response_formatter.py

# response_formatter.py
from typing import Dict, List, Any, Tuple, Callable
import re

class ResponseFormatter:
    # Class-level handler map for extensibility
    _handler_map = {}
    
    @staticmethod
    def format_healthcare_response(scenario_text: str, analysis_results: Dict[str, Any]) -> str:
        """Format healthcare analysis response based on scenario tasks"""
        # Extract tasks from scenario
        tasks = ResponseFormatter._extract_scenario_tasks(scenario_text)
        
        response = "# Healthcare Scenario Analysis\n\n"
        
        # Executive Summary
        response += "## Executive Summary\n\n"
        response += ResponseFormatter._generate_executive_summary(analysis_results)
        response += "\n\n"
        
        # Process each task
        for task in tasks:
            section_content = ResponseFormatter._process_task(task, analysis_results)
            if section_content:
                response += section_content + "\n\n"
        
        # Validation Results
        if "validation" in analysis_results:
            response += "## Analysis Validation\n\n"
            response += ResponseFormatter._format_validation_results(analysis_results["validation"])
            response += "\n\n"
        
        # Provenance
        response += "## Provenance\n\n"
        response += "This analysis is based on:\n"
        response += "- Scenario description provided by the user\n"
        response += "- Uploaded data files\n"
        response += "- Calculations performed on the provided data\n"
        
        return response
    
    @staticmethod
    def _extract_scenario_tasks(scenario_text: str) -> List[Tuple[str, str]]:
        """Extract specific tasks from scenario text and return as (section_header, task_description) tuples"""
        tasks = []
        lines = scenario_text.split('\n')
        in_tasks = False
        current_task = ""
        
        for line in lines:
            line = line.strip()
            
            # Check if we're entering the tasks section
            if line.lower().startswith('tasks'):
                in_tasks = True
                continue
            
            # Check if we're leaving the tasks section
            if in_tasks and (line.lower().startswith('operational recommendations') or 
                            line.lower().startswith('future integration') or
                            line.lower().startswith('prepare your findings') or
                            line.lower().startswith('conclusions') or
                            line.lower().startswith('next steps')):
                in_tasks = False
                if current_task:
                    section_header = ResponseFormatter._get_section_header(current_task)
                    tasks.append((section_header, current_task))
                continue
            
            # Collect task content
            if in_tasks:
                # Check if this is a new task (starts with number or bullet)
                if re.match(r'^\d+\.', line) or line.startswith(('•', '-', '*')):
                    if current_task:
                        section_header = ResponseFormatter._get_section_header(current_task)
                        tasks.append((section_header, current_task))
                    current_task = line
                elif line:
                    current_task += " " + line
        
        # Add the last task if exists
        if current_task:
            section_header = ResponseFormatter._get_section_header(current_task)
            tasks.append((section_header, current_task))
            
        return tasks
    
    @staticmethod
    def _get_section_header(task_description: str) -> str:
        """Map task description to a clean section header with comprehensive keyword matching"""
        task_lower = task_description.lower()
        
        # Data Preparation patterns
        if any(keyword in task_lower for keyword in [
            "load the data", "data preparation", "data loading", "data import", 
            "data processing", "data cleaning", "data filtering"
        ]):
            return "Data Preparation"
        
        # Capacity Analysis patterns
        elif any(keyword in task_lower for keyword in [
            "bed capacity", "bed utilization", "bed availability", "bed occupancy",
            "capacity analysis", "resource capacity", "service capacity"
        ]):
            return "Capacity Analysis"
        
        # Facility Decline patterns
        elif any(keyword in task_lower for keyword in [
            "facilities with the greatest declines", "facility decline", 
            "bed reduction", "capacity reduction", "facility closure"
        ]):
            return "Facilities with Greatest Declines"
        
        # Long-Term Care patterns
        elif any(keyword in task_lower for keyword in [
            "assess long-term care", "long-term care capacity", "ltc assessment",
            "nursing home capacity", "residential care capacity", "care facility assessment"
        ]):
            return "Long-Term Care Capacity Assessment"
        
        # Recommendations patterns
        elif any(keyword in task_lower for keyword in [
            "recommend actions", "operational recommendations", "recommendations",
            "action plan", "mitigation strategies", "improvement strategies"
        ]):
            return "Operational Recommendations"
        
        # Integration patterns
        elif any(keyword in task_lower for keyword in [
            "future integration", "augmented ai", "decision support", "ai integration",
            "system integration", "data integration", "predictive analytics"
        ]):
            return "Future Integration Opportunities"
        
        # Patient Satisfaction patterns
        elif any(keyword in task_lower for keyword in [
            "patient satisfaction", "patient experience", "patient feedback",
            "satisfaction analysis", "experience analysis"
        ]):
            return "Patient Satisfaction Analysis"
        
        # Staff Utilization patterns
        elif any(keyword in task_lower for keyword in [
            "staff utilization", "workforce analysis", "staffing analysis",
            "human resources", "staff productivity", "staff allocation"
        ]):
            return "Staff Utilization Analysis"
        
        # Equipment patterns
        elif any(keyword in task_lower for keyword in [
            "equipment inventory", "medical equipment", "device utilization",
            "equipment assessment", "resource inventory"
        ]):
            return "Equipment Inventory Assessment"
        
