115 acquisitions. 71 in Q2. Zero public exits in H1.

That is one of the clearest strategic signals in U.S. digital health in 2026.

Rock Health counted 115 acquisitions during the first half of the year, with 71 announced in Q2, making it the busiest digital-health M&A quarter since Q3 2021. After seven public exits in 2025 under Rock Health's later H1 2026 market framing, none had occurred in the first half of 2026.

At the same time, venture capital has not disappeared. U.S. digital-health companies raised $7.4 billion across 244 deals in H1 2026, up roughly $1 billion year over year. But 20 mega-rounds absorbed 45% of the capital. Funding and exit activity are therefore both becoming more concentrated around companies that can demonstrate scale, differentiation and commercial durability.

For a founder, I think that changes the question.

Not:

"Could we eventually IPO?"

And not:

"Do we have interesting technology?"

The more useful question is:

What would make another company prefer to buy us rather than build around us, copy us, partner with us or wait for us to run out of capital?

That is what my H1 2026 U.S. Digital Health Acquirer Map is designed to explore.

AI alone is becoming a weaker moat

There is an uncomfortable implication beneath the 2026 numbers.

AI is increasingly becoming an operating assumption rather than a sufficient differentiator.

Rock Health's H1 analysis highlighted domain expertise, broader workflow ownership, hands-on deployment and network effects as increasingly important sources of advantage as basic AI capability becomes easier to reproduce.

PwC reaches a similar conclusion from an M&A perspective.

Its 2026 software valuation work argues that defensibility is increasingly found beyond code, particularly in domain depth, ecosystem entrenchment, proprietary context and what it calls mission-critical "workflow gravity." PwC also warns that conventional SaaS retention metrics require more scrutiny in an AI-disrupted market and suggests buyers examine GRR alongside NRR to understand the underlying durability of the customer base.

For healthcare specifically, PwC says buyers are prioritizing scalable, cash-generating platforms with margin durability, reimbursement visibility and execution readiness, while AI valuation support increasingly requires measurable operating impact rather than pilot-stage promise.

That gives us a more useful definition of acquirability.

My 6-part HealthTech Acquirability Test

I would score a company across six assets:

RECURRING REVENUE → RETENTION → WORKFLOW OWNERSHIP → ROI → DISTRIBUTION → DATA + IP

These are related, but they answer different buyer questions.

1. Recurring revenue

The first question is simple:

What exactly is being acquired?

If most revenue comes from:

• temporary pilots
• implementation projects
• founder-led consulting
• one-off research
• custom integrations
• grant-funded projects

then a buyer may value the business very differently from a company with predictable, renewable revenue.

The useful breakdown is not simply:

"$5M revenue."

I would show:

Revenue quality matters because acquisition economics depend on what continues after the founders leave.

2. Retention

A strong acquisition target should make the buyer think:

"Customers are unlikely to disappear when ownership changes."

I would track:

Gross Revenue Retention

Net Revenue Retention

Logo retention

renewal duration

expansion by cohort

product-module adoption

and:

customer concentration.

PwC specifically notes that GRR can reveal contract durability more clearly than NRR when AI upsells may mask underlying seat or product contraction.

A company with:

120% NRR

but:

78% GRR

may have a different risk profile from one with:

105% NRR

and:

96% GRR.

The second business might be strategically more durable.

3. Workflow ownership

This may become one of the most important acquisition variables in AI-enabled healthcare.

A feature can be copied.

A workflow is harder to displace.

Consider the difference between:

"Our AI generates a billing recommendation."

and:

"Our platform sits between eligibility, authorization, coding, claims submission, denial management and collections across 500 provider organizations."

The second asset owns more operational context.

That creates:

data

switching friction

integration depth

customer trust

cross-sell potential

and potentially:

pricing leverage.

PwC's healthcare outlook specifically identifies revenue cycle, workflow, utilization and engagement technology as attractive where AI impact is already proven in operating KPIs.

RCM demonstrates what workflow consolidation looks like

Revenue-cycle management has been one of the clearest consolidation themes in 2026.

IKS Health agreed to acquire TruBridge in a $557 million transaction, combining IKS's care-enablement capabilities with TruBridge's RCM and EHR footprint across rural and community hospitals. The combined organization was expected to support more than 150,000 clinicians and roughly 2,000 healthcare organizations.

