Comprehensive GenerativeAI Framework Architecture

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GenerativeAI Framework Orchestrator Agent

Master controller coordinating all sub-agents

# GenerativeAI_Framework_Orchestrator.py
@ai_agent
class GenerativeAIFrameworkOrchestrator:
  def __init__(self):
    self.agents = []
    self.workflow_engine = WorkflowEngine()
    self.decision_tree = DecisionTree()

  async def process_claim(self, claim_data):
    # Intelligent routing based on claim type
    claim_type = self.analyze_claim(claim_data)
    agents = self.select_agents(claim_type)
    
    for agent in agents:
      await agent.execute(claim_data)
    
    return self.compile_results()

Appointment Scheduling Agent

Intelligent appointment optimization

# Appointment_Scheduling_Agent.py
@optimization_engine
class AppointmentSchedulingAgent:
  def __init__(self):
    self.calendar_optimizer = CalendarOptimizer()
    self.patient_predictor = PatientBehaviorModel()
    self.resource_manager = ResourceManager()

  def schedule_appointment(self, patient, provider):
    # Predict optimal time slots
    patient_prefs = self.patient_predictor.analyze(patient)
    available_slots = self.calendar_optimizer.find_slots(provider)
    
    # Minimize wait times and maximize efficiency
    optimal_slot = self.optimize_schedule(patient_prefs, available_slots)
    
    return self.book_appointment(optimal_slot)

No-Show Prediction Agent

Predicts and prevents appointment no-shows

# NoShow_Prediction_Agent.py
@predictive_analytics
class NoShowPredictionAgent:
  def __init__(self):
    self.ml_model = load_model('xgboost_noshow_v3')
    self.reminder_engine = ReminderEngine()
    self.intervention_system = InterventionSystem()

  def predict_no_show(self, appointment):
    # Extract features: history, weather, distance, etc.
    features = self.extract_features(appointment)
    risk_score = self.ml_model.predict_proba(features)
    
    if risk_score > 0.7:
      # High risk - implement interventions
      self.reminder_engine.send_multiple_reminders(appointment)
      self.intervention_system.offer_transportation(appointment)
      return self.suggest_double_booking(appointment)

Prior Authorization Agent

Automates prior auth submissions

# Prior_Authorization_Agent.py
@rules_engine
class PriorAuthorizationAgent:
  def __init__(self):
    self.payer_rules = PayerRulesEngine()
    self.clinical_validator = ClinicalValidator()
    self.auto_submitter = AutoSubmitter()

  async def process_auth(self, procedure, insurance):
    # Check if prior auth required
    auth_required = self.payer_rules.check_requirement(procedure, insurance)
    
    if auth_required:
      clinical_docs = self.clinical_validator.gather_documentation()
      auth_request = self.build_auth_request(clinical_docs)
      return await self.auto_submitter.submit(auth_request)

Patient Registration Agent

Validates patient demographics

# PatientRegistration_Agent.py
@ml_powered
class PatientRegistrationAgent:
  def __init__(self):
    self.nlp_engine = NLPEngine()
    self.validation_model = load_model('patient_val_v2')

  def validate_patient(self, patient_data):
    # AI-powered data validation
    confidence = self.validation_model.predict(patient_data)
    
    if confidence > 0.95:
      return self.auto_register(patient_data)
    else:
      return self.flag_for_review(patient_data)

Insurance Verification Agent

Real-time eligibility checking

# Insurance_Verification_Agent.py
@async_agent
class InsuranceVerificationAgent:
  def __init__(self):
    self.api_connector = APIConnector()
    self.cache = RedisCache()
    self.ml_predictor = BenefitPredictor()

  async def verify_coverage(self, insurance_info):
    # Check cache first for performance
    cached = await self.cache.get(insurance_info.id)
    if cached:
      return cached
    
    # Real-time API verification
    result = await self.api_connector.verify(insurance_info)
    return self.ml_predictor.enhance(result)

Medical Coding Agent

Automated ICD-10/CPT coding

# Medical_Coding_Agent.py
@transformer_based
class MedicalCodingAgent:
  def __init__(self):
    self.bert_model = load_pretrained('medical-bert')
    self.icd10_mapper = ICD10Mapper()
    self.cpt_engine = CPTEngine()

  def auto_code(self, clinical_notes):
    # Extract medical entities using BERT
    entities = self.bert_model.extract_entities(clinical_notes)
    
