligning payment with validated quality metrics and total cost of care.​How AI could “compete” on outcomes 1) Tie payment to pre-agreed clinical metricsContracts can reward AI only when specific endpoints move, such as reduced heart failure admissions, better diabetes control, or improved screening uptake.​ Performance-based linear and “dynamic” models already being piloted share upside with vendors when outcomes improve, and claw back fees when they do not.​ 2) Use value-based reimbursement structuresProposed frameworks include per-patient or per-episode fees contingent on achieving quality standards, time-limited add-on payments, and bonuses for demonstrable outcome gains instead of per-scan or per-click fees.​ For generalist medical AI, tiered reimbursement aligned with level of autonomy (assistive → augmentative → autonomous) could be coupled to outcome benchmarks at each tier.​ 3) Outcome-focused use casesIn value-based care programs, AI already supports risk prediction, early intervention and coordinated care, with reported 30–45% cost savings in high-cost episodes when outcomes improve.​ AI-driven personalized prevention and screening programs have increased screening rates and early cancer detection, illustrating how outcome-linked incentives for insurers and vendors can form a virtuous cycle.​ Benefits of outcome-based AI competition a) Better alignment of incentivesPayers can use reimbursement as a “gatekeeper” to prioritize AI that demonstrably improves workflows, access and outcomes rather than throughput or high-margin services.​ When life and health insurers share in financial gains from healthier members, they are natural funders of AI that drives sustained behaviour change and prevention.​ b) Stronger ROI disciplinePerformance-based pricing addresses buyer skepticism about paying high prices for AI without clear, realized value.​ Outcomes-based models support investment into prevention, chronic disease control and post-acute optimization that are often under-incentivized in fee-for-service.​ c) Potential to reduce inequitiesProperly designed AI can improve early detection, adherence and post-treatment monitoring in underserved populations, closing outcome gaps if metrics are stratified by race, gender and geography.​ Some policy proposals explicitly suggest rewarding AI that improves equity and penalizing tools that increase bias.​ Risks and failure modes i) Measurement and attribution challengesOutcomes such as mortality, readmissions or A1c can take time to move and are influenced by many factors, making causal attribution to a single AI tool nontrivial.​ Over-reliance on narrow metrics can drive gaming, such as avoiding high-risk patients, over-documenting, or optimizing for surrogate endpoints that do not translate into genuine health gains.​ ii) Equity and bias concernsThere is documented concern that AI can encode and amplify existing biases, worsening disparities unless datasets, objectives and incentives explicitly correct for this.​ If vendors are rewarded on average performance without equity constraints, they may focus on “easy” populations and neglect complex or disadvantaged groups.​ ii) Market structure and lock-inSophisticated outcome-based contracts could favour large incumbents who can carry risk, build data-sharing infrastructure, and tolerate delayed payments.​ Payer and provider dependence on a small number of high-performing platforms may reduce contestability unless interoperability and switching are also rewarded.​ What it would take to make this work a) Robust real-world evaluation infrastructureHealth systems need standardized evaluation pipelines, including prospective, multi-site studies and RWD-based monitoring, to validate that AI actually improves outcomes before and after deployment.​ National programs (e.g., AI in Health and Care evaluations) already highlight the need for careful measurement, bias assessment and ongoing post-deployment surveillance.​ b) Contract and policy innovationRegulators and payers are exploring targeted outcome incentives, transitional add-on payments, advance market commitments and reimbursement standards that explicitly include interoperability and bias mitigation.​ Performance-based pricing schemas in which fees escalate with realized outcome improvements (and fall with underperformance) are emerging templates for AI vendors.​ c) Governance and transparencyResponsible AI frameworks stress explainability, continuous monitoring, multidisciplinary oversight and clear allocation of liability between clinicians, institutions and vendors.​ To avoid perverse incentives, contracts will likely need guardrails around patient selection, minimum quality thresholds, and equity-adjusted metrics.​ For someone operating in healthtech M&amp;A, the implication is that a significant portion of future AI value will be priced off validated outcome improvements and risk-sharing capacity rather than mere model performance, which will directly influence business models, revenue visibility and valuation approaches.To discuss how Nelson Advisors can help your HealthTech, MedTech, Health AI or Digital Health company, please email <a data-mce-href="mailto:lloyd@nelsonadvisors.co.uk" href="mailto:lloyd@nelsonadvisors.co.uk" title="lloyd@nelsonadvisors.co.uk" target="_blank" rel="noopener" data-mce-selected="inline-boundary">lloyd@nelsonadvisors.co.uk</a>

What if AI competed on healthcare outcomes?

