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AuthorizAI - Prior Authorization Multi-Agent System

AuthorizAI implements an 8-agent orchestration pipeline that processes prior authorization requests in under 15 seconds. The system performs parallel analysis of eligibility, clinical necessity, policy criteria, and risk factors.

Parent Portal Nexgile-PulseIQ Hub
8 AI Agents
10 Tech Stack
AI Orchestrated
24/7 Available
Worker ID: authorizai_prior_auth

Problem Statement

The challenge addressed

Prior authorization processes are slow, labor-intensive, and frustrating for providers and members. Average turnaround times exceed regulatory requirements. Manual clinical review is inconsistent and creates bottlenecks. Providers lack visibility int...

Solution Architecture

AI orchestration approach

AuthorizAI implements an 8-agent orchestration pipeline that processes prior authorization requests in under 15 seconds. The system performs parallel analysis of eligibility, clinical necessity, policy criteria, and risk factors. Tier-1 auto-approval...
Interface Preview 4 screenshots

Demo Scenario Selection - Choose from pre-configured authorization scenarios including routine approvals, complex clinical reviews, and denial risk cases

Multi-Agent Orchestration - Real-time visualization of parallel agent execution flow with live system metrics and agent status tracking

AI Decision Output - Comprehensive authorization decision with medical necessity scoring, criteria evaluation, evidence strength, and technical metadata

PA Command Center - Real-time operations dashboard with performance metrics, agent health monitoring, decision feed, and human review queue management

Multi-Agent Orchestration

AI Agents

Specialized autonomous agents working in coordination

8 Agents
Parallel Execution
AI Agent

Orchestrator Agent

Prior authorization involves multiple specialized analyses that must be coordinated efficiently. Without orchestration, processing is sequential and slow. Agent failures can halt the entire workflow without graceful degradation.

Core Logic

Coordinates the multi-agent workflow using hybrid parallel-sequential execution. Initializes the orchestration pipeline, establishes inter-agent communication channels, and manages execution across 5 batches. Monitors agent health and progress. Collects and routes agent outputs to downstream consumers. Implements error handling and retry logic for fault tolerance.

ACTIVE #1
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AI Agent

Data Ingestion Agent

Prior authorization requests require data from multiple sources including member databases, claims history, provider credentialing systems, and clinical documentation. Incomplete data leads to delays and incorrect decisions.

Core Logic

Collects and normalizes patient data from multiple healthcare systems. Retrieves member demographics, coverage details, and claims history (last 24 months). Fetches clinical documentation including lab results, imaging history, and previous treatments. Assembles comprehensive data packages (847+ data points) with 96% quality scores. Validates data completeness before downstream processing.

ACTIVE #2
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AI Agent

Eligibility Verification Agent

Processing authorizations for ineligible members or non-covered services wastes resources. Provider network status affects payment rates. Benefit accumulator status determines member cost-sharing responsibility.

Core Logic

Verifies member eligibility via real-time X12 270/271 EDI transactions. Confirms active coverage, plan benefits, and service-specific authorization requirements. Validates provider network status (in-network, out-of-network, tier designation). Checks benefit accumulators including deductible and out-of-pocket maximum status. Calculates estimated member cost-sharing. Achieves 99% confidence with detailed reasoning.

ACTIVE #3
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AI Agent

Clinical Analysis Agent

Determining medical necessity requires evaluation against complex clinical criteria from InterQual, MCG, and plan-specific guidelines. Manual clinical review is slow and inconsistent. Clinicians may miss relevant criteria or apply them incorrectly.

Core Logic

Evaluates medical necessity using InterQual and MCG clinical criteria. Analyzes diagnosis codes, symptom duration and severity, conservative treatment history, and red flag symptoms. Calculates medical necessity scores (threshold: 70/100). Generates clinical recommendations with evidence strength ratings (strong, moderate, weak). Identifies criteria met and not met with supporting evidence citations. Achieves 92% confidence.

ACTIVE #4
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AI Agent

Policy Matching Agent

Health plans maintain hundreds of medical policies with complex approval criteria. Finding applicable policies and evaluating criteria manually is time-consuming. Policy updates may not be consistently applied across reviewers.

Core Logic

Searches medical policy database using semantic matching to find applicable policies for the requested service. Extracts approval criteria from policy documents. Evaluates each criterion against request documentation. Checks policy effective dates and place of service requirements. Identifies alternative service options when primary request doesn't meet criteria. Achieves 96% confidence with detailed policy references.

ACTIVE #5
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AI Agent

Risk Assessment Agent

Understanding patient risk profile helps prioritize complex cases and predict outcomes. Fraud patterns should be detected before authorization. Without risk stratification, all requests receive equal treatment regardless of complexity.

Core Logic

Calculates CMS-HCC risk scores using model v28 for cost prediction. Maps diagnosis codes to HCC categories with hierarchical condition rules. Computes 30-day readmission probability and complexity assessment. Runs fraud pattern detection algorithms to identify suspicious indicators. Provides risk tier classification (low, moderate, high) to inform processing pathway. Achieves 88% confidence.

ACTIVE #6
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AI Agent

Decision Synthesis Agent

Multiple analysis agents may produce conflicting recommendations. Without synthesis, decisions lack coherent rationale. Decision thresholds must be calibrated to achieve target auto-approval rates while maintaining accuracy.

Core Logic

Collects outputs from all analysis agents (Eligibility, Clinical, Policy, Risk). Weights confidence scores based on relevance and historical accuracy. Resolves conflicting recommendations using rule-based logic. Applies decision thresholds to determine approval tier. Generates unified recommendations with weighted confidence scores. Produces comprehensive decision rationale citing all contributing agent findings. Achieves 94% confidence.

ACTIVE #7
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AI Agent

Compliance Audit Agent

Prior authorization decisions must comply with HIPAA, state regulations, and CMS guidelines. Audit trails must be complete and immutable. Turnaround time requirements vary by urgency level and state.

Core Logic

Verifies HIPAA Privacy Rule compliance for all data access. Validates audit trail completeness with proper timestamps and actor attribution. Checks turnaround time compliance against state-specific regulations. Ensures documentation requirements are met per CMS guidelines. Generates compliance certificates with unique identifiers. Produces immutable audit entries with cryptographic hashes. Achieves 100% compliance verification.

ACTIVE #8
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Technical Details

Worker Overview

Technical specifications, architecture, and interface preview

System Overview

Technical documentation

Enterprise-grade multi-agent prior authorization system implementing Saga pattern with parallel/sequential agent execution. Features 5 orchestration phases: Initialization, Data Collection, Parallel Analysis, Synthesis, and Decision Output. Supports three decision tiers: Tier-1 Auto-Approval (67% of requests), Tier-2 Assisted Review, and Tier-3 Manual Review. Includes comprehensive Human-in-the-Loop capabilities with escalation management, peer-to-peer review scheduling, appeal processing, and real-time queue management.

Tech Stack

10 technologies

8-agent orchestration with parallel execution batches

Real-time eligibility verification via X12 270/271 EDI

InterQual and MCG clinical criteria integration

Medical policy database with semantic search

CMS-HCC Risk Adjustment Model v28

Fraud pattern detection algorithms

HIPAA-compliant audit trail with immutable logging

Human-in-the-Loop escalation and queue management

Peer-to-peer review scheduling with video conferencing

Multi-level appeal management system

Architecture Diagram

System flow visualization

AuthorizAI - Prior Authorization Multi-Agent System Architecture
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