    # Map to appropriate codes
    icd_codes = self.icd10_mapper.map(entities.diagnoses)
    cpt_codes = self.cpt_engine.map(entities.procedures)
    
    return {'icd10': icd_codes, 'cpt': cpt_codes}

Charge Capture Agent

Ensures no missed charges

# Charge_Capture_Agent.py
@real_time_monitoring
class ChargeCaptureAgent:
  def __init__(self):
    self.ehr_monitor = EHRMonitor()
    self.charge_validator = ChargeValidator()
    self.revenue_optimizer = RevenueOptimizer()

  def capture_charges(self, encounter):
    # Monitor all billable events
    services = self.ehr_monitor.extract_services(encounter)
    supplies = self.ehr_monitor.extract_supplies(encounter)
    
    # Validate against fee schedule
    validated_charges = self.charge_validator.validate(services, supplies)
    
    # Optimize revenue capture
    return self.revenue_optimizer.maximize(validated_charges)

Claims Submission Agent

Electronic claim generation

# Claims_Submission_Agent.py
@queue_based
class ClaimsSubmissionAgent:
  def __init__(self):
    self.edi_generator = EDI837Generator()
    self.submission_queue = PriorityQueue()
    self.error_predictor = ErrorPredictionModel()

  def submit_claim(self, claim_data):
    # Predict potential errors before submission
    error_prob = self.error_predictor.analyze(claim_data)
    
    if error_prob < 0.1:
      edi_file = self.edi_generator.create(claim_data)
      return self.submit_to_clearinghouse(edi_file)
    else:
      return self.route_to_review(claim_data)

Denial Management Agent

Automated denial appeals

# Denial_Management_Agent.py
@reinforcement_learning
class DenialManagementAgent:
  def __init__(self):
    self.denial_classifier = DenialClassifier()
    self.appeal_generator = AppealGenerator()
    self.success_tracker = SuccessTracker()

  def handle_denial(self, denial_info):
    # Classify denial reason using ML
    denial_type = self.denial_classifier.classify(denial_info)
    
    # Generate optimal appeal strategy
    appeal_strategy = self.get_best_strategy(denial_type)
    appeal_letter = self.appeal_generator.create(appeal_strategy)
    
    return self.submit_appeal(appeal_letter)

Payment Posting Agent

Automated reconciliation

# Payment_Posting_Agent.py
@real_time_processing
class PaymentPostingAgent:
  def __init__(self):
    self.ocr_engine = OCREngine()
    self.matching_algorithm = FuzzyMatcher()
    self.ledger_system = GeneralLedger()

  async def process_payment(self, payment_data):
    # Extract payment details using OCR if needed
    if payment_data.is_image:
      payment_data = self.ocr_engine.extract(payment_data)
    
    # Match payments to claims
    matched_claims = self.matching_algorithm.match(payment_data)
    
    await self.ledger_system.post(matched_claims)

A/R Follow-up Agent

Automated aging management

# AR_Followup_Agent.py
@priority_based
class ARFollowupAgent:
  def __init__(self):
    self.aging_analyzer = AgingAnalyzer()
    self.priority_engine = PriorityEngine()
    self.action_recommender = ActionRecommender()

  def manage_ar(self):
    # Analyze aging buckets
    aging_report = self.aging_analyzer.generate_report()
    
    # Prioritize follow-up actions
    priorities = self.priority_engine.rank_accounts(aging_report)
    
    # Recommend specific actions
    for account in priorities:
      action = self.action_recommender.suggest(account)
      self.execute_action(action)

Analytics & Reporting Agent

Real-time KPI monitoring

# Analytics_Reporting_Agent.py
@dashboard_enabled
class AnalyticsReportingAgent:
  def __init__(self):
    self.time_series_model = TimeSeriesPredictor()
    self.anomaly_detector = AnomalyDetector()
    self.visualization_engine = D3Visualizer()

  def generate_insights(self):
    # Predict future revenue trends
    revenue_forecast = self.time_series_model.forecast(30)
    
    # Detect anomalies in billing patterns
    anomalies = self.anomaly_detector.detect()
    
    # Generate interactive dashboards
    return self.visualization_engine.render({
      'forecast': revenue_forecast,
      'anomalies': anomalies
    })