        # Financial Analysis patterns
        elif any(keyword in task_lower for keyword in [
            "financial analysis", "cost analysis", "budget analysis",
            "economic analysis", "resource costing"
        ]):
            return "Financial Analysis"
        
        # Quality Metrics patterns
        elif any(keyword in task_lower for keyword in [
            "quality metrics", "performance metrics", "outcome measures",
            "quality indicators", "performance indicators"
        ]):
            return "Quality Metrics Analysis"
        
        # Geographic Distribution patterns
        elif any(keyword in task_lower for keyword in [
            "geographic distribution", "spatial analysis", "location analysis",
            "regional distribution", "service distribution"
        ]):
            return "Geographic Distribution Analysis"
        
        # Access patterns
        elif any(keyword in task_lower for keyword in [
            "access analysis", "accessibility", "service access",
            "barriers to care", "equity analysis"
        ]):
            return "Healthcare Access Analysis"
        
        # Wait Time patterns
        elif any(keyword in task_lower for keyword in [
            "wait time", "waiting time", "delay analysis",
            "queue analysis", "timeliness"
        ]):
            return "Wait Time Analysis"
        
        # Population Health patterns
        elif any(keyword in task_lower for keyword in [
            "population health", "epidemiology", "disease burden",
            "health status", "community health"
        ]):
            return "Population Health Analysis"
        
        # Emergency Services patterns
        elif any(keyword in task_lower for keyword in [
            "emergency services", "er analysis", "emergency department",
            "urgent care", "emergency response"
        ]):
            return "Emergency Services Analysis"
        
        # Specialized Care patterns
        elif any(keyword in task_lower for keyword in [
            "specialized care", "specialty services", "tertiary care",
            "specialized services", "advanced care"
        ]):
            return "Specialized Care Analysis"
        
        # Preventive Care patterns
        elif any(keyword in task_lower for keyword in [
            "preventive care", "prevention", "screening",
            "wellness programs", "health promotion"
        ]):
            return "Preventive Care Analysis"
        
        # Telehealth patterns
        elif any(keyword in task_lower for keyword in [
            "telehealth", "virtual care", "remote care",
            "digital health", "e-health"
        ]):
            return "Telehealth Analysis"
        
        # Research patterns
        elif any(keyword in task_lower for keyword in [
            "research", "clinical trials", "innovation",
            "evidence-based practice", "research analysis"
        ]):
            return "Research and Innovation Analysis"
        
        else:
            # Extract the first sentence as a fallback
            first_sentence = task_description.split('.')[0]
            return first_sentence.strip()
    
    @staticmethod
    def _process_task(task_tuple: Tuple[str, str], analysis_results: Dict[str, Any]) -> str:
        """Process a single task and return formatted content"""
        section_header, task_description = task_tuple
        
        # Initialize default handler map
        default_handler_map = {
            "Data Preparation": ResponseFormatter._handle_data_preparation_task,
            "Capacity Analysis": ResponseFormatter._handle_bed_capacity_task,
            "Facilities with Greatest Declines": ResponseFormatter._handle_facility_declines_task,
            "Long-Term Care Capacity Assessment": ResponseFormatter._handle_long_term_care_task,
            "Operational Recommendations": ResponseFormatter._handle_recommendations_task,
            "Future Integration Opportunities": ResponseFormatter._handle_integration_task,
            "Patient Satisfaction Analysis": ResponseFormatter._handle_patient_satisfaction_task,
            "Staff Utilization Analysis": ResponseFormatter._handle_staff_utilization_task,
            "Equipment Inventory Assessment": ResponseFormatter._handle_equipment_task,
            "Financial Analysis": ResponseFormatter._handle_financial_task,
            "Quality Metrics Analysis": ResponseFormatter._handle_quality_metrics_task,
            "Geographic Distribution Analysis": ResponseFormatter._handle_geographic_distribution_task,
            "Healthcare Access Analysis": ResponseFormatter._handle_access_task,
            "Wait Time Analysis": ResponseFormatter._handle_wait_time_task,
            "Population Health Analysis": ResponseFormatter._handle_population_health_task,
            "Emergency Services Analysis": ResponseFormatter._handle_emergency_services_task,
            "Specialized Care Analysis": ResponseFormatter._handle_specialized_care_task,
            "Preventive Care Analysis": ResponseFormatter._handle_preventive_care_task,
            "Telehealth Analysis": ResponseFormatter._handle_telehealth_task,
            "Research and Innovation Analysis": ResponseFormatter._handle_research_task
        }
        
        # Combine default handlers with any dynamically registered handlers
        handler_map = {**default_handler_map, **ResponseFormatter._handler_map}
        
        if section_header in handler_map:
            return handler_map[section_header](task_description, analysis_results)
        else:
            # Use generic handler for unknown task types
            return ResponseFormatter._handle_generic_task(section_header, task_description, analysis_results)
    
    @staticmethod
    def register_handler(section_header: str, handler_function: Callable):
        """Register a new handler for a specific section header"""
        ResponseFormatter._handler_map[section_header] = handler_function
    
    @staticmethod
    def _handle_generic_task(section_header: str, task_description: str, analysis_results: Dict[str, Any]) -> str:
        """Handle generic tasks that don't match specific patterns"""
        response = f"## {section_header}\n\n"
        
