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Nelson Advisors is proud to help peer review BMJ Connections Digital Health &amp; AI journal articles and support the healthcare technology community as we enter an exciting growth phase in the use of AI to improve health outcomes and the delivery of care. &nbsp;&nbsp; BMJ Connections Digital Health &amp; AI is an open access journal publishing the full spectrum of robust, reproducible, original research including negative results and small and specialist studies. The journal welcomes contributions from a wide range of fields including medicine, computer science and public health.BMJ Connections Digital Health &amp; AI is the companion title to BMJ Digital Health &amp; AI, a high impact journal publishing novel research, reviews, and opinion pieces. The close relationship between these titles enables seamless transfers from BMJ Digital Health &amp; AI, saving time and effort for authors.Source: <a href="https://connectionsdigitalhealth.bmj.com/" data-mce-href="https://connectionsdigitalhealth.bmj.com/">https://connectionsdigitalhealth.bmj.com/</a>The medical research community needs access to the full spectrum of robust, reproducible research—including work showing incremental advances or null results. BMJ Connections journals are open to submissions of all well-conducted research that will help to complete the scientific record. Publishing open access with us ensures that your work will be visible and available to your community of medical researchers and clinician peers, with the maximum chance of citation and wider, real-world impact.About BMJ Group &nbsp;&nbsp; Since 1840, BMJ Group has been at the forefront of providing research, knowledge, and education to health professionals worldwide, envisioning a healthier world for all. With a global reach spanning five offices across the UK, the Americas, India, and China, we maintain our position as one of the most trusted brands in the world by providing the very best publishing expertise, digital health tools, and learning resources. Every month, over 11 million visitors frequent our websites to access the most relevant and reliable research available. &nbsp;&nbsp; Evolved from the Provincial Medical and Surgical Journal to the esteemed general medical journal, The BMJ, our journey embodies continuous evolution and innovation. As pioneers of online medical publishing since 1995, we strive to uphold the highest editorial standards while embracing technological advancements.&nbsp; &nbsp;&nbsp; Our focus extends beyond publication metrics; we actively support authors from low and lower-middle-income countries, champion equity, diversity, and inclusion, and safeguard the integrity of scientific research globally. With BMJ New Ventures, our startup investment initiative, we work with partners aligned with our vision and values, fostering innovation and driving positive change in healthcare and beyond.&nbsp;From publishing research to investigating and responding to allegations of misconduct, we always treat researchers and institutions fairly and courteously so that they have a safe platform to share their research or raise concerns. We do this collectively by working in partnership with editors and publishing staff on all issues related to research integrity, at every stage of the publication process.<a href="https://journals.bmj.com/bmj-connections-journals">https://journals.bmj.com/bmj-connections-journals</a> &nbsp;&nbsp;

Nelson Advisors invited to peer review BMJ Connections Digital Health & AI journal

