Inflation Decomposition Engine

python
# Multiplicative Trend Decomposition
def decompose_medical_trend(claims_data, macro_data):
    # Component 1: General Economic Inflation (CPI)
    cpi_start = macro_data.cpi_medical[period_start]
    cpi_end = macro_data.cpi_medical[period_end]
    cpi_inflation = (cpi_end / cpi_start) - 1
    
    # Component 2: Healthcare-Specific Inflation (above CPI)
    # Compare actual unit costs to CPI-adjusted baseline
    baseline_unit_cost = historical_unit_cost * (1 + cpi_inflation)
    actual_unit_cost = current_period_unit_cost
    healthcare_inflation = (actual_unit_cost / baseline_unit_cost) - 1
    
    # Component 3: Utilization Change
    baseline_utilization = historical_services_per_member
    actual_utilization = current_services_per_member
    utilization_change = (actual_utilization / baseline_utilization) - 1
    
    # Total Trend (Multiplicative)
    total_trend = ((1 + cpi_inflation) * 
                   (1 + healthcare_inflation) * 
                   (1 + utilization_change)) - 1
    
    # Attribution Percentages
    cpi_contribution = cpi_inflation / total_trend
    healthcare_contribution = healthcare_inflation / total_trend
    utilization_contribution = utilization_change / total_trend
    
    return {
        'total_trend': total_trend,
        'cpi_inflation': cpi_inflation,
        'healthcare_inflation': healthcare_inflation,
        'utilization_change': utilization_change,
        'attribution': {
            'cpi_pct': cpi_contribution * 100,
            'healthcare_pct': healthcare_contribution * 100,
            'utilization_pct': utilization_contribution * 100
        }
    }

# Example Output:
# Total Trend: 9.8%
#   ├─ CPI Medical Inflation: 3.2% (33% of trend)
#   ├─ Healthcare-Specific: 5.1% (52% of trend)
#   └─ Utilization Change: 1.2% (12% of trend)
# 
# Interpretation: 52% of trend is unit cost growth ABOVE general inflation
# → Network negotiation is the highest-leverage intervention