HealthTech M&amp;A valuations going into January 2026 are holding in a disciplined but healthy band, with most quality assets changing hands around mid‑single‑digit revenue multiples and low‑teens EBITDA, and premium AI/data platforms stretching above that range.&nbsp;'Headline multiples as 2026 opens'EV/Revenue (core HealthTech / digital health)General HealthTech: ~4x–6x revenue remains the central band across 2025 data and late‑year outlooks into 2026.&nbsp; Premium AI, telehealth &amp; analytics: 6x–8x+ where there is proprietary data, deep workflow integration and strong growth.&nbsp; Sub‑scale or unprofitable assets without clear defensibility: often compressed to 3x–4x unless a strategic buyer sees a unique fit.&nbsp; &nbsp; EV/EBITDA (profitable / tech‑enabled services)Profitable HealthTech: broadly 10x–14x EV/EBITDA through 2025, with European HealthTech/MedTech sitting in low‑teens on average.&nbsp; Private equity healthcare deals overall: ~11x–13x median EV/EBITDA across 2025, with strategics typically 20–40% above financial sponsors on like‑for‑like assets.&nbsp;'Trendlines vs 2023–24'Normalisation after the COVID / 2021 peak: Revenue and EBITDA multiples have reset from 2021 highs but have not collapsed, with 2021‑era 8x–10x “tourist” pricing now reserved for only the best AI/data assets.&nbsp; Mid‑market healthcare IT deals from 2021–24 averaged ~6x EV/Revenue; recent reports show normalisation closer to 4x–6x depending on quality.&nbsp;Stabilisation through 2025 into early 2026: European HealthTech and MedTech multiples stabilised around ~4.8x revenue and low‑teens EV/EBITDA by Q4 2025, with outlooks flagging a cautiously more constructive M&amp;A market in 2026.&nbsp; Forecasts for 2026 point to higher healthcare deal volumes and renewed appetite for larger, strategic transactions, especially in tech‑enabled and AI‑rich platforms.&nbsp;'Variables driving valuations now'1. AI, data and “proprietary moat”Assets with proprietary, clinically validated datasets and AI that demonstrably improve workflow or outcomes command a clear premium, often 20–30% higher EV/Revenue than non‑AI peers.&nbsp; Buyers scrutinise whether AI is embedded in mission‑critical workflows (imaging, RCM, triage, operational optimisation) rather than just a feature; this is becoming a central lens for both strategics and PE.&nbsp;2. Growth quality, profitability and the “Rule of 40+Data”Growth on its own no longer suffices; acquirers place heavier weight on: High recurring or transaction‑based revenue with low churn.&nbsp; Attractive gross margins and a credible path to EBITDA in the near term, driving the shift from pure EV/Revenue to EV/EBITDA screens for mature vendors.&nbsp; Companies that combine strong growth metrics with robust data moats and operating leverage sit at the top of the valuation range.&nbsp;3. Regulatory positioning and evidenceIn Europe, clarity around the EU AI Act, MDR/IVDR and the European Health Data Space has begun to support multiples for assets that are proactively aligned and can scale under these regimes.&nbsp; Robust clinical and economic evidence (e.g. RCTs, real‑world outcomes, payer‑grade cost‑effectiveness data) is increasingly a prerequisite for premium pricing, particularly for value‑based care and virtual care models.&nbsp;4. Strategic fit, buyer universe and deal structureStrategics and PE platforms continue to pay meaningful premiums when a target: Fills a clear capability or geographic gap. Bolsters a buy‑and‑build thesis (e.g. roll‑ups in outpatient, diagnostics, tech‑enabled services).&nbsp; Across healthcare, strategic buyers are still paying 20–40% higher multiples than financial sponsors for comparable assets, and are more willing to stretch on revenue multiples where synergies and cross‑sell are tangible.&nbsp; Earn‑outs, seller notes and performance‑linked consideration remain common in 2025–26 to bridge valuation gaps between 2021 expectations and current discipline.&nbsp;Macro and segment‑specific influences into 2026Rates, macro and capital markets: Expectations for rate cuts and easing inflation in 2025–26 underpin a more supportive backdrop for healthcare M&amp;A, though buyers remain selective and focused on cash generation.&nbsp; Healthcare retains its role as a defensive sector, with HealthTech/digital health seen as a way to drive productivity and margin repair, which supports sustained M&amp;A appetite.&nbsp;Sub‑segment rotation: Capital is rotating toward provider‑operations tech, RCM/administrative automation, and AI‑enabled diagnostics, while some consumer‑only or point‑solution telehealth models see relatively weaker multiples.&nbsp; In the UK and Europe, assets selling into public systems (e.g. NHS‑aligned platforms) that can prove budget impact and interoperability are seeing stronger buyer interest and firmer pricing. To discuss how Nelson Advisors can help your HealthTech, MedTech, Health AI or Digital Health company, please email <a data-mce-href="mailto:lloyd@nelsonadvisors.co.uk" href="mailto:lloyd@nelsonadvisors.co.uk" title="lloyd@nelsonadvisors.co.uk" target="_blank" rel="noopener">lloyd@nelsonadvisors.co.uk</a>

