All-in monthly software cost per provider

EMR comparison

The number that matters to a practice is the all-in cost per provider per month — base subscription plus the AI / ambient scribe, plus the add-ons and fees that only surface on the MSA. REV is all-inclusive and all-published: one rate-card price with the ambient scribe already in it. Incumbents pile on AI fees and extras you only discover at contract, pushing their all-in past $1,000/provider/mo.

Want the full model? The EMR / RCM deep dive → nets out revenue lost to miscoding and weak RCM to show net revenue to the practice — REV is #1 on both TCO and net.

REV all-in ≈ $595/mo. Nearest competitor all-in >$1,000/mo once AI + extras are added. Every REV cost line is on a published rate card; most competitor lines are Only on MSA — i.e. only in the Master Service Agreement: quote-based, and you only see the real number when you’re signing the contract.

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All-in software cost / provider / month

Every cell is tagged Published (on a list / rate card) vs Only on MSA (quote-based, surfaces at contract). Any competitor figure that is not publicly citable is marked est. REV is highlighted.

Published on a public rate card Only on MSA quote-based / discovered at contract est. not publicly citable — our estimate

Vendor	Base subscription	AI / ambient scribe	Other / hidden	All-in $/provider/mo	RCM

RCM: turn-key vs co-sourced

REV: 4.9% of collections, turn-key (Published, ~90% attach) — REV runs the full revenue cycle; the practice does not staff billing. athenahealth: 4–7% of collections, co-sourced (Only on MSA) — the rules engine scrubs claims, but the practice still has to hire its own billing coordinator to work denials and exceptions. That extra headcount is a real cost that never shows up on athena’s sticker price, and it is why a low software floor (~$140/mo) does not mean a low all-in cost.

Why REV is also more efficient

REV internal data / modeled, not audited

Lower price is only half the story. REV’s architecture does more with the same minute — the following are REV’s own modeled figures, not third-party audited.

+20%

Per-minute resource-graph scheduling

Scheduling is solved as a per-minute resource graph rather than fixed slots — ~20% more scheduling efficiency.

≥15%

ML-based, not rules-based

The engine learns instead of running static rules — at least 15% more efficient than anything we evaluated.

∞

Every encounter improves the system

Each encounter feeds back into the models, so accuracy and efficiency compound over time.

Now

Newly affordable

This approach was too costly to attempt a few years ago; the economics only recently made it buildable.

Sources / our homework

Per-vendor source pointer and confidence, mirroring the comparison dataset we maintain (emr-compare-public + EMR Comparison workbook).

Disclaimer: pricing is NDA’d / quote-based for several vendors. Published figures come from public rate cards; everything else is a planning est. and is labeled as such — not a vendor quote. Competitor all-in ranges reflect base + AI + typical extras and will vary by volume and negotiation. REV figures are internal published pricing.