The full written analysis, as published. Everything in the six planning tabs is drawn from the data below.

STRATEGY & PLANNING · GLOBAL DIGITAL HEALTH · Q4 2026 BUDGET SEASON · 18 MIN READ

The Ten-Week Window: A Q4 2026 Planning Manual for Your 2027 Digital Health Budget

Most 2027 innovation budgets will be written in the next ten weeks. Thirty-seven rounds absorbed 58% of all digital health capital in H1 2026, the average acquired venture is now 10.7 years old, and the AI label no longer buys a funding premium. Take this into your Q4 planning cycle as a working manual: what to fund, what to stop, and how to choose between building, buying and partnering.

By Sara Schmachtenberg, Head of Research, Galen Growth. Published 8 September 2026. Updated 8 September 2026. 18 min read.

Key takeaways

• Budget for an industrial market, not an innovation market. H1 2026 digital health funding reached $17.46bn across 601 rounds, against $24.41bn across 1,433 rounds in H1 2022 — capital down 28%, company count down 58%, and the average disclosed round up from $18.7m to $33.3m.

• Treat concentration as a planning assumption, not a headline. Thirty-seven rounds of $100m or more — 6.2% of all transactions — took 58.4% of H1 2026 capital, up from 41.0% in H1 2022. Your 2027 sourcing pipeline is competing for a much smaller number of fundable assets.

• Stop paying for the AI label. Ventures that market themselves as AI accounted for 58.1% of H1 2026 rounds but only 54.0% of capital, and their average disclosed round ($30.9m) now sits below that of every other venture ($36.7m) — against a 39% premium in H1 2022. Almost every venture now runs AI somewhere in the product; what has lost its value is announcing it.

• Underwrite acquisition over a decade, not a cycle. Digital health recorded 83 M&A transactions worth a disclosed $5.15bn in H1 2026 against a single IPO, and the average acquired venture was 10.7 years old at exit, up from 8.2 years in H1 2022.

• Adoption is the cheapest diligence signal available to you. Health Management Solutions and Medical Diagnostics generated 280 and 268 corporate partnerships in H1 2026 on modest capital, and 31.6% of all partnering ventures signed two or more corporate partners within the half — up from 24.9% in H1 2021.

It is Q4, which means most healthcare innovation teams are three or four weeks from a budget submission and rather further from a settled view of what to put in it. The same three questions come up every time: what has actually changed, what should we stop doing, and where should the money go in 2027. Trends reports answer the first. They rarely answer the other two, and they never answer them in time to affect a submission deadline.

This analysis is built the other way round, and it is built for the calendar you are actually on. It starts from the decisions that have to be made before a 2027 budget can be signed — where to play, what to build, what to buy, what to partner for, what to kill, and how to measure it — and uses refreshed HealthTech Alpha data through August 2026 to put a number against each one. Work through the sections in order and you should finish with a defensible allocation rather than a list of themes: every section ends with the budget implication, not the observation.

First, name the market you are budgeting for

Digital health has not contracted. It has industrialised. Those are different markets and they require different budgets.

In H1 2026, $17.46bn of primary capital was deployed across 601 funding rounds. Four years earlier, in H1 2022, $24.41bn went into 1,433 rounds. Capital fell 28%; the number of financed companies fell 58%. The average disclosed round rose from $18.7m to $33.3m. Nothing about that pattern says the sector is shrinking. It says the sector has stopped subsidising experimentation and started paying for scale.

H1 Digital Health Funding vs Rounds Financed, 2022–2026

Source: HealthTech Alpha by Galen Growth, September 2026. Excludes M&A, IPO, SPAC, post-IPO equity and secondaries. Capital has recovered from the 2023 trough while the number of companies receiving it has fallen every single half-year — the defining feature of the market you are budgeting into.

The stage data explains where the money went. Early-stage rounds — angel through Series A — fell from 760 in H1 2022 to 282 in H1 2026, with capital down from $6.34bn to $3.13bn. Growth-stage capital moved the other way, rising from $4.67bn in H1 2025 to $6.30bn in H1 2026 across just 102 rounds, and late-stage capital reached $4.43bn across 36. The market has not lost its appetite for risk; it has moved that appetite to companies that have already removed some of it.

The practical consequence for an innovation team is that the population of investable, partnerable and acquirable companies in your category is materially smaller than your 2024 pipeline assumed, and each of those companies is better capitalised, more mature and more sought-after than its equivalent two years ago. Scarcity, not abundance, is the planning assumption for 2027.