HealthTech M&A Multiples January 2026: Current Trends and Variables driving valuations

European MedTech this week is shaped by three themes: MDR/IVDR simplification and EUDAMED timing, new guidance for Notified Bodies, and a steady drumbeat of innovation and capital around robotics, neuro and data‑rich devices.​Regulatory and guidance moves The Commission’s December 2025 proposal to “simplify” MDR/IVDR is setting the 2026 agenda, with a strong focus on digitalising procedures, harmonising Notified Body practices, and clarifying rules for AI‑enabled devices and nanomaterials.​ A draft implementing regulation on how Notified Bodies run conformity assessments for devices and IVDs is out to consultation until 9 January 2026, signalling tighter but more predictable oversight across the EU.​ EUDAMED and transparency in 2026 The Commission’s late‑2025 notice that four EUDAMED modules are now fully functional starts a six‑month transition, after which manufacturers, suppliers and Notified Bodies must meet new registration and data‑submission obligations under MDR/IVDR.​ From mid‑2026, EUDAMED’s staged roll‑out is expected to materially increase transparency around device registrations, vigilance and market actors, which in turn will influence payer scrutiny and due‑diligence processes for European MedTech deals.​ Technical guidance and classification The latest round of MDCG‑endorsed documents, published in December 2025, adds further guidance on applying MDR/IVDR, including to software and AI‑driven products, which many EU MedTech software vendors rely on when planning 2026 submissions.​ MedTech Europe’s 2026 version of the Global In Vitro Diagnostic (GIVD) Classification is now available and should be used by IVD manufacturers for data submissions from January 2026 onward, tightening alignment between product coding and EU regulatory expectations.​ Innovation, robotics and neuro focus Paris‑based startup Robeauté drew fresh attention this week with coverage of its microrobotics platform for diagnosing, treating and monitoring brain disease, illustrating the kind of high‑complexity, neuro‑focused MedTech that European investors are leaning into for 2026.​ Broader 2026 outlook pieces highlight MedTech dealmaking around devices that pair hardware innovation with strong data, reimbursement support and AI‑enhanced workflows, especially in cardiovascular, neurovascular, advanced diagnostics and surgical robotics.​ Capital formation and dealmaking tone Law‑firm and strategy notes published around year‑end flag 2026 as a year where MedTech M&amp;A will concentrate on fewer, higher‑value assets, particularly those that benefit from MDR/IVDR simplification, EUDAMED transparency and clear health‑technology‑assessment narratives.​ European-focused analyses point to continued buy‑and‑build strategies in fragmented device and MedTech‑adjacent software markets, with funds targeting platforms that can sit on top of EHDS‑style data flows and support cross‑border care pathways.&gt;&gt;&gt;European HealthTech this week is characterised by EU‑level AI and data initiatives moving into implementation, fresh and upcoming funding calls for digital health innovators, and a continued tilt toward AI‑driven automation and consolidation plays as 2026 opens.