The European healthcare technology landscape has reached a profound inflection point in 2026, transitioning from a period of speculative, venture-subsidised fragmentation into a disciplined era defined by industrial maturity and strategic consolidation. This systemic shift is most visible in the rapid maturation of Ambient Voice Technology (AVT), a subset of artificial intelligence designed to ambiently capture clinical consultations and automate documentation.&nbsp; The recent acquisitions of Juvoly by Tandem Health and ClinicLetter.ai (CLAI) by Mayden serve as critical signalling events, suggesting that the "Great Calibration" of 2024–2025 has given way to a robust resurgence in mergers and acquisitions (M&amp;A) driven by platform-scale logic rather than mere point-solution experimentation. &nbsp;&nbsp; This transformation is underpinned by what market analysts term "Regulatory Darwinism," where the full implementation of the EU Medical Device Regulation (MDR) and the EU AI Act has created a formidable capital-intensive barrier to entry, effectively forcing smaller, less-regulated entities into the arms of established platforms. As health systems across the continent grapple with a projected global shortage of 10 million healthcare workers by 2030, the strategic value of AVT has shifted from a novelty to a critical infrastructure requirement.&nbsp;The following analysis explores the catalysts of this consolidation wave, the technical evolution of AVT from simple scribing to agentic operating systems, and the macroeconomic forces shaping the European digital health ecosystem through 2026.Source: <a href="https://www.healthcare.digital/single-post/strategic-consolidation-in-ambient-voice-technology-and-the-emergence-of-clinical-operating-systems">https://www.healthcare.digital/single-post/strategic-consolidation-in-ambient-voice-technology-and-the-emergence-of-clinical-operating-systems</a>The acquisitions of Juvoly and CLAI are not isolated events but the opening salvos of a comprehensive industrialisation of the European healthtech sector. The "Great Calibration" of the past two years has purged the market of speculative point solutions that lacked regulatory rigor or workflow depth. In their place, a disciplined era of "Industrial Logic" has emerged, where capital is concentrated in platforms that can demonstrate immediate EBITDA uplift through automation. The drivers of this wave are structural rather than cyclical. Regulatory Darwinism (MDR, AI Act) has made it nearly impossible for SMEs to survive independently. Macroeconomic shifts (The Series A Off-Ramp) have forced founders to prioritize strategic exits. And the clinical reality of an aging population and a shrinking workforce has made AVT an essential utility rather than a luxury. As the market moves toward 2027, the "bifurcation" between well-funded, compliant platforms and distressed point solutions will likely widen, leading to a "string of pearls" acquisition strategy by dominant players seeking to secure geographic footprints and clinical data moats across the continent. &nbsp;&nbsp; The future of European healthcare will be defined by these "AI-native operating systems"—systems that respectfully remove administrative friction, allowing clinicians to focus their attention where it is most humanly needed: the patient.The consolidation seen in early 2025 is merely the precursor to a more profound transformation of care delivery, where technology finally transitions from being a "cost" to becoming the strategic enabler of clinical and economic sustainability.Read the report: <a href="https://www.healthcare.digital/single-post/strategic-consolidation-in-ambient-voice-technology-and-the-emergence-of-clinical-operating-systems">https://www.healthcare.digital/single-post/strategic-consolidation-in-ambient-voice-technology-and-the-emergence-of-clinical-operating-systems</a>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>

Ambient Voice Technology: Strategic Consolidation and the Emergence of Clinical Operating Systems

What Differentiates Winning Healthcare IT Investments1. Healthcare IT has delivered superior returns vs. other healthcare subsectors since 2017 and now represents roughly 20% of healthcare PE deal volume, up from about 15% in 2021.2. 2025 saw standout HCIT deals globally, including ModMed and HealthEdge/HealthProof in North America, Softway Medical Group in Europe and multiple AI-enabled RCM platforms in Asia such as AGS Health and Smarter Technologies.3. Performance expectations have reset upward: leading HCIT assets now clear a “Rule of 60” (growth plus EBITDA margin above 60%), versus the traditional software Rule of 40.4. Structural demand drivers, billing complexity, workflow digitization, interoperability needs, and value-based care are keeping IT spend a top priority for providers and payers and underpin continued HCIT deal activity.5. The asset pipeline remains healthy, with many sponsor-owned HCIT businesses nearing the end of their holding periods, supporting ongoing transaction flow.6. The value-creation model has shifted from simple adoption-led growth (eg. EMR rollouts post‑HITECH) to more complex, underwritten value levers baked into the base case of deals.7. Generative AI is a central value lever, used both to boost revenue (new products, enhanced offerings) and cut costs (workflow automation, back-office efficiencies), while also serving as a hedge against disruption.8. Commercial excellence is critical: investors are emphasizing sophisticated pricing/packaging programs, product and feature bundling, and structured upsell/cross-sell go-to-market motions.9. M&amp;A is a core tool in the playbook, used to accelerate growth, expand into adjacencies, and capture substantial cost synergies within HCIT platforms.10. To win, HCIT companies must aggressively embed generative AI, refine pricing and business models, and proactively manage downside and competitive risks to achieve Rule-of-60 outcomes and attractive exit returns.Source: <a href="https://www.bain.com/insights/what-differentiates-winning-healthcare-IT-investments-global-healthcare-private-equity-report-2026/" data-mce-href="https://www.bain.com/insights/what-differentiates-winning-healthcare-IT-investments-global-healthcare-private-equity-report-2026/">https://www.bain.com/insights/what-differentiates-winning-healthcare-IT-investments-global-healthcare-private-equity-report-2026/</a>Healthcare private equity reached a record high in global deal value in 2025, powered by large transactions and overcoming a slowdown in the second quarter in both North America and Asia-Pacific. Deal count posted the second-highest annual total on record, with strength across all deal sizes. And provider and biopharma anchored activity while healthcare IT continued to grow its share of healthcare transaction volume.Our report explores the underlying trends in 2025, including rising investor confidence in market fundamentals in the face of headwinds, the importance of operational sophistication, the return of sponsor-to-sponsor activity, and the growing importance of AI and technology. Looking ahead, investors will need conviction in their value-creation playbooks to deliver outsized returns as competition for assets remains intense.Bain’s Healthcare Private Equity Leadership TeamSource: <a href="https://www.bain.com/insights/topics/global-healthcare-private-equity-report">https://www.bain.com/insights/topics/global-healthcare-private-equity-report</a>

