Dental Trend Analysis Engine

python
# Dental Trend Decomposition Model
dental_service_categories = {
    'preventive': ['D1110', 'D1120', 'D1208'],  # Cleanings, fluoride, exams
    'basic_restorative': ['D2140', 'D2150', 'D2160'],  # Fillings, amalgams
    'endodontics': ['D3310', 'D3320', 'D3330'],  # Root canals
    'periodontics': ['D4210', 'D4240', 'D4260'],  # Gum treatments
    'major_restorative': ['D2740', 'D2750', 'D2790'],  # Crowns, bridges
    'oral_surgery': ['D7140', 'D7210', 'D7250'],  # Extractions
    'orthodontics': ['D8080', 'D8090']  # Braces, aligners
}

def analyze_dental_trend(claims_current, claims_prior):
    """
    Decompose dental trend into unit cost, utilization, and mix shift
    """
    trend_components = {}
    
    for category, cdt_codes in dental_service_categories.items():
        # Filter claims to category
        current_cat = claims_current[claims_current.cdt_code.isin(cdt_codes)]
        prior_cat = claims_prior[claims_prior.cdt_code.isin(cdt_codes)]
        
        # Calculate metrics
        current_pmpm = current_cat.allowed.sum() / member_months_current
        prior_pmpm = prior_cat.allowed.sum() / member_months_prior
        
        current_util = len(current_cat) / member_months_current  # Services PMPM
        prior_util = len(prior_cat) / member_months_prior
        
        current_unit = current_cat.allowed.mean()
        prior_unit = prior_cat.allowed.mean()
        
        # Trend decomposition
        unit_cost_trend = (current_unit / prior_unit) - 1
        utilization_trend = (current_util / prior_util) - 1
        total_trend = (current_pmpm / prior_pmpm) - 1
        
        trend_components[category] = {
            'pmpm_current': current_pmpm,
            'pmpm_prior': prior_pmpm,
            'total_trend': total_trend,
            'unit_cost_trend': unit_cost_trend,
            'utilization_trend': utilization_trend
        }
    
    return trend_components

def forecast_benefit_design_change(baseline_pmpm, change_type):
    """
    Predict impact of benefit design modifications
    """
    impact_factors = {
        'add_ortho': 1.25,  # +25% increase (ages 8-18 pent-up demand)
        'increase_annual_max_1500_to_2000': 1.04,  # +4% (major service utilization)
        'reduce_preventive_copay_to_zero': 1.02,  # +2% (utilization increase)
        'add_implant_coverage': 1.08,  # +8% (high unit cost, moderate uptake)
        'switch_DPPO_to_DHO': 0.88  # -12% (network discount improvement)
    }
    
    new_pmpm = baseline_pmpm * impact_factors[change_type]
    
    return {
        'baseline_pmpm': baseline_pmpm,
        'change': change_type,
        'projected_pmpm': new_pmpm,
        'dollar_impact': new_pmpm - baseline_pmpm,
        'percent_impact': impact_factors[change_type] - 1
    }

# Example: Multi-Year Dental Trend
# 2023: $42 PMPM
#   - Preventive: $18 (43%)
#   - Basic Restorative: $12 (29%)
#   - Major: $10 (24%)
#   - Ortho: $2 (5%)
#
# 2024: $45 PMPM (+7.1% total trend)
#   - Preventive: $19 (+5.6% — utilization up 3%, unit cost +2.5%)
#   - Basic: $13 (+8.3% — unit cost driven, fee schedule increase)
#   - Major: $11 (+10% — aging workforce, more crowns)
#   - Ortho: $2 (flat — no new ortho benefit additions)