We replay your designation portfolio digitally.
Before you buy anything, we bootstrap your AI-algorithm inventory and rebuild your compliance position from documents, attestations, public data, and exports you already own — and hand you the receipts. No EHR integration required. No implementation project. Every number below is traceable to a public source, and everything modeled says so.
The readiness spend is already seven figures. The proof is what’s missing.
Four receipts, built from data you already have.
The digital pilot is not a demo environment with fake dashboards. It is your designation portfolio, replayed once you share the exports: which algorithms are running in your house without an owner, what each designation is worth defending, how your team would perform on survey day, and how many registrar hours your case volume actually costs.
1. Per-Designation Revenue at Risk
For each designation you hold — trauma, stroke, cancer, Baby-Friendly — we model the revenue that designation gates, from public sources: CMS DRG tables, peer-reviewed service-line studies, and your own Medicare cost report. A comprehensive stroke center’s thrombectomy program alone bills MS-DRG 023 at $41,698 per case; at median volumes that is a modeled ~$2–3M a year riding on one certificate. Every figure is labeled: public fact or modeled estimate.
2. Mock-Survey Drill Replay
Incumbent consultants charge $25K for a single-site pre-survey and up to $151K for a network-wide engagement — real federal purchase orders. The pilot runs your team through a timed, scored walking drill of the same tracer methodology, digitally: cited touchpoints, found/missed scoring, a readiness debrief with the derivation shown. Drill results are sandboxed by construction — practice never touches your evidence chain.
3. Registrar Amplification Model
The peer-reviewed baseline is ~39 minutes of abstraction per trauma case before acuity multipliers. We model your registry backlog from your case volume, then show the abstract-once, submit-everywhere workflow that amplifies the registrar you already have — registry-shaped exports from a single attested abstraction, receipts included. Each export declares the documented shape it targets; registry acceptance is the registry’s call, and we never claim it for them.
4. AI-Algorithm Inventory Bootstrap
Certification for responsible AI use launched in June 2026 — and surveyors are no longer the only ones asking. The AI-scribe and payer-algorithm suits filed through 2025–2026 open on the same question most hospitals cannot answer: which algorithms are running, and who owns each one? In the pilot, we build your vendor-model inventory with you from the documents you already have — named owners, intended use, and the evidence trail a surveyor will ask for.
A published five-figure price, against a quote-only mid-six-figure basket.
The readiness stack hospitals actually assemble — a survey-tracking cockpit, standards manuals, a policy tool, and a mock survey each cycle — runs mid-six-figures per survey cycle, none of it cross-certifier, all of it quote-only. Real federal purchase orders put the cockpit alone at ~$234K a year and mock-survey consulting at $25K per site — to $151K network-wide. We publish a five-figure price that lands under the $100K board-approval line hospitals write into their purchasing policies — and the digital pilot is how you check our math before spending any of it.
| Incumbent line item | Obligated cost | Source |
|---|---|---|
| Survey-tracking cockpit (enterprise license) | ~$234K / yr | USAspending.gov, DoD, 2017–2021 |
| Standards-manual subscription | ~$67K / yr | USAspending.gov, VA, 2023–2026 |
| Readiness consulting engagement | $177K–$285K | USAspending.gov, VA, 2008–2015 |
| Mock survey (single site → network-wide) | $25K–$151K | USAspending.gov, VA/DoD, 2009–2011 |
| Charlie Owl | Published five figures | Cross-certifier, priced under the board line |
We show our work. Every number is traceable.
Limitations & Honest Disclosures
- Public facts vs. modeled estimates: the $2.33M readiness cost, the federal purchase-order prices, the ~39-minute abstraction baseline, and the designation counts are public, sourced figures. Per-designation revenue-at-risk for a specific hospital is a modeled estimate built from CMS DRG tables and per-1,000-patient peer-reviewed studies — it becomes your number only when you hand us your numbers.
- Dated dollars: the mock-survey purchase orders are 2009–2011 dollars; service-line revenue studies are ~2015–2018 dollars. We do not inflation-adjust them — the real figures today are likely higher.
- The loss anchor is honest, not precise: no published study since 2015 isolates the revenue lost specifically from losing a designation. The defensible anchors are CMS termination cases — hospitals that lost Medicare standing and then their census, payer contracts, or the building.
- The stakes are outcomes, not only dollars: a designation is the verified promise a service line works. The public evidence on losing one is real and honestly associational — in a large-vessel stroke an estimated 1.9 million neurons are lost per untreated minute (a modeled figure; Saver, Stroke 2006); injured patients whose drive time rose after a nearby trauma-center closure had 21% higher adjusted odds of in-hospital death (associated with, not caused by; Hsia et al., J Trauma Acute Care Surg 2014); and remote rural counties that lost obstetric services saw more preterm births the following year (+0.67 pp, an interval that nears zero; Kozhimannil et al., JAMA 2018). We cite these as stakes, not as claims the studies do not make.
- The board-line claim is inferred: published public-hospital purchasing policies converge on ~$100K board thresholds; no policy literally promises a sub-$100K purchase skips review.
- Litigation is cited as filed, not as decided: the payer-algorithm and AI-scribe matters we reference are public court filings with outcomes still pending — Kisting-Leung survived a motion to dismiss, it did not win. The $556M Kaiser settlement is a chart-review False Claims Act matter and we do not count it as an AI case. None of this is legal advice.
- No EHR integration, by design: the pilot runs on documents, attestations, public data, and exports you already own. Nothing in it depends on connecting to your EHR.
What we stand behind: every architecture claim in this pilot is backed by real code in the repository — the drill replay, the registry-shaped exports, the tamper-evident receipts. The market figures are cited to their public sources above. The modeled estimates are labeled modeled. The engineering is not an estimate.
Want to run your own numbers?
We will build a custom digital pilot for your hospital using your designation portfolio, your Medicare cost report, and the registry exports you already own. Every assumption will be visible. Every calculation will be auditable. No black boxes.
Community hospitals defending trauma, stroke, or specialty designations get priority.