Innovaccer acquired CaduceusHealth, adding RCM services and staff to an existing AI/data platform rather than simply buying another isolated algorithm.

Collectly acquired Pledge Health to add pre-service workflows including eligibility verification, estimates, financial clearance and payment setup to its existing patient billing and engagement platform.

Med-Metrix also agreed to acquire Vitalware from Health Catalyst in June.

The pattern matters.

These are not simply:

"AI buys AI."

They increasingly look like:

workflow A + workflow B = broader operating layer.

4. Measurable ROI

This is where I think many HealthTech companies still undersell themselves.

"Improves efficiency" is not transaction-grade evidence.

Translate it.

Instead of:

improves documentation

show:

minutes removed per encounter

after-hours work reduced

coding completeness

additional patient capacity

revenue captured.

Instead of:

improves patient engagement

show:

retention

adherence

conversion

appointment completion

cost-to-serve.

Instead of:

improves RCM

show:

denials prevented

days in A/R

cost-to-collect

staff hours

net revenue recovered.

PwC says ROI proof points are now central to health-services technology valuation and that pilot-stage AI claims are increasingly insufficient to support valuation premiums.

The founder equation should therefore become:

Customer Value = Revenue Gained + Cost Removed + Capacity Released + Risk Avoided

5. Distribution

Sometimes the thing being acquired is not primarily the technology.

It is:

the customers

the clinical network

payer contracts

consumer reach

geographic footprint

employer relationships

provider distribution

or:

sales channel.

Hims & Hers' 2026 acquisition of Eucalyptus, valued at up to $1.15 billion, is a useful example. Eucalyptus entered the transaction with an annualized revenue run rate above $450 million and operations across Australia, the UK, Germany, Canada and Japan. Hims explicitly framed the deal around international reach, local expertise and a larger closed-loop consumer ecosystem.

That is much more than a software acquisition.

It is:

REVENUE + DISTRIBUTION + LOCAL OPERATING CAPABILITY.

UHS and Talkspace show the same logic from the provider side

Universal Health Services agreed in March to acquire Talkspace for approximately $835 million enterprise value and completed the transaction in August.

Talkspace had generated $229 million of 2025 revenue, delivered more than 1.6 million therapy and psychiatry sessions, and was available to more than 200 million people through insurance, employer, school or government channels. UHS framed the combination around linking virtual behavioural health with its physical behavioural-health, acute-care and outpatient network.

Again, the buyer gets:

technology

plus:

network

plus:

distribution

plus:

care continuum.

That combination is much harder to replicate than an app feature.

6. Data + IP

The sixth layer is increasingly important because AI code itself is becoming easier to reproduce.

The diligence question becomes:

What does the target legally and operationally own that cannot simply be recreated?

Examples:

proprietary datasets

exclusive data rights

longitudinal context

clinical validation

integrations

embedded workflow history

specialized models

terminology assets

regulatory clearances

patient identity infrastructure

domain expertise

and:

IP ownership.

PwC's broader software analysis makes the same point: durable software moats increasingly sit in proprietary context, domain depth, ecosystem position and workflow entrenchment rather than code alone.

Health data M&A demonstrates this clearly

HealthVerity completed its acquisition of Symphony Health in May, combining HealthVerity's clinical-data infrastructure with Symphony's commercial-healthcare datasets and analytics. HealthVerity explicitly described the rationale as creating a more connected clinical and commercial view of patients and providers.

Verana Health merged with COTA in January, expanding its real-world-data footprint. The combined company said it would serve 17 of the top 20 global biopharma companies and gain access to data covering more than 95 million patients.

Those are useful signals for founders building data businesses.

The strategic asset is not:

"We have a dashboard."

It is:

DATA RIGHTS × DEPTH × CONTEXT × ACCESS × WORKFLOW.

Clinical workflow buyers are also buying capability

Chartis acquired Leap AI in March to expand AI-enabled healthcare product development and workflow automation capabilities.

Health Recovery Solutions acquired Rimidi, adding ambulatory chronic-disease expertise, continuous-glucose-monitoring capabilities and deeper EHR/workflow integration to HRS's remote-care platform.

This gives us another M&A model:

Installed distribution + missing capability = acquisition thesis

A smaller company does not necessarily need to become a $1B independent platform if it owns something a larger platform urgently lacks.

Diagnostics show the value of workflow + IP

Roche's proposed acquisition of PathAI is perhaps the clearest example in the diagnostics category.