What Changed: The Innovation Market and the Industrial Market

Source: HealthTech Alpha by Galen Growth, September 2026, H1 2026 unless stated. Each row is a budgeting assumption, not a slogan — if your 2027 plan still assumes the left-hand column, it is priced for a market that no longer exists.

Where should you play? Capital intensity and adoption intensity are not the same map

The most common mistake in 2027 planning will be to use funding league tables as an opportunity map. They are a map of investor conviction, not of enterprise demand, and in H1 2026 the two point in visibly different directions.

Research Solutions attracted $5.91bn — a third of all digital health capital — across only 69 rounds, and generated 193 corporate partnerships and two M&A exits. Health Management Solutions attracted $1.74bn across 91 rounds but produced 280 corporate partnerships and 22 acquisitions. Medical Diagnostics raised $1.45bn and produced 268 partnerships and 11 acquisitions. On a capital map, Research Solutions dominates. On an adoption map, it is a distant third.

Cluster Positioning: Capital vs Adoption Intensity, H1 2026

Source: HealthTech Alpha by Galen Growth, September 2026. Bubble size reflects H1 2026 M&A exits; dashed lines mark the cluster median on each axis. The clusters that enterprise buyers are actually deploying sit in the upper-left quadrant, not alongside the largest financings.

Neither map is wrong. They answer different questions. Capital intensity tells you where a small number of platform-scale bets are being made and, by implication, where you will be outbid. Adoption intensity tells you where your peer institutions are already committing budget, integration effort and clinical governance — which is a far better predictor of what you will be able to deploy in 2027.

Reading them together produces a usable classification. Where adoption and exit activity are both high relative to capital, the category is ready to scale and the constraint is your own integration capacity. Where capital is high but adoption is thin, the category is worth watching and probably worth partnering into rather than competing in. Where both are thin and falling, the honest answer is to stop spending.

The 2027 Opportunity Map: Where Capital, Adoption and Exits Line Up

Source: HealthTech Alpha by Galen Growth, September 2026, H1 2026 (1 January–30 June). Funding excludes M&A, IPO, SPAC and post-IPO equity. The 2027 posture column is Galen Growth's interpretation of the underlying data, not a HealthTech Alpha field — treat it as a starting hypothesis to test against your own strategic priorities.

Run the same exercise against your own priorities before you accept ours. The three inputs that matter are capital momentum, partnership momentum and exit activity, and all three are visible in the data for every cluster and category. What you should not do is take a single dollar-share figure from any half-year and treat it as a category verdict: Research Solutions moved from 10.2% to 18.0% and back again on dollar share across recent periods, and any strategy built on one such reading will need rewriting by the next.

The ladder that should decide your roadmap: feature, product, platform, infrastructure

Health systems stopped shopping for features some time ago. What they are buying now is a layer — something that sits underneath documentation, scheduling, claims or care coordination and becomes structurally difficult to remove. That shift has a direct budgeting consequence, because the four rungs of that ladder have completely different economics.

The evidence sits in the partnership and M&A data rather than the funding data. Health Management Solutions ventures signed 280 corporate partnerships in H1 2026, more than any other cluster, and were acquired 22 times — more than a quarter of all digital health M&A in the half — while raising an average round of just $21.5m. That is the signature of a category being absorbed into the operating fabric of healthcare rather than sold to it.

Contrast that with a category selling a feature. A feature competes on attention and price, renews annually, and is replaced the moment a platform ships an equivalent capability. A platform competes on integration depth and switching cost, and is bought when a larger player needs the position rather than the product. In H1 2026 that difference was worth the gap between a $21.5m average round and the $650m paid for Weave in August, or the $1.5bn paid for Personalis in July.

For a 2027 roadmap, the question is not whether your portfolio contains AI, or wearables, or ambient documentation. It is which rung each asset sits on, and whether there is a credible path to the next one. Features should be bought cheaply or partnered for, never built. Platform positions are the only ones worth building internally, and only where the capability is genuinely differentiating. Infrastructure — the layer everyone else's products depend on — is now the most expensive thing to acquire and the most valuable thing to own.

What should you actually spend the AI budget on?

The single most useful finding in the refreshed data is also the most awkward for anyone whose 2027 budget line is labelled simply “AI”.

