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Medical Plan Selection Advisor Using Predictive Cost Modeling

Demo on request
Decision Support

This proof-of-concept implements a decision support system that evaluates medical plan options using predictive cost modeling and user-defined risk preferences. Live execution is restricted due to IP-sensitive calculation logic.

System Overview

Inputs

  • Household size and composition
  • Income tier for subsidy calculations
  • Risk tolerance preference
  • Expected utilization (office visits, prescriptions, hospitalizations)

Plan Data

  • Monthly premiums and employer contributions
  • Deductibles (individual and family)
  • Coinsurance percentages
  • Copays and HSA contribution options

Core Logic

  • Deductible consumption modeling
  • Out-of-pocket accumulation tracking
  • Risk-weighted scoring algorithm

Output

  • Ranked plan recommendations
  • Projected annual costs by scenario
  • Risk exposure breakdown

Workflow Walkthrough

Key Capabilities

  • Models healthcare cost behavior instead of static comparison — deductible consumption, out-of-pocket accumulation, and risk-weighted scoring
  • Supports scenario-based sensitivity analysis for different utilization patterns
  • Separates fixed premiums from variable exposure to surface true cost risk
  • Designed for benefit selection and decision support use cases
  • Execution restricted — IP-sensitive scoring and calculation logic

Interested in a private demonstration of this system?

Request full demo