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Proactive Healthcare Coverage Risk Analysis System

Implements a 9-phase agentic workflow with autonomous decision-making capabilities. Uses Holt-Winters forecasting, multi-employer hour aggregation, and proactive alert generation to prevent coverage loss.

9 AI Agents
5 Tech Stack
AI Orchestrated
24/7 Available
Worker ID: Coverage Intelligence Advisor

Problem Statement

The challenge addressed

Union members with variable work hours across multiple employers risk losing healthcare coverage without warning. Manual monitoring cannot predict coverage gaps or coordinate proactive interventions before termination occurs.

Solution Architecture

AI orchestration approach

Implements a 9-phase agentic workflow with autonomous decision-making capabilities. Uses Holt-Winters forecasting, multi-employer hour aggregation, and proactive alert generation to prevent coverage loss.
Interface Preview 4 screenshots

Coverage analysis input screen with quick start templates, member information form, hours data tracking, and AI agent pipeline visualization

Agent orchestration theater displaying real-time multi-agent workflow execution with inter-agent communication, tool invocations, and overall progress tracking

Coverage analysis results showing risk assessment scores, days to action, people affected, monthly savings projections, and COBRA cost comparisons

Detailed risk assessment view with probability of coverage loss, risk factors, protective factors, SHAP-like feature contributions, and AI reasoning chain

Multi-Agent Orchestration

AI Agents

Specialized autonomous agents working in coordination

9 Agents
Parallel Execution
AI Agent

Multi-Employer Intelligence Agent

Union members work across multiple contributing employers, making it difficult to aggregate total hours for eligibility determination and identify reciprocity opportunities.

Core Logic

Aggregates hours from all contributing employers in real-time, applies reciprocity rules for cross-fund transfers, identifies hour banking opportunities, calculates combined eligibility status, and tracks employer contribution patterns for reliability scoring.

ACTIVE #1
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AI Agent

Risk Assessment Agent

Identifying members at risk of coverage loss requires analyzing complex patterns in work hours, employer reliability, seasonal variations, and historical coverage gaps.

Core Logic

Applies logistic regression model with 8 risk factors to calculate Probability of Coverage Loss (PCL). Analyzes rolling 3-month hours against 360-hour threshold, evaluates employer count and volatility, generates risk scores with Wilson confidence intervals, and identifies protective factors.

ACTIVE #2
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AI Agent

Forecasting Agent

Predicting future work hours and eligibility status requires sophisticated time series analysis accounting for seasonality, trends, and employer-specific patterns.

Core Logic

Implements Triple Exponential Smoothing (Holt-Winters) for 90-day coverage forecasts. Decomposes time series into level, trend, and seasonal components, calculates MAPE accuracy metrics, projects daily hour accumulation, and identifies critical eligibility threshold crossing dates.

ACTIVE #3
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AI Agent

Family Impact Analysis Agent

Coverage loss affects entire families differently based on dependent health needs, ages, and healthcare utilization patterns requiring personalized impact assessments.

Core Logic

Calculates family vulnerability scores based on dependent count, ages, and chronic conditions. Models COBRA cost burden against household income, identifies at-risk dependents with ongoing treatment needs, generates family-specific intervention recommendations.

ACTIVE #4
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AI Agent

Agent Collaboration Coordinator

Multiple specialized agents may produce conflicting assessments requiring structured consensus-building to reach reliable conclusions.

Core Logic

Facilitates cross-validation between Risk Assessment, Forecasting, and Family Impact agents. Implements confidence-weighted consensus voting, resolves discrepancies through evidence comparison, and produces unified analysis with documented reasoning chains.

ACTIVE #5
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AI Agent

Recommendation Agent

Generating actionable recommendations requires synthesizing risk assessments, forecasts, family impact, and available intervention options into prioritized action plans.

Core Logic

Produces prioritized intervention recommendations with urgency levels. Calculates optimal intervention timing, estimates success probability for each option, generates personalized member communications, and schedules automated follow-up actions.

ACTIVE #6
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AI Agent

Proactive Alert Agent

Members and administrators need timely warnings about impending coverage issues before they become critical, delivered through appropriate channels.

Core Logic

Generates smart alerts based on configurable triggers: PCL thresholds, days-to-termination, hour shortfalls, and family vulnerability scores. Determines optimal communication channels (email, SMS, portal), schedules outreach windows, and tracks alert acknowledgment.

ACTIVE #7
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AI Agent

Autonomous Decision Agent

Routine coverage interventions require human approval creating delays. Low-risk decisions could be automated while maintaining appropriate oversight.

Core Logic

Implements autonomous decision authority within defined guardrails. Auto-approves low-risk actions (notifications, hour banking), escalates high-impact decisions with recommendation, maintains complete audit trail, and supports human override at any point.

ACTIVE #8
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AI Agent

Validation & Compliance Agent

All coverage decisions and communications must comply with ERISA notice requirements, COBRA regulations, and plan document provisions.

Core Logic

Validates recommendations against plan document rules, ensures COBRA notice timing compliance, verifies ERISA disclosure requirements, checks 2025 regulatory updates, and generates compliant member communications with required legal language.

ACTIVE #9
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Technical Details

Worker Overview

Technical specifications, architecture, and interface preview

System Overview

Technical documentation

Enhanced agentic orchestration engine for healthcare coverage analysis featuring autonomous decisions, real-time agent collaboration, smart outreach scheduling, family vulnerability scoring, and 2025 COBRA rate benchmarking.

Tech Stack

5 technologies

BehaviorSubject state management

Holt-Winters time series forecasting implementation

Logistic regression risk scoring model

Multi-employer hour aggregation with reciprocity support

2025 DOL COBRA rate database integration

Architecture Diagram

System flow visualization

Proactive Healthcare Coverage Risk Analysis System Architecture
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