Roche agreed to pay $750 million upfront plus up to $300 million in milestones for PathAI. The companies had already been partners since 2021, and Roche highlighted PathAI's image-management platform, AI pathology capabilities and ability to complement its existing digital-pathology and companion-diagnostics business.

That sequence is worth noting:

PARTNERSHIP → VALIDATION → STRATEGIC FIT → ACQUISITION

Founders often think buyer relationships start when they hire an investment bank.

In reality, strategic familiarity can begin years earlier.

Strategic relationships are part of exit readiness

That does not mean founders should approach every partner as a future buyer.

It means acquisition optionality is stronger when likely buyers already understand:

the product

the customer value

the team

the integration

and:

the strategic adjacency.

This is why I see revenue pipeline work and exit-readiness work as more connected than they first appear.

A strategically selected hospital, payer, platform or partner can create:

revenue now

proof

distribution

industry references

and sometimes:

future buyer familiarity.

The six acquirer pools I would monitor

The visual is designed as a buyer/sponsor research universe, not as a claim that every logo completed an acquisition in H1 2026.

I would structure the universe as follows.

I have treated ambiguous logo-only marks in the graphic as a reason to clean the directory rather than invent brand identities. These are market-watch companies and sponsors, not a declaration that all 60 are currently seeking acquisitions.

What is private equity looking for?

The PE story also needs nuance.

PwC says 2026 healthcare buyers are more selective, with underwriting increasingly focused on cash generation, reimbursement visibility, margin durability and executable value creation within roughly 12 to 24 months.

It specifically sees continued opportunity in healthcare IT where revenue cycle, patient access, infrastructure optimization and AI-enabled automation can produce sustainable EBITDA growth. In RCM, PwC expects AI-driven bolt-ons across areas such as prior authorization, coding and denials to remain a primary route for building larger platforms.

The founder implication is important.

PE generally does not need your technology to sound futuristic.

It needs to understand:

HOW DOES THIS BECOME MORE PROFITABLE, MORE SCALABLE OR MORE VALUABLE AFTER OWNERSHIP CHANGES?

The valuation benchmark needs context

Berkery Noyes tracked 201 Healthcare/Pharma Information & Technology transactions in H1 2026 and reported a median disclosed revenue multiple of about 3.5×, down slightly from 3.6× in H2 2025.

That does not mean:

every digital-health startup is worth 3.5× ARR.

It is a broad transaction dataset.

Company-specific valuation can vary dramatically with:

growth

profitability

revenue mix

clinical/regulatory risk

customer concentration

strategic scarcity

gross margin

retention

and:

buyer synergies.

That is why I use 3.5× only as an editable reference input in the accompanying calculator, not a valuation recommendation.

A more useful valuation equation

For founders, I would separate:

Standalone Value

from:

Strategic Value

A buyer may underwrite:

existing revenue

plus:

cross-sell

plus:

cost synergies

plus:

time saved versus building

plus:

customer/channel access

plus:

IP/data value

minus:

integration risk

minus:

concentration risk

minus:

regulatory / reimbursement exposure.

That is why two companies with identical ARR can attract very different offers.

Example: $4M ARR does not automatically mean $14M of acquisition value

Suppose a startup has:

$4M repeatable revenue

and someone uses a broad:

3.5× revenue benchmark.

That gives:

$14M illustrative enterprise value

But now compare two businesses.

Company A

$4M ARR
45% growth
95% GRR
115% NRR
75% gross margin
10% largest-customer concentration
workflow embedded in the EHR
measured $3M customer ROI

Company B

$4M revenue
45% growth
80% GRR
95% NRR
45% gross margin
40% largest-customer concentration
large implementation team required
no quantified customer ROI

Both can say:

"$4M revenue."

A sophisticated buyer will not treat them as equivalent.

Customer concentration can quietly destroy leverage

Suppose your largest customer represents:

30% of ARR.

A buyer now needs to underwrite:

renewal risk

change-of-control risk

pricing power

implementation dependence

and:

whether the customer relationship belongs to the company or to the founder.

That is why the calculator separately shows:

ARR × Top-Customer Concentration

If $5M ARR includes $1.5M from one customer, the diligence conversation will probably reach that contract quickly.

Runway matters too

Exit readiness is not only about being attractive.

It is also about having enough leverage to say:

No.

