# Prior Authorization Orchestration

*/Opportunities/Prior_Authorization_Orchestration*

## Opportunity Overview

**Wedge**: Begin with high-cost, scheduled procedures in Orthopedics within a specific regional payer market. Orthopedic guidelines are highly structured and repeatable, allowing the system to achieve high first-pass approval rates quickly to prove reliability. Expansion proceeds by adding adjacent procedure-heavy specialties like Cardiology, followed by crossing over into managing retroactive claim denials using the same payer-logic engine.
**Timing**: Current long-context language models successfully ingest 100-page payer policy PDFs and cross-reference them against unstructured electronic health record notes to extract clinical rationale. Two years ago, determining medical necessity from free-text physician notes required clinical human judgment, but model reasoning now clears the threshold for accurate medical synthesis.
**Why This I C P**: Independent specialty clinics such as Orthopedics, Oncology, and Gastroenterology handle the highest concentration of expensive procedures requiring authorization. They experience direct revenue blockage and patient care delays from authorization bottlenecks, forcing them to adopt automation faster than heavily bureaucratic hospital networks.
**Size Of Prize**: ~150,000 specialty medical practices in the US spend an average of ~$30,000 annually on dedicated administrative labor for prior authorizations, yielding an addressable market of ~$4.5B in direct labor replacement.
**Gap Narrative**: Specialty medical practices lose thousands of hours annually manually matching patient charts to opaque, constantly changing health insurance clinical guidelines. Existing tools rely on brittle RPA scripts or offshore human labor that fails to accurately synthesize complex medical histories into successful authorization requests. Providers require a system that reads unstructured clinical notes, determines the exact payer requirements, and submits the completed packet without human intervention.
**Defensibility**: The system compounds value by mapping the undocumented, payer-specific shadow rules that cause rejections. Each submitted and adjudicated authorization trains the engine on exactly what clinical phrasing guarantees approval for specific insurance plans. Once integrated bi-directionally into the clinic's EHR, the platform establishes total workflow lock-in by owning the critical revenue-gating step before patient treatment.
**Why This Thesis**: A Service-as-Software approach matches this problem because clinics do not want another workflow tool to manage; they want the entire task executed. Deploying agents to act as digital billers replaces the headcount directly, delivering the outcome of an approved authorization rather than software that helps a human work faster.

## Opportunity Linked Thesis

**Thesis**: [Service-as-Software](/Theses/Service-as-Software)

## Opportunity Linked I C P

**Icp**: [Specialty Medical Practice](/CompanyTypes/Specialty_Medical_Practice)

## Opportunity Market Sizing

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**S A M**: ~$2-3B US independent and mid-sized specialty practice segments
**S O M**: ~$50-150M
**T A M**: ~150k US specialty medical clinics × ~$40k/yr allocated to PA admin and tooling ≈ $6B
**Growth Rate**: ~12-18%/yr, driven by increasing payer scrutiny on specialty procedures and chronic shortages in medical administrative staffing
**Paid Comparable Spend**: ~$40k-80k/yr per practice currently spent on dedicated administrative headcount and outsourced RCM service fees

## Opportunity Incumbents

- [CoverMyMeds Platform](/Products/CoverMyMeds_Platform) — Tool
- [Availity Essentials](/Products/Availity_Essentials) — Tool
- [Change Healthcare](/Products/Change_Healthcare) — Service
- [Manual Fax Workflows](/Products/Manual_Fax_Workflows) — DIY
- [Excel Spreadsheets](/Products/Excel_Spreadsheets) — Spreadsheet
- [Epic Systems](/Products/Epic_Systems) — Tool
- [Outsourced Billing Agencies](/Products/Outsourced_Billing_Agencies) — Service

## Opportunity Win Conditions

**Kill Thresholds**:
- Human escalation rate > 40 percent after 45 days
- Payer sync failure rate > 15 percent of daily volume
- Conversion rate from trial to paid < 50 percent
- Customer acquisition cost > 10000 dollars
**Leading Metrics**:
- Time-to-first-automated-submission
- End-to-end automation success rate
- Human-in-the-loop escalation percentage
- EHR-to-payer field mapping accuracy
- Daily active usage by billing staff
**What Proves Right**: Clinics route 80 percent of their prior authorization volume through the system within 30 days of deployment. Administrative staff reduce time spent on payer portals by 15 hours per week. Practices convert to a 2500 dollar monthly subscription after 60 days based on a documented 50 percent reduction in time-to-approval.
**What Proves Wrong**: Clinics default back to manual workflows because payer portals require dynamic clinical documentation that the orchestration layer fails to extract from the EHR. The system generates frequent sync errors, forcing staff to manually intervene on more than 40 percent of submissions. Engineering maintenance costs for payer data extraction scripts exceed the average account revenue.

## Opportunity Build Profile

**Hardest Part**: Parsing unstructured clinical notes from messy EHRs into the exact structured criteria required by hundreds of constantly changing payer policies without hallucinating medical necessity.
**Min Viable Scope**: Focus strictly on one high-volume, low-variance specialty like dermatology or gastroenterology for a handful of major regional payers. Leave out complex inpatient procedures, appeals generation, and automated payer portal submission, relying instead on a human-in-the-loop fallback for the actual portal data entry.
**Cold Start Problem**: You need historical clinical notes and payer policies to train extraction models, but clinics withhold access until you prove accuracy. Break this by starting as a tech-enabled service for a single specialty clinic, manually mapping their most common payer rules to process their immediate backlog.
**Time To First Value**: 2-4 weeks (gated by EHR read-access provisioning and initial policy mapping)
**Data Moat Available**: true
**Technical Difficulty**: High

## Neighborhood

### Embodied by

- [Agent](/Theses/Agent) — embodies · Theses

### Incumbent in

- [Manual Fax Processing](/Products/Manual_Fax_Processing) — incumbent in · Products
- [Availity Essentials](/Products/Availity_Essentials) — incumbent in · Products
- [Change Healthcare](/Products/Change_Healthcare) — incumbent in · Products
- [CoverMyMeds Platform](/Products/CoverMyMeds_Platform) — incumbent in · Products
- [Epic Systems](/Products/Epic_Systems) — incumbent in · Products
- [Excel Spreadsheets](/Products/Excel_Spreadsheets) — incumbent in · Products
- [Outsourced Billing Agencies](/Products/Outsourced_Billing_Agencies) — incumbent in · Products

### Applies thesis

- [Specialty Medical Practice](/CompanyTypes/Specialty_Medical_Practice) — applies thesis · CompanyTypes

### Embodies

- [Service-as-Software](/Theses/Service-as-Software) — embodies · Theses

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