        # Try to find relevant data in analysis_results
        relevant_data = {}
        
        # Look for data keys that might be related to the task
        task_keywords = section_header.lower().split()
        for key, value in analysis_results.items():
            key_lower = key.lower()
            if any(keyword in key_lower for keyword in task_keywords):
                relevant_data[key] = value
        
        if relevant_data:
            for key, value in relevant_data.items():
                if isinstance(value, dict) and value:
                    response += f"### {key.replace('_', ' ').title()}\n\n"
                    for subkey, subvalue in value.items():
                        if isinstance(subvalue, (int, float)):
                            response += f"**{subkey.replace('_', ' ').title()}**: {subvalue:,}\n\n"
                        elif isinstance(subvalue, str):
                            response += f"**{subkey.replace('_', ' ').title()}**: {subvalue}\n\n"
                        elif isinstance(subvalue, list):
                            response += f"**{subkey.replace('_', ' ').title()}**:\n\n"
                            for item in subvalue[:5]:  # Show first 5 items
                                if isinstance(item, dict):
                                    for item_key, item_value in item.items():
                                        response += f"- {item_key.replace('_', ' ').title()}: {item_value}\n"
                                else:
                                    response += f"- {item}\n"
                            response += "\n"
                elif isinstance(value, (int, float)):
                    response += f"**{key.replace('_', ' ').title()}**: {value:,}\n\n"
                elif isinstance(value, str):
                    response += f"**{key.replace('_', ' ').title()}**: {value}\n\n"
        else:
            response += "No specific analysis results available for this task.\n\n"
            response += "This task requires specialized analysis that may not be available in the current dataset.\n"
        
        return response
    
    @staticmethod
    def _handle_data_preparation_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle data preparation task"""
        response = "## Data Preparation\n\n"
        
        if "data_preparation" not in analysis_results:
            return response + "No data preparation results available"
        
        data_prep = analysis_results["data_preparation"]
        
        # Facility type frequency
        if "facility_type_frequency" in data_prep:
            response += "### Facility Type Frequency\n\n"
            response += "| Facility Type | Count |\n"
            response += "|---------------|-------|\n"
            for ftype, count in data_prep["facility_type_frequency"].items():
                response += f"| {ftype} | {count} |\n"
            response += "\n"
        
        # Top cities with facility breakdown
        if "top_cities" in data_prep and "city_facility_breakdown" in data_prep:
            response += "### Top Cities by Facility Count\n\n"
            response += "| City | Hospitals | Nursing/Residential | Ambulatory | Total |\n"
            response += "|------|-----------|-------------------|------------|-------|\n"
            
            for city in data_prep["top_cities"]:
                if city in data_prep["city_facility_breakdown"]:
                    breakdown = data_prep["city_facility_breakdown"][city]
                    hospitals = breakdown.get("Hospitals", 0)
                    nursing = breakdown.get("Nursing and residential care facilities", 0)
                    ambulatory = breakdown.get("Ambulatory health care services", 0)
                    total = hospitals + nursing + ambulatory
                    response += f"| {city} | {hospitals} | {nursing} | {ambulatory} | {total} |\n"
            
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_bed_capacity_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle bed capacity analysis task"""
        response = "## Capacity Analysis\n\n"
        
        if "capacity_analysis" not in analysis_results:
            return response + "No capacity analysis results available"
        
        capacity = analysis_results["capacity_analysis"]
        
        # Bed capacity by zone
        if "bed_capacity_by_zone" in capacity:
            response += "### Bed Capacity by Zone\n\n"
            response += "| Zone | Current Beds | Previous Beds | Absolute Change | Percentage Change |\n"
            response += "|------|--------------|---------------|-----------------|-------------------|\n"
            for zone, data in capacity["bed_capacity_by_zone"].items():
                current = data.get("beds_current", 0)
                previous = data.get("beds_prev", 0)
                abs_change = current - previous
                perc_change = (abs_change / previous * 100) if previous > 0 else 0
                response += f"| {zone} | {current:,} | {previous:,} | {abs_change:+,} | {perc_change:+.1f}% |\n"
            response += "\n"
        
        # Zones with largest decreases
        if "zone_with_largest_absolute_decrease" in capacity:
            response += f"**Zone with Largest Absolute Decrease**: {capacity['zone_with_largest_absolute_decrease']}\n\n"
        
        if "zone_with_largest_percentage_decrease" in capacity:
            response += f"**Zone with Largest Percentage Decrease**: {capacity['zone_with_largest_percentage_decrease']}\n\n"
        
        return response
    
    @staticmethod
    def _handle_facility_declines_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle facilities with greatest declines task"""
        response = "## Facilities with Greatest Declines\n\n"
        
        if "capacity_analysis" not in analysis_results or "facilities_with_declines" not in analysis_results["capacity_analysis"]:
            return response + "No facility decline data available"
        
        facilities = analysis_results["capacity_analysis"]["facilities_with_declines"]
        
        response += "| Facility Name | Zone | Teaching Status | Bed Change |\n"
        response += "|---------------|------|----------------|------------|\n"
        for facility in facilities[:5]:  # Top 5
            name = facility.get("facility_name", "")
            zone = facility.get("zone", "")
            teaching = facility.get("teaching_status", "")
            change = facility.get("bed_change", 0)
            response += f"| {name} | {zone} | {teaching} | {change:+,} |\n"
        
        return response
    
    @staticmethod
    def _handle_long_term_care_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle long-term care capacity assessment task"""
        response = "## Long-Term Care Capacity Assessment\n\n"
        
        if "long_term_care_assessment" not in analysis_results:
            return response + "No long-term care assessment results available"
        
        ltc = analysis_results["long_term_care_assessment"]
        