Bain Capital Global Healthcare Private Equity Report: 10 Key Takeaways

Last week, BioXconomy reported on Novartis’ announcement at the conference that detailed two licensing agreements with SciNeuro Pharmaceuticals and Zonsen PepLib. Sanofi also made big plays at the start of the month, signing a deal with Earendil Labs worth $2.56 billion to lead the development and commercialization of bispecific antibodies. The French pharmaceutical company also acquired Dynavax for $2.2 billion, along with its immunization drug candidates.A report by Nelson Advisors noted that while large pharmaceutical companies remain active in M&amp;A scouting, many are taking a more disciplined approach to favoring targeted acquisitions over large-scale transactions.“The strategy involves the systematic acquisition of smaller, early- to mid-stage innovative companies or assets, primarily to fortify drug pipelines, mitigate the impact of impending patent expirations, and integrate crucial new capabilities.”Source: <a href="https://www.bioxconomy.com/partnering/rumor-has-it-sanofi-secretly-bids-for-retinal-drug-developer">https://www.bioxconomy.com/partnering/rumor-has-it-sanofi-secretly-bids-for-retinal-drug-developer</a>About BioXonomyBioXconomy, owned by Informa, engages the industry, builds community, and connects life sciences professionals to current, credible information, products and services relevant to their business. As the official media partner for Informa Life Sciences flagship events including BIO-Europe and LSX World Congress, TIDES US and RNA Leaders, ACCESS US and Pharma Forum, BioXconomy offers our audiences exclusive event-based insights, updated news and features, and interactive media.<a href="https://www.bioxconomy.com">https://www.bioxconomy.com</a>

Nelson Advisors featured in BioXconomy, the flagship publication for Informa Life Sciences

