Manifesto AI — Clinical Impact & Business Case

Why this matters clinically, operationally, and financially

1. Clinical Impact

The problem is not ignorance — it is inaptitude

"We have accumulated stupendous know-how... yet avoidable failures remain common, because the know-how is not applied correctly, consistently, or safely."
— Atul Gawande, The Checklist Manifesto
44-98K
Deaths/year from preventable medical errors
IOM, "To Err Is Human"
4.8%
Surgical adverse events from communication failures
WHO Surgical Safety Checklist
70%
Sentinel events with communication as root cause
Joint Commission
90%+
BPA alert override rate
JAMIA 2019

What Manifesto AI Prevents

Failure Mode How It Happens Today How Manifesto AI Prevents It
Wrong antibiotic given Allergy buried in chart; clinician doesn't review full history Surfaces allergy + cross-reactivity in pre-procedure brief
Bleeding crisis in OR Anticoagulant not held; lab results missed in 200-page chart Flags active anticoagulants, last INR, and hold recommendations
Day-of cancellation NPO instructions not followed; pre-op labs expired Generates patient-specific prep checklist days before procedure
Post-op DVT/PE VTE risk not calculated; prophylaxis not ordered Auto-calculates Caprini score, recommends prophylaxis protocol
Perioperative hypoglycemia Insulin regimen not adjusted for NPO status Alerts to diabetes medications requiring peri-procedural adjustment
Latex reaction in OR Allergy documented in notes but not flagged in OR setup Includes latex allergy in pre-procedure alert with OR setup implications

Evidence Base: Surgical Checklists Work

Study Setting Key Finding Source
WHO Safe Surgery Saves Lives 8 hospitals, 8 countries 36% reduction in major complications; 47% reduction in mortality NEJM 2009
Michigan Keystone ICU 103 ICUs, Michigan 66% reduction in central line infections; sustained over 18 months NEJM 2006
Safe Surgery 2015 South Carolina 22% reduction in mortality with checklist implementation Ann Surg 2015
Ontario Surgical Quality 101 hospitals, Ontario Checklist compliance correlated with lower complication rates (r=-0.31) CMAJ 2014

Key Insight

Static checklists are one-size-fits-all paper forms. Manifesto AI generates dynamic, patient-specific checklists that adapt to each patient's conditions, medications, allergies, and procedure type — capturing the benefits of checklists while eliminating their key limitation: generality.

2. Operational Impact

Time saved, cancellations prevented, workflows streamlined

20 min
Saved per patient on pre-procedure preparation
Estimated from workflow analysis
3-5%
Day-of cancellation rate (preventable)
Industry benchmark
5 hrs
Reclaimed daily across perioperative team
Projected from time savings model

Time Savings Model (minutes per patient)

Pre-Op Coordinator
Before
20 min
After
5 min
Pre-Op Nurse
Before
12 min
After
4 min
Anesthesiologist
Before
8 min
After
3 min
Surgeon
Before
5 min
After
2 min
OR Charge Nurse
Before
15 min
After
5 min
Before (manual review) After (Manifesto AI)

Cancellation Prevention

Cancellation Reason % of Cancellations Manifesto AI Preventable?
Incomplete pre-op workup / expired labs 25-30% Yes
NPO violation 10-15% Yes
Medication not held (anticoagulants) 10-12% Yes
Missing consent / documentation 8-10% Yes
Patient no-show 15-20% Partial
Acute illness / clinical change 15-20% No
Scheduling / resource conflict 10-15% No

3. Business Case

Hard-dollar savings and revenue recovery

Cost of a Single Surgical Cancellation

$2,790
OR Time Wasted
~30 min @ $93/min average
~$1,500
Staff Idle Cost
Surgeon, anesthesia, nursing, techs
$5K-$50K
Revenue Lost
Depends on procedure complexity

Annual Impact Model (Interactive)

400
Current Annual Cancellations
200
Cancellations Prevented
$3,000,000
Revenue Recovered
2.4
FTE Equivalent Saved

ROI Projection (12-Month View)

$500K $400K $300K $200K $100K $0 1 2 3 4 5 6 7 8 9 10 11 Month
Cumulative Savings Cumulative Cost Net Value

4. Market Opportunity

A massive, underserved market ready for disruption

$37B
Total Addressable Market
Clinical Decision Support + Perioperative IT
$4.2B
Serviceable Addressable Market
US hospitals with Epic EHR, surgical volume >5K/yr
$180M
Serviceable Obtainable Market
Year 5 target: 150 hospital systems

Why Now?