        # Zone with largest percentage decrease
        if "zone_with_largest_percentage_decrease" in ltc:
            response += f"**Zone with Largest Percentage Decrease**: {ltc['zone_with_largest_percentage_decrease']}\n\n"
        
        # Major city in that zone
        if "major_city_in_zone" in ltc:
            response += f"**Major City in Zone**: {ltc['major_city_in_zone']}\n\n"
        
        # Facility counts in major city
        if "facility_counts" in ltc:
            counts = ltc["facility_counts"]
            response += "### Facility Counts in Major City\n\n"
            response += f"- Hospitals: {counts.get('hospitals', 0)}\n"
            response += f"- Nursing/Residential Care Facilities: {counts.get('nursing_residential_care', 0)}\n"
            response += f"- Ambulatory Health Services: {counts.get('ambulatory', 0)}\n\n"
        
        # Nursing to hospital ratio
        if "nursing_to_hospital_ratio" in ltc:
            ratio = ltc["nursing_to_hospital_ratio"]
            response += f"**Nursing/Residential to Hospital Ratio**: {ratio:.2f}\n\n"
        
        # Capacity assessment
        if "capacity_assessment" in ltc:
            assessment = ltc["capacity_assessment"]
            response += f"**Long-Term Care Capacity Assessment**: {assessment.upper()}\n\n"
            
            if assessment == "insufficient":
                response += "The ratio of nursing/residential care facilities to hospitals is below the recommended threshold of 1.5. "
                response += "This indicates insufficient long-term care capacity to support the healthcare system in this area.\n\n"
            else:
                response += "The ratio of nursing/residential care facilities to hospitals meets or exceeds the recommended threshold. "
                response += "This indicates sufficient long-term care capacity.\n\n"
        
        return response
    
    @staticmethod
    def _handle_recommendations_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle operational recommendations task"""
        response = "## Operational Recommendations\n\n"
        
        if "recommendations" not in analysis_results or not analysis_results["recommendations"]:
            return response + "No recommendations available"
        
        recommendations = analysis_results["recommendations"]
        
        # Group by priority
        high_priority = [r for r in recommendations if r.get("priority") == "High"]
        medium_priority = [r for r in recommendations if r.get("priority") == "Medium"]
        low_priority = [r for r in recommendations if r.get("priority") == "Low"]
        
        if high_priority:
            response += "### High Priority Recommendations\n\n"
            for i, rec in enumerate(high_priority, 1):
                response += f"**{i}. {rec.get('title', 'Recommendation')}**\n\n"
                response += f"{rec.get('description', '')}\n\n"
                if "justification" in rec:
                    response += f"**Justification**: {rec['justification']}\n\n"
                if "expected_impact" in rec:
                    response += f"**Expected Impact**: {rec['expected_impact']}\n\n"
                response += "---\n\n"
        
        if medium_priority:
            response += "### Medium Priority Recommendations\n\n"
            for i, rec in enumerate(medium_priority, 1):
                response += f"**{i}. {rec.get('title', 'Recommendation')}**\n\n"
                response += f"{rec.get('description', '')}\n\n"
                if "justification" in rec:
                    response += f"**Justification**: {rec['justification']}\n\n"
                if "expected_impact" in rec:
                    response += f"**Expected Impact**: {rec['expected_impact']}\n\n"
                response += "---\n\n"
        
        if low_priority:
            response += "### Low Priority Recommendations\n\n"
            for i, rec in enumerate(low_priority, 1):
                response += f"**{i}. {rec.get('title', 'Recommendation')}**\n\n"
                response += f"{rec.get('description', '')}\n\n"
                if "justification" in rec:
                    response += f"**Justification**: {rec['justification']}\n\n"
                if "expected_impact" in rec:
                    response += f"**Expected Impact**: {rec['expected_impact']}\n\n"
                response += "---\n\n"
        
        return response
    
    @staticmethod
    def _handle_integration_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle future integration opportunities task"""
        response = "## Future Integration Opportunities\n\n"
        
        if "future_integration" not in analysis_results:
            return response + "No integration opportunities identified"
        
        integration = analysis_results["future_integration"]
        
