Specialty-specific EHRs are back

The pendulum swing

Horizontal EHRs won the last decade by winning enterprise contracts. Their weakness — depth in any single specialty — has become their vulnerability.

Where the new entrants are winning

Behavioral health, women's health, pediatric specialty care, and value-based primary care are all seeing specialty-native EHRs displace horizontal incumbents.

The AI overlay

Specialty EHRs are unusually well positioned to embed clinical AI natively, because the workflow is well understood. Horizontal EHRs have to serve too many masters to keep up.

The strategic question

Will these specialty EHRs consolidate into a new horizontal platform, or remain vertical champions? The answer will shape the next decade of clinical software.

The virtual-first economics finally work

For most of the last decade, virtual-first models struggled to hit unit economics that a payer would underwrite at scale. That is changing. The combination of ambient documentation, asynchronous triage, and specialty-specific care pathways has pushed provider capacity up and cost-to-serve down enough that a well-run virtual practice is now defensibly cheaper than the in-person alternative for a growing set of conditions.

The winners are the teams that resisted the temptation to be everything to everyone and instead pointed the entire operation at a single population until the CAC-to-LTV curve was decisively positive.

Distribution is still the moat

Product beats no product. Distribution beats product. The digital health graveyard is full of clinically superior tools that could not get in front of the patients they were built for. The founders winning in 2026 are the ones who chose a distribution channel — an employer, a health plan, a specialty group, a condition-specific community — and built the product for that channel from day one.

The economics underneath the demo

A demo is a snapshot of the best hour of a system's month. Enterprise economics are a function of the worst hour. The teams pricing themselves confidently in 2026 have done three things: they have measured deflection or throughput impact against a matched baseline, they have quantified the reviewer or clinician time returned per shift, and they have translated both into the currency the health system already uses in its own budget cycle.

Where founders lose margin is in the gap between what the model costs to run at peak and what it delivers on the median case. Inference cost curves are helping, but not fast enough to bail out a business built on a demo-day accuracy number. Underwriting a deployment requires a distribution, not a headline.

Expect procurement to get sharper about this in the next two cycles. The health systems that were embarrassed by 2023-era pilots have hired the people who will ask the harder questions in 2026.

Why the incumbent playbook keeps failing

The instinct of a large healthcare organization is to procure a platform, run a governance committee, and let the technology diffuse through mandate. That playbook worked for imaging PACS in the 2000s. It has failed, visibly and expensively, for the current wave of AI-native tooling. The reason is structural: modern systems have to be tuned to the institution's own data, workflow, and liability posture, and that tuning is a product-engineering exercise, not a procurement exercise.

Founders who understand this shape their commercial motion around a technical champion inside the health system — usually a CMIO, a service-line chief, or a director of quality — and treat every deployment as a co-development contract with clear evaluation gates.

The corollary is that the sales cycle is longer than any founder wants to admit, and the winners raise capital that lets them survive twelve months of pilot without a single dollar of expansion revenue.

The field notes

Across the last quarter we sat in on operating reviews with fourteen portfolio and prospective teams working adjacent problems. Three patterns kept surfacing. First, the teams that moved fastest were not the ones with the deepest research bench — they were the ones with the shortest feedback loop between a real clinical user and the roadmap. Second, the winners had unusually opinionated evaluation harnesses. Third, none of them treated regulatory strategy as a phase; they treated it as a running conversation with the product.

What follows is a longer look at what we saw, what we think it implies for founders, and where we are actively deploying capital and studio effort in the coming twelve months.