Shadow AI in health systems refers to clinicians and staff using AI tools (like public chatbots or unapproved apps) without their organisation’s formal approval or oversight and it is now widespread in hospitals and health systems.What “shadow AI” means in healthcareShadow AI is the unsanctioned use of AI tools, models or features without visibility from IT, security or governance teams. In healthcare, that often means staff pasting patient details into public generative AI tools, using unvetted documentation assistants, or standing up their own models in cloud environments outside official processes. Evidence it’s a growing issue at health systems A Wolters Kluwer survey of more than 500 hospital and health system workers found 40% had encountered unauthorised AI tools at work, and about 17–20% admitted using them themselves. Around one in ten respondents said they had used an unauthorised AI tool for direct patient care use cases, underscoring that this is not just back‑office experimentation. Healthcare workers report turning to shadow AI primarily to speed workflows, cope with documentation burden, and access functionality they feel approved tools lack or do not yet offer. Why it’s particularly risky in health systems Data privacy and cybersecurity: Uploading PHI or other sensitive data into public or unvetted AI tools can bypass organisational controls, create “silent” cross‑border data leaks, and increase breach costs. Patient safety and clinical quality: Unvalidated models can give inaccurate or biased outputs; if clinicians rely on them for documentation or decision support, errors may not be visible to governance teams until harm occurs. Regulatory and legal exposure: Unapproved AI use can trigger violations of HIPAA and other privacy regimes and also complicate accountability when an AI output influences care without traceable oversight. What’s driving shadow AI in hospitals Burnout and workload: Clinicians and admin staff use generative AI to draft emails, summarise notes, or translate content because it feels like the only way to keep up with documentation and communication demands.​ Innovation gap: Staff perceive that official AI programmes are moving too slowly or that approved tools are less capable than consumer‑grade offerings, so they “experiment” on their own. Low AI literacy and unclear policy: Many organisations have not yet provided clear, practical guidance on what is permitted, where data may go, and how to request new tools, which fuels informal workarounds. How leading health systems are responding Visibility and monitoring: Security leaders are starting with discovery tools to detect unauthorised AI usage and data flows, especially those involving patient information. Governance structures: Some systems have created cross‑functional AI governance councils (clinical, IT, legal, compliance, operations) to evaluate tools, set guardrails, and approve use cases. “Enable, don’t ban” strategies: Rather than blanket blocking, a number of organisations allow controlled experimentation, provide sanctioned AI options (e.g., ambient scribe, clinical decision support), and educate staff to keep usage inside safe channels.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>