​EU AI, data and digital health policyThe Commission’s Artificial Intelligence in Health and broader digital strategy pages now explicitly link the AI Act, MDR and the Digital Omnibus as the core framework for “robust and trustworthy” AI in healthcare, emphasising harmonised rules and reduced compliance friction for innovators.​ Under the Apply AI Strategy and the Digital Omnibus package, the EU is preparing data‑intensive infrastructures and simplification measures that will support AI Factories, health data infrastructures tied to the European Health Data Space, and sector‑specific deployment in healthcare from 2026 onward.​ Grants and EU‑backed funding windows The UNITE Open Call for European digital health innovators is live with a total budget of €4 million, offering up to €1 million per project and a submission deadline of 15 January 2026 for cross‑border digital health solutions.​ In parallel, the 2026 cycle of the Future of Health Grant in Switzerland is opening this month, targeting early‑stage digital health startups in telemedicine, patient analytics, preventive care and digital therapeutics, adding another visible capital source for European HealthTech.​ Horizon Europe and global health programmes The Health‑NCP network reports that the Commission has adopted the main Horizon Europe 2026–2027 work programme, with a €14 billion R&amp;I envelope that includes significant health and digital components relevant to data, AI and HealthTech infrastructure.​ Global Health EDCTP3’s 2026 work programme will invest up to €147 million across six research topics, with calls opening by mid‑January 2026 and full proposals due by 31 August 2026, providing another route for consortia working on infectious‑disease‑focused digital and clinical innovations.​ Market structure, consolidation and strategic themes A late‑December 2025 consolidation outlook notes that 2026 is expected to be a year of “Great Rationalisation” in European HealthTech and MedTech, with PE‑backed roll‑ups in services and strategic consolidation in AI‑enabled radiology, digital pathology and tech‑enabled home care.​ That same analysis highlights regulatory inflection points around the AI Act and Digital Omnibus, plus portfolio rationalisation under MDR/IVDR, as catalysts for both deconsolidation at the corporate level and aggressive acquisition of AI and digital health capabilities by majors like Siemens Healthineers.​ Startup activity and AI automation in care delivery A recent EU‑Startups feature spotlights European startups using AI to automate healthcare administration and back‑office workflows, underscoring investor interest in tools that free up clinical time and integrate with existing hospital information systems rather than purely consumer apps.​ Broader newsletters on digitalisation of healthcare in January 2026 point to sustained momentum in virtual care, remote monitoring and AI triage tools across Europe, but with heightened focus on interoperability, reimbursement evidence and readiness for the AI Act’s high‑risk requirements.To discuss how Nelson Advisors can help your HealthTech, MedTech, Health AI or Digital Health company, please email <a data-mce-href="mailto:lloyd@nelsonadvisors.co.uk" href="mailto:lloyd@nelsonadvisors.co.uk" title="lloyd@nelsonadvisors.co.uk" target="_blank" rel="noopener" data-mce-selected="inline-boundary">lloyd@nelsonadvisors.co.uk</a>