        # Summary
        if "summary" in integration:
            response += f"{integration['summary']}\n\n"
        
        # Opportunities
        if "opportunities" in integration:
            for i, opp in enumerate(integration["opportunities"], 1):
                response += f"**{i}. {opp.get('title', 'Opportunity')}**\n\n"
                response += f"{opp.get('description', '')}\n\n"
                
                if "benefits" in opp:
                    response += "**Benefits:**\n"
                    for benefit in opp["benefits"]:
                        response += f"- {benefit}\n"
                    response += "\n"
                
                if "challenges" in opp:
                    response += "**Challenges:**\n"
                    for challenge in opp["challenges"]:
                        response += f"- {challenge}\n"
                    response += "\n"
                
                if "example_metric_or_model" in opp:
                    response += f"**Example Metric/Model**: {opp['example_metric_or_model']}\n\n"
                
                if "timeline" in opp:
                    response += f"**Timeline**: {opp['timeline']}\n\n"
                
                response += "---\n\n"
        
        return response
    
    @staticmethod
    def _handle_patient_satisfaction_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle patient satisfaction analysis task"""
        response = "## Patient Satisfaction Analysis\n\n"
        
        if "patient_satisfaction" not in analysis_results:
            return response + "No patient satisfaction data available"
        
        satisfaction = analysis_results["patient_satisfaction"]
        
        # Overall satisfaction
        if "overall_satisfaction" in satisfaction:
            response += f"**Overall Patient Satisfaction**: {satisfaction['overall_satisfaction']:.1f}/5.0\n\n"
        
        # Satisfaction by category
        if "satisfaction_by_category" in satisfaction:
            response += "### Satisfaction by Category\n\n"
            response += "| Category | Score |\n"
            response += "|----------|-------|\n"
            for category, score in satisfaction["satisfaction_by_category"].items():
                response += f"| {category} | {score:.1f}/5.0 |\n"
            response += "\n"
        
        # Trends
        if "satisfaction_trends" in satisfaction:
            response += "### Satisfaction Trends\n\n"
            response += "| Period | Satisfaction Score |\n"
            response += "|--------|-------------------|\n"
            for period, score in satisfaction["satisfaction_trends"].items():
                response += f"| {period} | {score:.1f}/5.0 |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_staff_utilization_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle staff utilization analysis task"""
        response = "## Staff Utilization Analysis\n\n"
        
        if "staff_utilization" not in analysis_results:
            return response + "No staff utilization data available"
        
        staff = analysis_results["staff_utilization"]
        
        # Overall utilization
        if "overall_utilization" in staff:
            response += f"**Overall Staff Utilization**: {staff['overall_utilization']:.1%}\n\n"
        
        # Utilization by role
        if "utilization_by_role" in staff:
            response += "### Utilization by Role\n\n"
            response += "| Role | Utilization Rate |\n"
            response += "|------|------------------|\n"
            for role, rate in staff["utilization_by_role"].items():
                response += f"| {role} | {rate:.1%} |\n"
            response += "\n"
        
        # Staffing levels
        if "staffing_levels" in staff:
            response += "### Staffing Levels\n\n"
            response += "| Role | Current Staff | Recommended Staff | Gap |\n"
            response += "|------|---------------|-------------------|-----|\n"
            for role, data in staff["staffing_levels"].items():
                current = data.get("current", 0)
                recommended = data.get("recommended", 0)
                gap = current - recommended
                response += f"| {role} | {current} | {recommended} | {gap:+} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_equipment_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle equipment inventory assessment task"""
        response = "## Equipment Inventory Assessment\n\n"
        
        if "equipment_inventory" not in analysis_results:
            return response + "No equipment inventory data available"
        
        equipment = analysis_results["equipment_inventory"]
        
        # Total equipment value
        if "total_value" in equipment:
            response += f"**Total Equipment Value**: ${equipment['total_value']:,.2f}\n\n"
        
        # Equipment by category
        if "equipment_by_category" in equipment:
            response += "### Equipment by Category\n\n"
            response += "| Category | Count | Total Value |\n"
            response += "|----------|-------|-------------|\n"
            for category, data in equipment["equipment_by_category"].items():
                count = data.get("count", 0)
                value = data.get("value", 0)
                response += f"| {category} | {count} | ${value:,.2f} |\n"
            response += "\n"
        
        # Utilization rates
        if "utilization_rates" in equipment:
            response += "### Equipment Utilization Rates\n\n"
            response += "| Equipment Type | Utilization Rate |\n"
            response += "|----------------|------------------|\n"
            for eq_type, rate in equipment["utilization_rates"].items():
                response += f"| {eq_type} | {rate:.1%} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_financial_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle financial analysis task"""
        response = "## Financial Analysis\n\n"
        
        if "financial_analysis" not in analysis_results:
            return response + "No financial analysis data available"
        
        financial = analysis_results["financial_analysis"]
        
        # Total budget
        if "total_budget" in financial:
            response += f"**Total Budget**: ${financial['total_budget']:,.2f}\n\n"
        
        # Expenditure by category
        if "expenditure_by_category" in financial:
            response += "### Expenditure by Category\n\n"
            response += "| Category | Amount | Percentage |\n"
            response += "|----------|--------|------------|\n"
            for category, data in financial["expenditure_by_category"].items():
                amount = data.get("amount", 0)
                percentage = data.get("percentage", 0)
                response += f"| {category} | ${amount:,.2f} | {percentage:.1f}% |\n"
            response += "\n"
        
        # Cost per patient
        if "cost_per_patient" in financial:
            response += f"**Average Cost per Patient**: ${financial['cost_per_patient']:,.2f}\n\n"
        