Shadow AI is becoming a growing issue for hospitals and  health systems

Health AI has moved from hype to execution, with a new cohort of AI-native businesses scaling faster, with better unit economics, and attracting both IPO and private-market capital; Bessemer’s thesis is that this “Health Tech 2.0” wave is real, not another ZIRP-style bubble.​1. Health Tech 2.0 vs 1.0 Health Tech 1.0 IPOs (telehealth, virtual care, broad “digital health”) rode COVID/ZIRP tailwinds with weak unit economics and subsequently destroyed public-market trust, closing the IPO window through 2023.​ Health Tech 2.0 IPOs (Waystar, Tempus, Hinge, Omada, Caris, HeartFlow) came public 2024–25 with profitable or near-profitable models, strong net retention and clear ROI, and now represent ~30% of the $121B BVP Health Tech Index market cap.​ 2. Public market comeback, but with a trust gap New Health Tech 2.0 stocks rose ~18% in 2025, roughly in line with NASDAQ and S&amp;P 500, while the broader health tech index was up 4% and cloud software (EMCLOUD) fell 7%.​ Despite 2x the revenue growth and FCF margins of high‑growth software peers, health tech still trades at a 10–20% valuation discount due to perceived complexity, regulatory risk, and memories of 2020–21, a gap Bessemer expects to narrow over 12–24 months.​ 3. Private-market proof: M&amp;A, funding, valuations Global health tech M&amp;A hit ~400 deals in 2025 (vs 350 in 2024), with acquirers using AI to drive both revenue growth and margin expansion (e.g., SmarterTechnologies–Access Healthcare–SmarterDx roll‑up, Waystar–Iodine, R1–Phare Health).​ Venture deal volume (~527 health tech VC deals, ~$14B deployed) and a 42% jump in average round size to $29.3M show deal-making back at pandemic levels; 55% of all health tech funding now goes to AI, and late-stage valuations (especially Series D+) are rising fastest, led by mega‑rounds such as Abridge, Ambience, Function Health, and OpenEvidence.​ 4. Health AI X Factor and “supernovas” A small set of Health AI “supernovas” (e.g., SmarterDx, Abridge, OpenEvidence) are growing 6–10x annually, hitting $100–200M ARR in under five years and compressing the time to $100M ARR from a decade to as little as 18–36 months.​ The Health AI X Factor is the justification for premium NTM multiples, arguing some $30M ARR businesses can be fairly valued at $1B+ because growth curves are structurally steeper than traditional SaaS.​ 5. Four pillars of X Factor companies Velocity: Continuous 6x+ growth supported by visible pipeline, strong customer references, and no “lumpy” resets; future growth must already be embedded in implementations and expansions.​ Durability &amp; defensibility: High NRR, recurring revenue, deep workflow integration, proprietary data moats, clinical validation, and pricing power; companies competing mainly on price or with sub‑100% NRR are flagged as fragile.​ AI productivity &amp; margins: Truly AI‑native firms show ARR/FTE of $500k–$1M+ (vs $100–200k in services, $200–400k in pre‑AI SaaS) and can reach 70–80% gross margins by automating human work rather than merely wrapping services with “AI”.​ Platform expansion: The strongest players land with a high‑ROI wedge and expand to “systems of action” across workflows (e.g., Zingage moving from AI care navigation into rev‑ops, claims, recruiting), rather than trying to build a full platform from day one.​ 6. Prediction: Payers race to catch up Provider‑side AI in RCM has improved documentation, appeals and revenue capture, putting pressure on payers via higher medical loss ratios, more complex claims, and rising administrative load.​ Bessemer expects 2026 to be an inflection point where payers accelerate AI adoption across payment integrity, prior authorization/utilization review, and member engagement, with founders advised to pick high‑ROI, high‑complexity wedges.​ 7. Prediction: Clinical AI in triage and risk, not autonomy (yet) Clinical AI is shifting from concept to scale in triage and risk assessment use cases that keep clinicians in the loop: pre‑visit risk stratification, inpatient deterioration prediction, triage optimization, and smarter specialty referral.​ Regulatory, liability, and reimbursement constraints still limit fully autonomous diagnosis, so founders are urged to start from front‑office/admin entry points that naturally extend into decision support, risk scoring, and coordination.​ 8. Prediction: CMS pilots AI-first reimbursement The key bottleneck for clinical AI is payment, not tech; most providers are still paid for time and procedures, not AI‑enabled prevention or monitoring.​ CMS is expected in 2026 to test new CPT codes and models for AI‑assisted diagnosis, preventive care and AI‑enhanced remote monitoring, with the logic that successful CMS pilots will pull commercial payers into similar reimbursement within 12–24 months.​ 9. Prediction: Consumer cash-pay drives fastest clinical AI uptake Consumers are already paying out of pocket for AI‑enhanced care, exemplified by RadNet’s study where 36% of 747k+ women chose $40 AI mammography, yielding 43% higher cancer detection and ~93% accuracy when radiologists used AI assistance.​ Direct‑to‑consumer models (AI‑first primary/urgent care, AI second opinions, AI health coaches) offer a faster route to revenue and validation than waiting for reimbursement, and are framed as laying the groundwork for “AI doctors” over the next decade.​ 10. Prediction: Infrastructure, VBC, and digital CROs as next wave A new health AI data infrastructure layer is emerging to serve model labs and AI apps, but founders must differentiate from Snowflake/AWS/Databricks, design recurring “AI‑services‑as‑software” revenue, and eventually capture some application‑layer value.​ AI is expected to revive value‑based care by radically lowering the marginal cost of engagement and monitoring, and to enable “digital CROs” that replace large swathes of wet‑lab and animal testing with in silico models, robotic labs, and AI‑optimized trial design, attacking drug R&amp;D’s cost–speed–competition “trilemma”.Source: <a href="https://www.bvp.com/atlas/state-of-health-ai-2026">https://www.bvp.com/atlas/state-of-health-ai-2026﻿</a>

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Nelson Advisors invited to peer review BMJ Connections Di...

Ambient Voice Technology: Strategic Consolidation and the...

Bain Capital Global Healthcare Private Equity Report: 10 ...

Nelson Advisors featured in BioXconomy, the flagship publ...

Shadow AI is becoming a growing issue for hospitals and ...

Bessemer Venture Partners 'State of Health AI 2026' Repor...