This Week in European HealthTech and MedTech: 3rd January 2026

1) AI Moves From Hype to Healthcare Infrastructure at JPM 2026AI is now treated as core infrastructure across R&amp;D, diagnostics, revenue cycle, and ops, not a side-show.​ Investors are rewarding AI platforms with clear ROI, interoperability and payer alignment, rather than generic point solutions.​ 2) Oncology, Neuro and Heme Dominate the JPM 2026 Deal PipelineConference agendas and guides flag late‑stage oncology, neuropsychiatry/neurology and hematology as the key therapeutic hotspots.​ Many licensing and BD conversations are expected to cluster around biomarker‑linked, companion‑diagnostic enabled assets in these areas.​ 3) Capital Discipline Rules: Fewer, Bigger, De‑Risked Rounds Shape 2026 Narratives2025 data show VC dollars skewing to larger, later‑stage financings with falling deal counts but resilient capital deployment.​ JPM 2026 is framed as a year where investors prioritize clinical proof, regulatory readiness and line‑of‑sight to profitability.​ 4) Medtech and Digital Health Face a ‘Proof Over Promise’ MomentMedtech and digital health sessions emphasize profitability, unit economics and evidence of scale, not growth at any cost.​ Investors are gravitating toward device‑plus‑software, monitoring and real‑world data platforms with defensible data moats.​ 5) IPO Window Narrow, M&amp;A and Take Privates Back at Center StageReports highlight a thin IPO window with a small cohort of scaled, profitable issuers testing public appetite.​ Expectations point to increased tuck‑in M&amp;A, roll‑ups and take‑privates, particularly to add AI and data capabilities.​ 6) Corporate Venture and Strategics Reassert Themselves in 2026 DealmakingCorporate venture arms at large strategics are stepping up to secure early exposure to robotics, diagnostics and AI infrastructure.​ At JPM 2026, strategics are positioned as key partners for later‑stage rounds, platform validation and cross‑border scale‑up.​ 7) Regulators, Payors and AI Governance Take the Main StagePolicy and regulation panels around FDA AI/ML frameworks, privacy, and reimbursement have moved into the conference mainstream.​ Algorithmic bias, explainability and real‑world performance metrics are becoming gating items for both approvals and funding.​ 8) Health Systems Pivot to Care‑Anywhere Models Under Margin PressureProviders arrive at JPM focused on shifting volume to outpatient, home and virtual settings to manage cost and workforce strain.​ AI and automation, combined with new contracting models, underpin many of the health‑system strategy stories told during the week.​ 9) TechBio and Compute‑First Platforms Redefine Biotech’s Next WaveSide forums such as TechBio and AI‑driven showcases spotlight computational biology, AI‑enabled discovery and platform plays.​ Investors increasingly frame these as infrastructure bets that can feed multiple therapeutic programs and partnerships.​ 10) JPM 2026 Marks a Tentative Turn From Survival Mode to Selective GrowthIndustry outlooks suggest 2026 could be a stronger year than the recent downturn, with cautious optimism in biopharma and medtech.​ The week is positioned as a “clearing event,” where high‑quality, de‑risked platforms reset valuations and reopen selective growth pathways.

JP Morgan Healthcare Conference 2026: 10 Potential Headlines and Key Talking Points

Most advanced capitalist economies adopted strong public or “socialised” health systems because broad access to care turned out to be economically useful, politically popular and more efficient than relying mainly on private markets for a complex, high‑cost risk like illness.​Clarifying the premise Almost all high‑income countries combine capitalist product and labour markets with universal or near‑universal health coverage financed largely through taxes or mandatory insurance, rather than pure state‑run “socialist” systems.​Within the OECD, government or compulsory schemes usually account for 70–90% of health spending, even where delivery is mixed public–private.​ Economic reasons Health care has classic market failures: information asymmetry, emergency demand, and huge cost uncertainty, making standard consumer markets bad at pooling risk and ensuring access.​ Comparative OECD analysis finds no evidence that shifting from public to privately dominated financing improves efficiency, while higher public shares of financing are associated with higher system‑wide efficiency on average.​ Historical and political reasons Modern welfare states grew out of industrialisation and social conflict; Bismarck‑era social insurance and later post‑war reforms extended sickness insurance and health services to workers to stabilise capitalist societies and undercut radical movements.​ After the Second World War, many European governments used tax‑funded universal health systems (for example, the NHS in the UK and Sécurité sociale in France) to cement social solidarity and rebuild legitimacy, not to abolish markets more broadly.​ Business and productivity reasons A healthy workforce raises productivity and labour supply, so capital‑owning and centrist parties often accepted public health coverage as a way to support growth while leaving most of the rest of the economy to market forces.​ In systems with employer‑based or fragmented private coverage, like the US, high costs and gaps in coverage are now seen by many firms as a competitiveness problem, reinforcing arguments that universal coverage is compatible with, and even supportive of, capitalism.​ Why the US looks different The US is the main outlier because it locked in employer‑based private insurance during the mid‑20th century and has unusually powerful health‑industry interests, which raises the political cost of shifting to a more socialised model, despite already high public spending.​ Even there, large tax‑funded programs such as Medicare, Medicaid, and the VA mean a substantial share of US health care is already publicly financed, showing the same underlying logic at work.

Why do most capitalist economies have socialist health care systems?