Factor What Changed Why It Matters
21st Century Cures Act Mandates open APIs for EHR data (FHIR) Enables third-party access to patient data without custom integrations
Epic App Orchard / Cosmos Epic's marketplace now supports third-party clinical apps Distribution channel to 250M+ patient records
Alert fatigue crisis 90%+ override rates on BPAs; clinician burnout at all-time high Hospitals actively seeking alternatives to interruptive alerts
Staffing shortage Post-COVID nursing shortage; 100K+ RN deficit projected Automation of cognitive tasks is no longer optional
Value-based care CMS shifting from fee-for-service to outcomes-based payment Hospitals financially incentivized to reduce complications

5. Go-to-Market Strategy

Prove, validate, scale

Phase 1 — Months 1-6

Prove

Single hospital pilot. Deploy in 1-2 surgical departments. Measure time savings, catch rate, and cancellation reduction. Build clinical evidence.

Phase 2 — Months 6-12

Validate

Expand to 3-5 hospital systems. Publish clinical results. Build case studies. Establish pricing model based on demonstrated value.

Phase 3 — Year 2+

Scale

Epic App Orchard listing. National sales team. Multi-specialty expansion. Platform APIs for health system customization.

Pricing

Starter

$8K
per month

Single department, up to 200 cases/month. Includes standard protocols and email support.

Enterprise

$20K
per month

Hospital-wide deployment. Custom protocols, analytics dashboard, dedicated CSM, EHR deep integration.

Per-Case

$15
per case

Volume-based pricing for large systems. No minimum commitment. Scales with surgical volume.

6. Defensibility

Why can't Epic just build this?

Dimension Epic Manifesto AI
Release cycle Quarterly updates; 12-18 month feature timelines Continuous deployment; weekly protocol updates
Incentives Sell software licenses; minimize support burden Reduce errors and cancellations; aligned with outcomes
Specialization General-purpose EHR covering all workflows Purpose-built for perioperative intelligence
Iteration speed Changes require committee review across 500+ clients Protocol updates deployed same-day based on evidence
Protocol maintenance Static order sets maintained by each hospital individually Centralized, evidence-based protocol library updated continuously

The Real Moat

Who's Tried and Failed?

Company / Approach What They Did Why They Failed
Generic CDS vendors Rule-based alerts triggered on orders Alert fatigue; 90%+ override rates; no synthesis
Checklist apps (paper digitization) Turned paper checklists into tablet forms Not patient-specific; no EHR integration; extra work for clinicians
NLP chart summarizers AI-generated summaries of chart notes Summarization without clinical logic; no actionable recommendations
Hospital-built internal tools Custom Epic reports and SmartPhrases Maintenance burden; no cross-hospital learning; limited to IT team capacity

7. The Ask

What we need to make this real

Immediate Next Steps

  • Hospital partner: LOI from one academic medical center for pilot deployment
  • Epic sandbox: Access to Epic FHIR sandbox for development and testing
  • Clinical advisory board: 3-5 surgeons/anesthesiologists for protocol validation
  • Runway: 18 months to reach pilot results and Series A readiness

Success Metrics (12-Month Pilot)

  • 50%+ reduction in preventable day-of cancellations
  • 15+ minutes saved per patient in pre-procedure prep
  • Zero missed critical findings vs. manual process
  • NPS > 70 from perioperative clinicians

Why We Win

  • Clinical depth: Built by people who understand perioperative workflows
  • Technical approach: Rules engine + LLM synthesis (not just one or the other)
  • Integration-first: FHIR-native, Epic-compatible from day one
  • Measurable ROI: Every installation generates provable savings data
  • Right timing: Open APIs + staffing crisis + value-based care convergence

What We're NOT

  • × Not a replacement for clinical judgment
  • × Not an EHR replacement
  • × Not another alert / pop-up system
  • × Not dependent on LLMs alone (rules engine is deterministic)
  • × Not a research project — this is a product