Read the tag carefully, because it records positioning rather than engineering. HealthTech Alpha classifies a venture as AI when the venture presents itself that way — and by 2026 almost everything in the dataset is running machine learning somewhere in the product, whether or not it says so in the deck. What the comparison below measures, therefore, is not the value of using AI. It is the value of advertising it.

Ventures carrying the tag took 349 of the 601 rounds closed in H1 2026 — 58.1% of all transactions, up from 45.4% in H1 2022 — but only $9.43bn, or 54.0% of the capital. Their average disclosed round was $30.9m, against $36.7m for everyone else. In H1 2022 the same comparison ran $22.1m against $15.9m, a 39% premium for saying it out loud. That premium has gone, the median says the same, and the plain reading is uncomfortable for anyone still building a pitch around the acronym: rewarding the marketing department for putting AI on the front page has stopped being a strategy, because the claim no longer separates anyone from anyone.

Average Disclosed Round Size: Ventures That Market Themselves as AI vs All Others

Source: HealthTech Alpha by Galen Growth, September 2026. Disclosed H1 rounds only, excluding M&A, IPO, SPAC and post-IPO equity. Ventures that position themselves as AI companies commanded a 39% size premium in H1 2022 and a 16% discount in H1 2026 — the tag now measures how loudly a venture markets the technology, not whether it uses it.

“AI is no longer a thesis. It is a component. Budgeting for it as a category in 2027 is like budgeting for cloud in 2015 — the money belongs in the workflow it changes, not in a line item named after the technology.”

— Sara Schmachtenberg, Head of Research, Galen Growth

The budgeting implication is precise. Because the label carries no premium, you cannot use “it is an AI company” as either a valuation justification or a strategic rationale. What still carries a premium is what the AI is embedded in: the ventures raising the largest rounds in H1 2026 were AI-enabled drug discovery platforms selling to pharmaceutical R&D budgets, clinical data infrastructure selling to health systems, and diagnostic platforms selling into reimbursed pathways — not AI capabilities sold as capabilities.

A workable split for 2027 divides AI spending into three pools rather than one. The first is automation of processes you already run and already measure, where the return is a cost line you can name and the implementation risk is low. The second is augmentation and decision support embedded in clinical or operational workflow, where the return is real but the evidence and governance burden is heavy enough to need its own budget. The third is infrastructure — data quality, interoperability, model governance and monitoring — which produces no visible product, is invariably underfunded, and determines whether the first two pools deliver anything at all. If your 2027 AI budget has no third pool, it is a pilot budget wearing a strategy label.

Build, buy or partner — and how to tell which

Once you know where to play, the operative question is how to access the capability. Most innovation teams answer it by default: they partner when procurement is easy, build when engineering has capacity, and buy when a banker calls. The data supports a more disciplined decision rule.

Start with differentiation. If the capability is not strategically differentiating for your organisation, partner for it. Nothing in the 2026 data suggests you will win by building a commodity capability internally, and the partnership market is deep: 1,591 venture–corporate partnerships were disclosed in H1 2026, with healthcare providers (270), pharmaceutical companies (166) and technology corporates (143) the largest counterparty types. Nvidia and Eli Lilly and Company each closed 15 disclosed venture partnerships in 2026 to date, ahead of Microsoft (8), Novo Nordisk and Daiichi Sankyo (7 each). Partnering at volume is now normal corporate behaviour, not an experiment.

If the capability is differentiating, ask whether you already have the underlying assets — data, distribution, clinical governance, engineering. If you do, build. If you do not, ask whether you could assemble them faster than the market will move. In most categories the honest answer in 2027 is no, which points to acquisition.

But acquisition in this market has a specific shape, and it is not the shape most corporate development plans assume. H1 2026 recorded 83 M&A transactions worth a disclosed $5.15bn against a single IPO — the narrowest exit route mix on record. Fewer deals, larger cheques, and much older targets: the average venture acquired in H1 2026 had been in existence for 10.7 years, against 8.2 years in H1 2022. This is a market for mature capabilities, not speculative technologies.

Largest Disclosed Digital Health Acquisitions, 2026 Year to Date

Source: HealthTech Alpha by Galen Growth, September 2026, covering 1 January–31 August 2026. Age at exit is measured from recorded incorporation date. Eight of the ten largest acquisitions this year were of companies at least seven years old, and half were of companies over a decade old.

