11 days
Median 11-day cycle time across ~4,500 monthly requests. Roughly 30% came back for more documentation, adding ~4 days each.
Prior Authorization: 80% Faster with AI Agents
How a health system cut prior authorization cycle time from 11 days to 2.1.
Get StartedAbout the Project
An AI agent architecture cut the median authorization cycle from 11 days to 2.1 and staff time by 65%.
Industry
Healthcare / Regional Health System
~4,500 authorization requests a month across its specialty practices.
Business Type
Multi-Specialty Provider Network
A 14-person authorization team working payer portals across the network.
Core Offering
AI-Assisted Prior Authorization
Agents gather documentation, match payer criteria, draft justifications, and submit.
Integration
SMART on FHIR Connections to Epic
Payer document requirements mapped to Epic data-model locations for direct retrieval.
Rollout
Five Months to Full Deployment
Five phases, starting in shadow mode with specialists reviewing every AI output.
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Scope AI-assisted prior authorization for your own payer mix.
What Prior Auth Really Cost
Slow prior auth delayed care and cost revenue.
14 staff
14 specialists lived in payer portals, gathering EHR documentation and writing justifications. Payer expertise sat in heads, not systems.
~8 days
Authorization added ~8 days to order-to-procedure time on the ~60% of orders needing it — rescheduled procedures, missed clinical windows.
Cut authorization delays.
Free your clinical staff.
Get patients to care faster.
Talk to Our Team
The Implementation Journey
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Phase 1 — Criteria Library (Months 1–2)
Phase 1 — Criteria Library (Months 1–2)
- Coverage criteria structured per payer and procedure
- Staff validated every payer-procedure combination
- The base for criteria matching and ongoing upkeep
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Phase 2 — EHR Integration (Months 2–3)
Phase 2 — EHR Integration (Months 2–3)
- SMART on FHIR connections to the Epic EHR
- Payer document needs mapped to Epic data locations
- Handled documentation variance across departments
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Phase 3 — Shadow-Mode Pilot (Months 3–4)
Phase 3 — Shadow-Mode Pilot (Months 3–4)
- Shadow mode: specialists reviewed every output
- Caught systematic matching and documentation errors
- Refined before routine cases moved to exception review
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Phase 4 — Full Deployment (Month 5+)
Phase 4 — Full Deployment (Month 5+)
- High-confidence cases submitted after brief review
- Lower-confidence cases sent to human review
- Weekly cycle time, approval, and return tracking
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Phase 5 — Scale & Governance
Phase 5 — Scale & Governance
- Extended to other service lines once the pilot held
- Monthly governance on accuracy, denials, rule drift
- Ownership moved to operations, informatics on support
What the AI Agent Architecture Did
The agent handled routine cases and routed exceptions with context, cutting specialist time from 38 minutes to 13.
Automated Documentation Gathering
The agent pulls each payer's required documentation from the EHR itself.
Criteria Matching & Justification Drafting
It drafts justification letters citing the findings that meet payer criteria.
Automated Submission & Status Tracking
FHIR payers get electronic submissions; portal payers get pre-filled fields.
Prioritized Human Review Queue
Exceptions reach specialists with the assessment and criteria attached.
The Results
Every number below was measured in production after launch — not projected in a pitch deck.
80%
Cycle Time Reduction — 11 days down to 2.1 days
65%
Less Clinical Staff Time — On authorization tasks
13 min
Specialist Time Per Auth — Down from 38 minutes
79%
First-Pass Approval Rate — Up from 71%
Global presence