        # Financial trends
        if "financial_trends" in financial:
            response += "### Financial Trends\n\n"
            response += "| Period | Revenue | Expenditure | Surplus/Deficit |\n"
            response += "|--------|---------|-------------|-----------------|\n"
            for period, data in financial["financial_trends"].items():
                revenue = data.get("revenue", 0)
                expenditure = data.get("expenditure", 0)
                surplus = revenue - expenditure
                response += f"| {period} | ${revenue:,.2f} | ${expenditure:,.2f} | ${surplus:+,.2f} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_quality_metrics_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle quality metrics analysis task"""
        response = "## Quality Metrics Analysis\n\n"
        
        if "quality_metrics" not in analysis_results:
            return response + "No quality metrics data available"
        
        quality = analysis_results["quality_metrics"]
        
        # Overall quality score
        if "overall_quality_score" in quality:
            response += f"**Overall Quality Score**: {quality['overall_quality_score']:.1f}/100\n\n"
        
        # Quality indicators
        if "quality_indicators" in quality:
            response += "### Quality Indicators\n\n"
            response += "| Indicator | Current Value | Target | Status |\n"
            response += "|-----------|---------------|--------|--------|\n"
            for indicator, data in quality["quality_indicators"].items():
                current = data.get("current", 0)
                target = data.get("target", 0)
                status = "✅ Met" if current >= target else "❌ Not Met"
                response += f"| {indicator} | {current:.1f} | {target:.1f} | {status} |\n"
            response += "\n"
        
        # Trends
        if "quality_trends" in quality:
            response += "### Quality Trends\n\n"
            response += "| Period | Quality Score |\n"
            response += "|--------|---------------|\n"
            for period, score in quality["quality_trends"].items():
                response += f"| {period} | {score:.1f}/100 |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_geographic_distribution_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle geographic distribution analysis task"""
        response = "## Geographic Distribution Analysis\n\n"
        
        if "geographic_distribution" not in analysis_results:
            return response + "No geographic distribution data available"
        
        geo = analysis_results["geographic_distribution"]
        
        # Total facilities
        if "total_facilities" in geo:
            response += f"**Total Facilities**: {geo['total_facilities']:,}\n\n"
        
        # Distribution by region
        if "distribution_by_region" in geo:
            response += "### Distribution by Region\n\n"
            response += "| Region | Facility Count | Population Served | Facilities per 100K |\n"
            response += "|--------|----------------|-------------------|-------------------|\n"
            for region, data in geo["distribution_by_region"].items():
                count = data.get("facility_count", 0)
                population = data.get("population_served", 0)
                per_100k = (count / population * 100000) if population > 0 else 0
                response += f"| {region} | {count:,} | {population:,} | {per_100k:.1f} |\n"
            response += "\n"
        
        # Access inequality
        if "gini_coefficient" in geo:
            gini = geo["gini_coefficient"]
            level = "High" if gini > 0.4 else "Moderate" if gini > 0.2 else "Low"
            response += f"**Access Inequality**: {level} (Gini coefficient: {gini:.2f})\n\n"
        
        return response
    
    @staticmethod
    def _handle_access_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle healthcare access analysis task"""
        response = "## Healthcare Access Analysis\n\n"
        
        if "healthcare_access" not in analysis_results:
            return response + "No healthcare access data available"
        
        access = analysis_results["healthcare_access"]
        
        # Overall access score
        if "overall_access_score" in access:
            response += f"**Overall Access Score**: {access['overall_access_score']:.1f}/100\n\n"
        
        # Access by service type
        if "access_by_service" in access:
            response += "### Access by Service Type\n\n"
            response += "| Service Type | Access Score | Wait Time (Days) | Availability |\n"
            response += "|--------------|-------------|-----------------|-------------|\n"
            for service, data in access["access_by_service"].items():
                score = data.get("access_score", 0)
                wait_time = data.get("wait_time_days", 0)
                availability = data.get("availability", "N/A")
                response += f"| {service} | {score:.1f}/100 | {wait_time:.1f} | {availability} |\n"
            response += "\n"
        
        # Barriers to care
        if "barriers_to_care" in access:
            response += "### Top Barriers to Care\n\n"
            for i, barrier in enumerate(access["barriers_to_care"][:5], 1):
                response += f"{i}. {barrier}\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_wait_time_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle wait time analysis task"""
        response = "## Wait Time Analysis\n\n"
        
        if "wait_time_analysis" not in analysis_results:
            return response + "No wait time data available"
        
        wait_time = analysis_results["wait_time_analysis"]
        
        # Average wait time
        if "average_wait_time" in wait_time:
            response += f"**Average Wait Time**: {wait_time['average_wait_time']:.1f} days\n\n"
        
        # Wait time by service
        if "wait_time_by_service" in wait_time:
            response += "### Wait Time by Service\n\n"
            response += "| Service | Average Wait (Days) | Target Wait (Days) | Status |\n"
            response += "|---------|-------------------|-------------------|--------|\n"
            for service, data in wait_time["wait_time_by_service"].items():
                current = data.get("current_wait", 0)
                target = data.get("target_wait", 0)
                status = "✅ Met" if current <= target else "❌ Exceeded"
                response += f"| {service} | {current:.1f} | {target:.1f} | {status} |\n"
            response += "\n"
        