Three planning consequences follow. Your acquisition pipeline should be built now for capabilities you will need in 2028 and 2029, because the assets worth buying are already visible and already partnered with someone. Your reserve and capital planning should assume a decade-long path from formation to liquidity for anything you back early. And your competitive scanning should extend beyond your own industry: technology-native and adjacent-sector entrants are buying healthcare capability rather than building it, on cycles measured in weeks.

Turn the list of pilots into a portfolio

Most innovation functions do not have a portfolio. They have a list of pilots of varying age, unclear ownership and no exit criteria. The difference matters more in a concentrated market, because the cost of running a weak pilot is no longer just the pilot budget — it is the partnership slot, the integration capacity and the clinical governance attention that a scalable programme needed.

A workable structure has four buckets and one rule per bucket. Explore covers early, uncertain bets whose only job is to produce a decision — fund them small and time-box them. Validate covers programmes generating clinical or commercial evidence, where the rule is that the evidence question must be defined before the money is released. Scale covers proven capabilities with demonstrated enterprise demand, where the constraint is integration capacity rather than conviction. Strategic covers the small number of capabilities that could reshape the organisation, which should be governed at board level and funded on a multi-year basis rather than annually.

The allocation across those four is yours to calculate, not ours to prescribe, but the discipline is in the arithmetic: if you cannot state what percentage of your innovation budget sits in each bucket, you do not yet have a portfolio. Two market signals should inform the balance. First, the scaling of enterprise relationships is real — 31.6% of ventures partnering with corporates in H1 2026 signed two or more distinct corporate partners inside the same half-year, up from 24.9% in H1 2021, which means the companies in your Scale bucket are being deployed by several of your peers at once. Second, the venture population feeding your Explore bucket is thinning: 282 early-stage rounds in H1 2026 against 760 four years ago.

Measurement should change with the structure. Counting pilots, startups met and events attended measures activity. What matters in an industrial market is the proportion of the portfolio aligned to stated strategic priorities, deployments and renewals rather than launches, evidence and regulatory milestones achieved, time from pilot to scale decision, and — the metric almost nobody tracks — capital recycled out of terminated programmes into funded ones.

The evidence gate: what the market is actually paying for

If capital is concentrating, it is worth knowing precisely what it is concentrating behind. Segmenting every venture that raised in H1 2026 by round size gives an unusually clean answer.

Venture Quality Scores by H1 2026 Round Size

Source: HealthTech Alpha by Galen Growth, September 2026. Scores are HealthTech Alpha proprietary 0–100 measures of clinical evidence, partnership activity, overall maturity and commercial strength. Every quality dimension rises monotonically with round size — the market is pricing proof, not narrative.

Ventures raising $100m or more scored 70% higher on Evidence and 60% higher on Partnership activity than those raising under $25m. The gap on Money score — 61.4 against 25.3 — is wider still. These are not companies that raised large rounds and subsequently became credible. They were already the most evidenced and most adopted companies in the market when they raised.

For an innovation leader, that reframes the diligence conversation. If your evaluation of a venture would produce a materially different verdict from the one the capital markets have already reached, you need to be able to say why. The most common legitimate reason is timing: you may be evaluating a company two years before the evidence base that will eventually attract institutional capital exists. That is a defensible bet, and it is precisely what a partnership is for. It is not a defensible basis for an acquisition.

The 2027 kill list

Budgets are set by addition and rescued by subtraction. Seven things are worth stopping before you allocate a pound or a dollar to anything new.

• Stop running pilots without a defined scale pathway. If nobody can name the budget line, the integration owner and the decision date that would follow a successful pilot, the pilot is a purchase of information you will not act on.

• Stop funding AI because your competitors are funding AI. The label carries no funding premium and, on the H1 2026 evidence, a modest discount. Fund the workflow, not the technology category.

• Stop treating partnership counts as an innovation metric. Signing partnerships is easy and getting easier; 1,591 were disclosed in a single half-year. Depth — second and third partnerships, renewals, deployment scope — is the signal.

• Stop building capabilities you could buy faster. With 83 acquisitions in H1 2026 and mature targets available at every scale, an internal build that takes three years to reach parity is a decision to arrive late.

• Stop assuming technical novelty creates defensibility. The categories being acquired most often are the least novel: workflow, documentation, scheduling, diagnostics infrastructure.

• Stop evaluating ventures without mapping their likely acquirers. A partner that is bought by your competitor mid-deployment is a strategic problem, not a commercial one. Ask who buys this company, and what happens to you if they do.