Founders can maximise shareholder value heading into 2026 by building capital efficient, evidence led businesses that are strategically positioned for a consolidation heavy exit market rather than an IPO.​1. Design for M&amp;AAssume your most likely liquidity event is a strategic or sponsor-led acquisition rather than a listing; most digital health and MedTech exits in 2025 are via M&amp;A, with IPOs still subdued.​ Map 5–10 “natural acquirers” and align roadmap, data assets, and geography with their portfolio gaps and roll‑up theses, as PE &nbsp;and VC backed platforms increasingly pursue consolidation plays.​ 2. Prove hard outcomes and ROIInvestors heading into 2026 are explicitly favouring solutions that show measurable improvements in outcomes, cost, or operational efficiency, not just novel tech.​ Build a small number of high‑quality outcome studies (e.g. reduced length of stay, NNT, avoided admissions) and bake a health‑economic case into every board pack and fundraising narrative.​ 3. Be ruthlessly capital efficient The funding model has shifted to “selective scale”: fewer but larger cheques go to companies that demonstrate capital efficiency and clear paths to profitability.​ Track and manage burn multiple, CAC payback, and time-to-profitability at board level; investors now explicitly reward disciplined cost control and opex leverage in valuations.​ 4. Navigate EU regulation as an edge New frameworks such as MDR/IVDR, the EU HTA Regulation and the European Health Data Space are creating both barriers and defensible moats, reinforcing a flight to quality.​ Invest early in regulatory, data protection, and quality infrastructure so you are “acquisition ready” and can sell regulatory readiness and EHDS compliance as part of the asset.​ 5. Focus on consolidating hot sub‑sectors Consolidation pressure is highest in fragmented segments like diagnostics, imaging, virtual care, women’s health, mental health, home care, and specialty outpatient services, which are priority areas for PE.​Position as a “must‑own” platform in a narrowly defined niche rather than a generalist; depth in one consolidation theme typically commands better multiples.​ 6. Build a data and AI moat, not just features Investors and acquirers are favouring AI‑enabled solutions with proprietary data sets and workflow‑embedded models, especially in diagnostics, imaging, and personalised medicine.​ Treat data architecture, interoperability, and model performance as core IP, ensuring ownership and rights to use and commercialise datasets are clean for diligence.​ 7. Professionalise governance and reporting Strong governance, clean cap tables, and high‑quality financial and clinical reporting are now non‑negotiable for value-maximising exits.​ Move early to institutional‑grade board packs: monthly KPI dashboards, cohort economics, regulatory risk registers, and ESG metrics that match healthcare PE and corporate buyer expectations.​ 8. Optimise equity and dilution In a market of larger, less frequent rounds, poor dilution management can erase founder and early shareholder upside even if the exit headline looks strong.​ Model multiple financing and secondary scenarios, use structured rounds sparingly, and align option pools and vesting so key talent is still meaningfully incentivised at exit.​ 9. Play offense on portfolio and geography Large strategics and sponsors are actively pruning portfolios and seeking carve‑outs and cross‑border platform plays across Europe.​ Consider disciplined tuck‑in acquisitions or partnerships to secure missing capabilities or key geographies, making your platform more attractive to roll‑up buyers.​ 10. Tell a 2026 ready equity story Shareholder value in 2026 will accrue disproportionately to companies that combine credible growth, clear profitability path, regulatory readiness, and a role in major thematic trends (AI, outpatient shift, home care, women’s health, electric medicine).​ Refresh your narrative around these themes, anchor it in data, and ensure every investor and strategic conversation connects your company directly to where healthcare capital is actually flowing in 2026.To discuss how Nelson Advisors can help your HealthTech, MedTech, Health AI or Digital Health company, please email <a data-mce-href="mailto:lloyd@nelsonadvisors.co.uk" href="mailto:lloyd@nelsonadvisors.co.uk" title="lloyd@nelsonadvisors.co.uk" target="_blank" rel="noopener">lloyd@nelsonadvisors.co.uk</a>

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What if AI competed on healthcare outcomes?

HealthTech M&A Multiples January 2026: Current Trends and...

This Week in European HealthTech and MedTech: 3rd January...

JP Morgan Healthcare Conference 2026: 10 Potential Headli...

Why do most capitalist economies have socialist health ca...

Maximising shareholder value: 10 Tips for European Health...