        # Trends
        if "wait_time_trends" in wait_time:
            response += "### Wait Time Trends\n\n"
            response += "| Period | Average Wait (Days) |\n"
            response += "|--------|-------------------|\n"
            for period, wait in wait_time["wait_time_trends"].items():
                response += f"| {period} | {wait:.1f} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_population_health_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle population health analysis task"""
        response = "## Population Health Analysis\n\n"
        
        if "population_health" not in analysis_results:
            return response + "No population health data available"
        
        health = analysis_results["population_health"]
        
        # Total population
        if "total_population" in health:
            response += f"**Total Population**: {health['total_population']:,}\n\n"
        
        # Health indicators
        if "health_indicators" in health:
            response += "### Key Health Indicators\n\n"
            response += "| Indicator | Value | Target |\n"
            response += "|-----------|-------|--------|\n"
            for indicator, data in health["health_indicators"].items():
                value = data.get("value", 0)
                target = data.get("target", 0)
                response += f"| {indicator} | {value:.1f} | {target:.1f} |\n"
            response += "\n"
        
        # Disease burden
        if "disease_burden" in health:
            response += "### Top Causes of Disease Burden\n\n"
            response += "| Disease | DALYs | Percentage |\n"
            response += "|---------|-------|------------|\n"
            for disease, data in health["disease_burden"].items():
                dalys = data.get("dalys", 0)
                percentage = data.get("percentage", 0)
                response += f"| {disease} | {dalys:,} | {percentage:.1f}% |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_emergency_services_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle emergency services analysis task"""
        response = "## Emergency Services Analysis\n\n"
        
        if "emergency_services" not in analysis_results:
            return response + "No emergency services data available"
        
        emergency = analysis_results["emergency_services"]
        
        # Total ER visits
        if "total_er_visits" in emergency:
            response += f"**Total ER Visits**: {emergency['total_er_visits']:,}\n\n"
        
        # ER utilization
        if "er_utilization" in emergency:
            response += "### ER Utilization Metrics\n\n"
            response += "| Metric | Value |\n"
            response += "|--------|-------|\n"
            for metric, value in emergency["er_utilization"].items():
                if isinstance(value, float):
                    response += f"| {metric.replace('_', ' ').title()} | {value:.1f} |\n"
                else:
                    response += f"| {metric.replace('_', ' ').title()} | {value} |\n"
            response += "\n"
        
        # Wait times
        if "er_wait_times" in emergency:
            response += "### ER Wait Times\n\n"
            response += "| Triage Level | Average Wait (Hours) | Target Wait (Hours) |\n"
            response += "|--------------|---------------------|---------------------|\n"
            for level, data in emergency["er_wait_times"].items():
                current = data.get("current_wait", 0)
                target = data.get("target_wait", 0)
                response += f"| {level} | {current:.1f} | {target:.1f} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_specialized_care_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle specialized care analysis task"""
        response = "## Specialized Care Analysis\n\n"
        
        if "specialized_care" not in analysis_results:
            return response + "No specialized care data available"
        
        specialized = analysis_results["specialized_care"]
        
        # Total specialized facilities
        if "total_specialized_facilities" in specialized:
            response += f"**Total Specialized Facilities**: {specialized['total_specialized_facilities']:,}\n\n"
        
        # Services by specialty
        if "services_by_specialty" in specialized:
            response += "### Services by Specialty\n\n"
            response += "| Specialty | Facility Count | Patient Volume | Wait Time (Days) |\n"
            response += "|-----------|----------------|----------------|-----------------|\n"
            for specialty, data in specialized["services_by_specialty"].items():
                count = data.get("facility_count", 0)
                volume = data.get("patient_volume", 0)
                wait_time = data.get("wait_time_days", 0)
                response += f"| {specialty} | {count} | {volume:,} | {wait_time:.1f} |\n"
            response += "\n"
        
        # Access metrics
        if "access_metrics" in specialized:
            response += "### Access Metrics\n\n"
            response += "| Metric | Value |\n"
            response += "|--------|-------|\n"
            for metric, value in specialized["access_metrics"].items():
                if isinstance(value, float):
                    response += f"| {metric.replace('_', ' ').title()} | {value:.1f} |\n"
                else:
                    response += f"| {metric.replace('_', ' ').title()} | {value} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_preventive_care_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle preventive care analysis task"""
        response = "## Preventive Care Analysis\n\n"
        
        if "preventive_care" not in analysis_results:
            return response + "No preventive care data available"
        
        preventive = analysis_results["preventive_care"]
        
        # Screening coverage
        if "screening_coverage" in preventive:
            response += "### Screening Coverage Rates\n\n"
            response += "| Screening Type | Coverage Rate | Target |\n"
            response += "|----------------|---------------|--------|\n"
            for screening, data in preventive["screening_coverage"].items():
                current = data.get("current_rate", 0)
                target = data.get("target_rate", 0)
                response += f"| {screening} | {current:.1%} | {target:.1%} |\n"
            response += "\n"
        