• Stop measuring the innovation function by activity. Pilots launched, startups screened and events attended describe effort. Deployments, renewals, evidence generated and capital recycled describe outcomes.

The uncomfortable part: today's discipline is tomorrow's pipeline gap

Everything above describes a healthier market than the one that existed in 2021. It also describes a risk that no individual organisation has an incentive to solve.

Early-stage funding rounds fell from 760 in H1 2022 to 282 in H1 2026, a 63% contraction that is steeper than the decline in the market as a whole. The companies that will be acquisition-ready in 2032 are being founded and seeded now, and there are far fewer of them. If the average path from incorporation to acquisition really is 10.7 years and lengthening, then the discipline being applied in 2026 sets the size of the opportunity set available to every corporate development team at the end of the decade.

There is a second-order version of the same problem inside the evidence data. Selecting only for companies that already have evidence rewards incumbency and age over quality: a venture founded five years ago will out-score a better one founded two years ago on any cumulative measure of trials, approvals or publications. Distinguishing evidence velocity from evidence stock is the single most useful correction an innovation team can make to its own diligence in 2027.

Two data caveats belong here as well. H1 2026 partnership and funding counts are preliminary and will revise upward as later-reported deals are backfilled — the corporate partnership figure of 1,591 should be read as a floor rather than a final count. And a partnership announcement records that a relationship exists, not its contract value or deployment scope, so the multi-partner share is the best available proxy for the shift from pilot to scale, not proof of it.

The question to answer before your 2027 budget is signed

There is one test that separates an innovation budget from an innovation wish list. Can you explain, line by line, where the money is going and why — in terms of the capability it buys, the access model it uses, the evidence it will generate and the decision it will produce?

Most 2027 budgets will not survive that test on first reading. The ones that do will share a structure: a small number of categories chosen deliberately rather than opportunistically, an explicit build, buy or partner decision for each capability, a portfolio with stated proportions and stated kill criteria, an AI allocation that includes the unglamorous infrastructure layer, and a set of measures that describe outcomes rather than effort.

The market has already decided how it allocates capital: to fewer companies, on more evidence, over longer horizons. The open question is whether corporate innovation budgets will be rebuilt on the same logic, or whether they will keep funding activity in a market that has stopped paying for it.

What this means

Four things to settle before the 2027 numbers are locked, by audience.

For investors: Use the remainder of Q4 to rebuild the 2027 deployment model around concentration rather than reacting to it next year — 6.2% of H1 2026 rounds took 58.4% of capital, and the ventures winning those rounds were already the most evidenced and most adopted in the market. Reset reserve assumptions to a decade-long path to liquidity before the LP conversation rather than after it, add partnership depth to the diligence template alongside evidence stock, and introduce evidence velocity as the correction for a metric that structurally favours older companies.

For pharma and corporate partners: Make the build, buy or partner call explicitly for each priority capability during this planning round, rather than defaulting to whichever route procurement finds easiest in March. Partnering is now the standard access model for non-differentiating capability and the most active corporates run it at volume — Nvidia and Eli Lilly and Company each disclosed 15 venture partnerships in 2026 to date. The strategic-buyer map for your priority categories is a Q4 exercise, not a 2027 one: with 83 acquisitions and a single IPO in H1 2026, the assets you will want in 2028 are being partnered with, and bought, while you are writing the budget.

For health systems and payors: Take the 2027 vendor and pilot list apart now, while there is still time to cut it: every pilot without a named scale owner, budget line and decision date is consuming integration capacity a scalable programme will need next year. Your leverage has increased and should be spent on integration terms, evidence obligations and data rights rather than pricing alone. Treat a Health Management Solutions or diagnostics partner as an infrastructure decision from day one — these are the categories with the deepest partnership activity and the highest acquisition rates, which makes both switching costs and ownership changes foreseeable rather than surprising.

For digital health ventures: Your 2027 plan is being written into the budgets of the corporates and health systems you sell to during exactly this quarter, which makes Q4 the moment to convert conversations into named line items rather than a quiet period before a January push. The bar for institutional capital has moved to evidence and adoption simultaneously, and the average disclosed round of $33.3m is going to companies that arrive with both. A second and third corporate partnership is a more persuasive proof point than a funding announcement, and a decade-long path to exit is the base case to plan runway against, not a pessimistic scenario.

Frequently asked questions

Is digital health funding declining going into 2027?

