Beyond Subscription: The Business Model Case for AI-Native Vertical EHRs (Part 2)

Sam Toole is an entrepreneur and operator turned investor with NYC-based Primary Ventures.

In Part 1 of this series, we laid out why we believe AI-native, vertical EHRs could represent one of the more interesting bets in healthcare software right now. We described the structural dynamics that make certain specialties worth targeting: provider independence, workflow complexity, administrative burden, and competitive fragmentation. 

‍We closed with a question we've been spending time on since: does the EHR market need business model innovation to be truly venture scale? 

‍The “SaaSpocalypse” has made this question hard to ignore. If the terminal value of the world's largest software companies is being written down, verticalized ambulatory EHR software is not immune.

‍At its core, the "SaaSpocalypse" debate is a structural one: when AI can automate the workflows that per-seat software was built to support, does the subscription model hold? For vertical EHRs, the question cuts even deeper. These platforms sit on top of an enormous clinical context and currently do almost nothing with it. AI doesn't just put pressure on the subscription model. It opens the door to a better one, priced on consumption rather than seats.

‍That pressure has direct implications for the incumbents. The last wave of EHR PE (Thoma Bravo's acquisition of NextGen, Warburg's backing of ModMed, Francisco Partners' ownership of AdvancedMD) was underwritten on a familiar thesis: sticky subscriptions, low churn, customers too entrenched to migrate. If AI-native entrants show up with better software at a cheaper price and a business model that makes money elsewhere, how much of that stickiness really holds?

‍The EHR business model status quo

‍Most vertical EHRs today charge per provider, per seat, or as a flat monthly fee. It's a clean model: predictable, easy to price, easy to negotiate. But we believe it also dramatically underprices the value that an EHR, sitting at the center of a practice's workflow, is actually positioned to deliver.

‍EHRs capture an immense amount of data: every prescription decision, every diagnosis code, every prior auth submission, every referral, every lab order, every payer interaction, every billing event. And yet they do almost nothing with it, which is reflected in their pricing. Ambulatory EHRs capture 1-2% of the revenue a practice generates. The data live in the EHR, but the actions and labor happen elsewhere.