        # Vaccination rates
        if "vaccination_rates" in preventive:
            response += "### Vaccination Rates\n\n"
            response += "| Vaccine | Coverage Rate | Herd Immunity Threshold |\n"
            response += "|---------|---------------|------------------------|\n"
            for vaccine, data in preventive["vaccination_rates"].items():
                coverage = data.get("coverage_rate", 0)
                threshold = data.get("herd_immunity_threshold", 0)
                status = "✅ Achieved" if coverage >= threshold else "❌ Not Achieved"
                response += f"| {vaccine} | {coverage:.1%} | {threshold:.1%} | {status} |\n"
            response += "\n"
        
        # Wellness programs
        if "wellness_programs" in preventive:
            response += "### Wellness Program Participation\n\n"
            response += "| Program | Participants | Completion Rate |\n"
            response += "|---------|-------------|-----------------|\n"
            for program, data in preventive["wellness_programs"].items():
                participants = data.get("participants", 0)
                completion = data.get("completion_rate", 0)
                response += f"| {program} | {participants:,} | {completion:.1%} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_telehealth_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle telehealth analysis task"""
        response = "## Telehealth Analysis\n\n"
        
        if "telehealth" not in analysis_results:
            return response + "No telehealth data available"
        
        telehealth = analysis_results["telehealth"]
        
        # Total virtual visits
        if "total_virtual_visits" in telehealth:
            response += f"**Total Virtual Visits**: {telehealth['total_virtual_visits']:,}\n\n"
        
        # Adoption metrics
        if "adoption_metrics" in telehealth:
            response += "### Telehealth Adoption Metrics\n\n"
            response += "| Metric | Value |\n"
            response += "|--------|-------|\n"
            for metric, value in telehealth["adoption_metrics"].items():
                if isinstance(value, float):
                    response += f"| {metric.replace('_', ' ').title()} | {value:.1f} |\n"
                else:
                    response += f"| {metric.replace('_', ' ').title()} | {value} |\n"
            response += "\n"
        
        # Satisfaction
        if "patient_satisfaction" in telehealth:
            response += "### Patient Satisfaction with Telehealth\n\n"
            response += "| Aspect | Satisfaction Score |\n"
            response += "|--------|-------------------|\n"
            for aspect, score in telehealth["patient_satisfaction"].items():
                response += f"| {aspect} | {score:.1f}/5.0 |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _handle_research_task(task: str, analysis_results: Dict[str, Any]) -> str:
        """Handle research and innovation analysis task"""
        response = "## Research and Innovation Analysis\n\n"
        
        if "research_innovation" not in analysis_results:
            return response + "No research and innovation data available"
        
        research = analysis_results["research_innovation"]
        
        # Active trials
        if "active_clinical_trials" in research:
            response += f"**Active Clinical Trials**: {research['active_clinical_trials']:,}\n\n"
        
        # Research areas
        if "research_areas" in research:
            response += "### Research Focus Areas\n\n"
            response += "| Area | Number of Projects | Funding |\n"
            response += "|------|-------------------|---------|\n"
            for area, data in research["research_areas"].items():
                projects = data.get("projects", 0)
                funding = data.get("funding", 0)
                response += f"| {area} | {projects} | ${funding:,.2f} |\n"
            response += "\n"
        
        # Innovation metrics
        if "innovation_metrics" in research:
            response += "### Innovation Metrics\n\n"
            response += "| Metric | Value |\n"
            response += "|--------|-------|\n"
            for metric, value in research["innovation_metrics"].items():
                if isinstance(value, float):
                    response += f"| {metric.replace('_', ' ').title()} | {value:.1f} |\n"
                else:
                    response += f"| {metric.replace('_', ' ').title()} | {value} |\n"
            response += "\n"
        
        return response
    
    @staticmethod
    def _generate_executive_summary(results: Dict[str, Any]) -> str:
        """Generate executive summary based on analysis results"""
        summary = []
        
        if "capacity_analysis" in results:
            capacity = results["capacity_analysis"]
            if "total_capacity" in capacity:
                summary.append(f"Total system capacity: {capacity['total_capacity']:,} beds")
            if "average_utilization" in capacity:
                summary.append(f"Average utilization: {capacity['average_utilization']:.1%}")
        
        if "facility_distribution" in results:
            dist = results["facility_distribution"]
            if "geographic_inequality" in dist:
                inequality = dist["geographic_inequality"]
                level = "High" if inequality > 0.4 else "Moderate" if inequality > 0.2 else "Low"
                summary.append(f"Geographic distribution inequality: {level} (Gini: {inequality:.2f})")
        
        if "recommendations" in results:
            high_priority = [r for r in results["recommendations"] if r.get("priority") == "High"]
            if high_priority:
                summary.append(f"{len(high_priority)} high-priority recommendations identified")
        
        if "validation" in results:
            completion_rate = results["validation"].get("completion_rate", 0)
            summary.append(f"Analysis completion rate: {completion_rate:.1%}")
        
        return " | ".join(summary) if summary else "No key metrics identified"
    
    @staticmethod
    def _format_validation_results(validation: Dict[str, Any]) -> str:
        """Format validation results"""
        response = f"**Analysis Completion Rate**: {validation['completion_rate']:.1%}\n\n"
        
        if validation["all_tasks_completed"]:
            response += "✅ All required tasks were completed successfully.\n\n"
        else:
            response += "⚠️ The following tasks were not completed:\n\n"
            for task in validation["missing_tasks"]:
                response += f"- {task}\n"
            response += "\n"
        
        return response