Not in capital terms. H1 2026 recorded $17.46bn of primary funding, above the $16.72bn of H1 2025 and well above the 2023 trough. What has fallen is the number of companies receiving it: 601 rounds in H1 2026 against 1,433 in H1 2022, a 58% decline. The correct planning assumption is scarcity of fundable companies, not scarcity of capital.

Should our 2027 innovation budget have an AI line item?

Not as a standalone category. Ventures that describe themselves as AI companies took 58.1% of H1 2026 rounds but only 54.0% of capital, and their average disclosed round of $30.9m sits below the $36.7m average for everything else — the claim no longer carries a premium, largely because almost every venture now uses AI in some form and saying so has stopped being a differentiator. Budget AI inside the workflows it changes, and fund the data, interoperability and model governance layer explicitly, because it is the layer that determines whether anything else works.

How should we decide between building, buying and partnering a capability?

Partner where the capability is not strategically differentiating; build only where it is differentiating and you already hold the underlying data, distribution and governance assets; buy where it is differentiating and you cannot assemble those assets fast enough. The 2026 M&A data supports the last route for mature capabilities in particular: 83 transactions worth a disclosed $5.15bn, with an average target age of 10.7 years.

Which digital health categories deserve most attention in 2027?

On the H1 2026 data, Health Management Solutions and Medical Diagnostics combine the deepest enterprise adoption (280 and 268 corporate partnerships) with the highest acquisition activity (22 and 11 exits) on moderate capital intensity. Research Solutions leads on capital by a wide margin at $5.91bn, but that is concentrated in a handful of platform-scale bets rather than broad enterprise deployment.

How long should we assume it takes a venture to reach an exit?

Plan for a decade. The average time from incorporation to acquisition rose from 8.2 years in H1 2022 to 10.7 years in H1 2026, and eight of the ten largest acquisitions in 2026 to date involved companies at least seven years old. Reserve planning, partnership horizons and acquisition pipelines should all be built on that timeline rather than a seven-year assumption.

What is the biggest strategic risk in this market?

Not excessive caution in any single organisation, but the collective effect of it. Early-stage rounds fell 63% between H1 2022 and H1 2026, from 760 to 282. On a ten-year path to exit, that contraction sets the size of the acquisition and partnership opportunity set available at the end of the decade, which is a problem for every corporate development and innovation team simultaneously.

Data source and methodology

Data source: HealthTech Alpha by Galen Growth, accessed September 2026, covering venture financing, venture–corporate and venture–venture partnership activity, M&A and exit transactions, venture profiles, technology tagging and proprietary venture scores across the global digital health ecosystem. Funding analysis covers H1 (1 January–30 June) periods from 2022 to 2026 and excludes M&A, IPO, SPAC, post-IPO equity, pre-IPO, delisted and secondaries transactions unless exit activity is being analysed directly; the acquisition table covers 1 January–31 August 2026. Figures are in US dollars.

H1 2026 funding and partnership counts are preliminary and are expected to revise upward as later-reported transactions are disclosed and classified, so year-on-year declines in transaction counts should be read as a floor. Average round sizes are calculated on disclosed amounts only. Age at exit is measured from recorded incorporation date to recorded M&A transaction date for ventures with a disclosed incorporation date. AI classification reflects HealthTech Alpha's technology tagging of the venture as a whole, not of the individual round, and captures how a venture describes and positions its technology rather than an independent audit of the models in its product.

Galen Growth is the Healthcare Innovation Intelligence company behind HealthTech Alpha. Built on proprietary data, AI-enabled workflows and expert insights, HealthTech Alpha delivers decision-grade intelligence that helps healthcare leaders identify opportunities, evaluate companies and make better strategic decisions.

Related Galen Growth analysis

• The Maturity Era: Digital Health Funding, H1 2026

• The Return of the Strategic Buyer: Digital Health M&A, H1 2026

• Healthcare Is Buying Infrastructure, Not Apps

• H1 2026 Digital Health Trends: Why Partnerships Matter More Than Funding

• Digital Health Funding 2026: Ventures with Strong Clinical Evidence Raise 3.5x More

Disclaimer

This analysis is provided solely for informational purposes and was prepared in good faith on the basis of public information available at the time of publication without independent verification. Numbers will be updated from time to time to reflect information identified after the event. Galen Growth does not guarantee or warrant the reliability or completeness of the data nor its usefulness in achieving any particular purposes. Galen Growth shall not be liable for any loss, damage, cost or expense incurred by any reason because of any person's use or reliance on this report.

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