Compliance Monitoring Agent

HIPAA and regulatory compliance

# Compliance_Monitoring_Agent.py
@audit_trail
class ComplianceMonitoringAgent:
  def __init__(self):
    self.hipaa_validator = HIPAAValidator()
    self.audit_logger = AuditLogger()
    self.risk_assessor = RiskAssessor()

  def monitor_compliance(self):
    # Continuous HIPAA monitoring
    violations = self.hipaa_validator.scan_all_systems()
    
    # Log all access and changes
    self.audit_logger.log_activities()
    
    # Assess and mitigate risks
    risk_score = self.risk_assessor.calculate()
    if risk_score > threshold:
      self.implement_safeguards()

Patient Portal Agent

Self-service patient interactions

# Patient_Portal_Agent.py
@chatbot_enabled
class PatientPortalAgent:
  def __init__(self):
    self.nlp_chatbot = NLPChatbot()
    self.payment_processor = PaymentProcessor()
    self.document_manager = DocumentManager()

  async def handle_patient_request(self, request):
    # Understand patient intent
    intent = self.nlp_chatbot.classify_intent(request)
    
    match intent:
      case 'payment':
        return await self.payment_processor.process()
      case 'documents':
        return self.document_manager.retrieve()
      case 'estimate':
        return self.generate_cost_estimate()

Audit & Quality Agent

Continuous quality improvement

# Audit_Quality_Agent.py
@quality_assurance
class AuditQualityAgent:
  def __init__(self):
    self.audit_sampler = StatisticalSampler()
    self.quality_scorer = QualityScorer()
    self.improvement_engine = ImprovementEngine()

  def conduct_audit(self):
    # Statistical sampling of claims
    sample = self.audit_sampler.select_claims()
    
    # Score quality metrics
    quality_scores = self.quality_scorer.evaluate(sample)
    
    # Generate improvement recommendations
    improvements = self.improvement_engine.recommend(quality_scores)
    return self.implement_improvements(improvements)

Referral Management Agent

Tracks and manages referrals

# Referral_Management_Agent.py
@network_aware
class ReferralManagementAgent:
  def __init__(self):
    self.network_validator = NetworkValidator()
    self.referral_tracker = ReferralTracker()
    self.loop_closer = LoopCloser()

  def manage_referral(self, referral):
    # Validate in-network status
    in_network = self.network_validator.check(referral.specialist)
    
    # Track referral lifecycle
    self.referral_tracker.create(referral)
    self.referral_tracker.monitor_status()
    
    # Ensure loop closure
    return self.loop_closer.follow_up(referral)

Contract Management Agent

Payer contract optimization

# Contract_Management_Agent.py
@contract_analyzer
class ContractManagementAgent:
  def __init__(self):
    self.rate_analyzer = RateAnalyzer()
    self.performance_tracker = PerformanceTracker()
    self.negotiation_ai = NegotiationAI()

  def optimize_contracts(self):
    # Analyze reimbursement rates
    rate_analysis = self.rate_analyzer.compare_to_market()
    
    # Track contract performance
    performance = self.performance_tracker.evaluate()
    
    # AI-powered negotiation suggestions
    negotiation_points = self.negotiation_ai.suggest(rate_analysis)
    return negotiation_points

Credentialing Agent

Provider credential management

# Credentialing_Agent.py
@automated_verification
class CredentialingAgent:
  def __init__(self):
    self.credential_verifier = CredentialVerifier()
    self.expiration_monitor = ExpirationMonitor()
    self.application_manager = ApplicationManager()

  def manage_credentials(self, provider):
    # Verify all credentials
    verification = self.credential_verifier.verify_all(provider)
    
    # Monitor expiration dates
    expiring = self.expiration_monitor.check_60_days()
    
    # Auto-submit applications
    for credential in expiring:
      self.application_manager.auto_renew(credential)

Patient Collections Agent

Compassionate collections AI

# Patient_Collections_Agent.py
@empathetic_ai
class PatientCollectionsAgent:
  def __init__(self):
    self.propensity_model = PropensityToPayModel()
    self.payment_plan_ai = PaymentPlanAI()
    self.communication_engine = CommunicationEngine()

  def collect_payment(self, account):
    # Predict payment probability
    propensity = self.propensity_model.predict(account)
    
    # Create personalized payment plans
    plan = self.payment_plan_ai.generate(account, propensity)
    
    # Empathetic communication
    message = self.communication_engine.craft_message(account, plan)
    return self.send_communication(message)