Suppose monthly burn is:

$300K

and a weak process delays strategic options by nine months.

Runway exposure:

$300K × 9 = $2.7M

A company with six months of cash can look very different to an acquirer from exactly the same company with 24 months.

The product did not change.

Negotiating leverage did.

This is why I would build buyer relationships before an exit process

Imagine a company identifies:

25 plausible strategic buyers.

But only:

28% actually have strong product, workflow or distribution adjacency.

That leaves:

7 genuinely high-fit accounts.

If senior relationships currently exist at only 40% of them:

roughly 3 are meaningfully covered.

That gap is more useful than knowing 500 healthcare company names.

It tells the founder where commercial relationship-building should happen next.

What founders should build 12 to 24 months before an exit

I would create six diligence-ready evidence packs.

Then add a seventh:

Buyer Synergy Map

For every serious strategic buyer:

What do they already own?

What are they missing?

What would we add?

Could they build it?

How long would that take?

Which customers could they cross-sell us into?

Which of our customers matter to them?

What data/workflow advantage transfers?

That is much closer to an acquisition thesis than an investor pitch deck.

What executives at the companies on the map should look for

For strategic buyers, the map can also work in reverse.

Instead of asking:

"Which startup has the most impressive AI?"

I would ask:

Where is the portfolio incomplete?

Which workflow do customers currently leave the platform to perform?

Where are customers buying another vendor?

That may be a stronger acquisition signal than technology alone.

Which product could increase retention?

An adjacent acquisition may reduce churn even if it is not a massive standalone business.

Which acquisition opens a new channel?

Hims/Eucalyptus illustrates this clearly.

Which dataset makes the existing platform smarter?

HealthVerity/Symphony illustrates this logic.

Which clinical capability is too slow to build internally?

Roche/PathAI illustrates this route.

What investors should diligence before the next round

If I were evaluating exit optionality at Series A, B or C, I would ask:

1. Who are the five most logical strategic buyers today?
2. Why would each buy rather than partner?
3. What part of the business survives without the founders?
4. What is GRR, not just NRR?
5. What percentage of revenue is recurring?
6. What percentage comes from the top three customers?
7. What economic outcome can customers quantify?
8. Which workflow does the product actually control?
9. Which data/IP rights survive change of control?
10. Does customer #20 become easier to acquire than customer #5?

That is a much more useful exit-readiness conversation than:

"M&A is hot."

My 90-day founder framework

Days 1-30: quantify

Build:

ARR/repeatable revenue bridge

GRR + NRR cohorts

gross-margin bridge

customer concentration

customer ROI

and:

implementation cost.

Days 31-60: identify

Map:

25 strategic buyers / channel partners

and:

15 decision-makers

across:

corporate development

strategy

product

commercial

clinical

data

and:

operating leadership.

Days 61-90: strengthen adjacency

Do not pitch:

"Would you acquire us?"

Create legitimate commercial reasons to engage:

partnership

integration

enterprise sale

co-selling

data collaboration

distribution

or:

product adjacency.

A future transaction is healthier when it emerges from genuine strategic fit.

Where I can help

I do not see my role here as telling a founder:

"Go sell the company."

And I am not positioning the HealthTech Buyer Pipeline Sprint as an M&A advisory service.

The missing commercial layer I can help with is earlier:

Which companies have a reason to care about what you have built?

That means mapping:

25 priority healthcare buyers / strategic partners

plus:

15 relevant decision-makers

around:

workflow adjacency

customer overlap

distribution

market access

buyer economics

and:

commercial timing.

That can help generate revenue today while also reducing the number of future "strategic buyers" that exist only in a spreadsheet.

HealthTech Buyer Pipeline Sprint: 25 Buyers + 15 Decision-Makers

Final takeaway

The useful lesson from 115 acquisitions and zero H1 public exits is not:

"Every HealthTech founder should sell."

It is:

BUILD THE BUSINESS THAT SOMEBODY WOULD RATHER BUY THAN RECREATE.

In 2026, that increasingly means:

repeatable revenue

× durable retention

× workflow ownership

× provable ROI

× distribution

× defensible data/IP

The best outcome is not necessarily an acquisition.

The best outcome is optionality.

A company with those six assets is usually better positioned to:

raise

sell

partner

grow independently

or:

walk away from a weak offer.

That is a much stronger position than building specifically for an exit.