❤️ PyHeart - Healthcare Interoperability & Workflow Engine

PyHeart is the integration layer of the BrainSAIT Healthcare Unification Platform, providing universal healthcare system connectivity, workflow orchestration, and secure data exchange.

🚀 Features

• Universal API Gateway: Single interface for all healthcare system integrations
• Event-Driven Architecture: Real-time data streaming and processing
• Microservices Framework: Modular, scalable healthcare services
• Security & Compliance Engine: HIPAA, GDPR, and regional compliance automation
• Workflow Orchestration: Complex healthcare process automation

📦 Installation

pip install pyheart

For development:

pip install pyheart[dev]

For legacy system support:

pip install pyheart[legacy]

🔧 Quick Start

FHIR Client Usage

from pyheart import FHIRClient

# Connect to FHIR server
client = FHIRClient("https://fhir.example.com")

# Get patient
patient = client.get_patient("12345")
print(f"Patient: {patient}")

# Search patients
bundle = client.search("Patient", {"family": "Smith", "birthdate": "ge1970"})
for entry in bundle.get("entry", []):
    print(f"Found: {entry['resource']['id']}")

# Create patient
new_patient = {
    "resourceType": "Patient",
    "name": [{"given": ["John"], "family": "Doe"}],
    "gender": "male",
    "birthDate": "1990-01-01"
}
created = client.create(new_patient)

Workflow Engine

from pyheart import WorkflowEngine, ProcessDefinition, Task

# Define a clinical process
process = ProcessDefinition(
    id="medication-reconciliation",
    name="Medication Reconciliation Process",
    tasks=[
        Task(
            id="fetch-current-meds",
            name="Fetch Current Medications",
            type="api_call",
            config={
                "url": "${fhir_server}/MedicationRequest?patient=${patient_id}",
                "method": "GET"
            }
        ),
        Task(
            id="analyze-interactions",
            name="Analyze Drug Interactions",
            type="transformation",
            dependencies=["fetch-current-meds"],
            config={
                "transform": {"type": "drug_interaction_check"}
            }
        )
    ]
)

# Execute workflow
engine = WorkflowEngine()
engine.register_process(process)

instance_id = await engine.start_process(
    "medication-reconciliation",
    {"patient_id": "12345", "physician_email": "dr.smith@example.com"}
)

Healthcare System Integration

from pyheart import IntegrationHub, FHIRAdapter, HL7Adapter

# Setup integration hub
hub = IntegrationHub()

# Register adapters for different systems
hub.register_adapter("hospital_a", FHIRAdapter("hospital_a"))
hub.register_adapter("lab_system", HL7Adapter("lab_system"))

# Connect to systems
await hub.connect_system("hospital_a", {"base_url": "https://hospital-a.com/fhir"})
await hub.connect_system("lab_system", {"host": "lab.hospital.com", "port": 2575})

# Fetch data from all systems
patient_data = await hub.fetch_from_all_systems("Patient", {"id": "12345"})

CLI Usage

# FHIR operations
pyheart fhir -s https://fhir.example.com -r Patient -i 12345
pyheart fhir -s https://fhir.example.com -r Observation -q '{"patient": "12345"}'

# Run workflows
pyheart workflow -f medication-check.json -v '{"patient_id": "12345"}'

# Start server
pyheart serve --port 8000

# Sync data between systems
pyheart sync -s https://old.example.com -t https://new.example.com -r Patient

# System diagnostics
pyheart doctor

🏗️ Architecture

PyHeart provides a layered architecture for healthcare integration:

pyheart/
├── core/
│   ├── client/      # FHIR and legacy clients
│   ├── server/      # API gateway and FHIR server
│   ├── workflow/    # Process orchestration
│   ├── integration/ # System adapters
│   └── security/    # Auth and encryption
├── adapters/        # Legacy system adapters
├── messaging/       # Event streaming
└── api/            # REST/GraphQL APIs

🤝 Integration with PyBrain

PyHeart and PyBrain work together seamlessly:

from pyheart import FHIRClient, WorkflowEngine
from pybrain import AIEngine, DataHarmonizer

# Use PyHeart for data access
client = FHIRClient("https://fhir.example.com")
observations = client.search("Observation", {"patient": "12345"})

# Use PyBrain for intelligence
ai = AIEngine()
harmonizer = DataHarmonizer()

# Process observations with AI
for entry in observations.get("entry", []):
    obs = entry["resource"]
    
    # Harmonize if needed
    if obs.get("meta", {}).get("source") != "unified":
        obs = harmonizer.harmonize_to_fhir(obs, "custom", "Observation")
    
    # AI analysis
    risk = ai.predict_risk_score({"patient_id": "12345"})
    
    # Trigger workflow if high risk
    if risk > 0.8:
        engine = WorkflowEngine()
        await engine.start_process("high-risk-intervention", {
            "patient_id": "12345",
            "risk_score": risk
        })

🔒 Security & Compliance

PyHeart includes comprehensive security features:

from pyheart import SecurityManager, AuthProvider

# Configure security
security = SecurityManager()
security.enable_encryption("AES-256-GCM")
security.enable_audit_logging()
security.configure_compliance(["HIPAA", "GDPR"])

# OAuth2/SMART on FHIR authentication
auth = AuthProvider("oauth2")
token = await auth.get_token(
    client_id="app-123",
    scope="patient/*.read launch"
)

# Use authenticated client
client = FHIRClient(
    base_url="https://fhir.example.com",
    auth_token=token
)

🌟 Advanced Features

Multi-System Client

from pyheart import HealthcareClient

# Query multiple systems simultaneously
client = HealthcareClient()
client.add_fhir_system("hospital_a", FHIRClient("https://a.example.com"))
client.add_fhir_system("hospital_b", FHIRClient("https://b.example.com"))

# Unified patient record
unified_patient = await client.get_unified_patient("12345")

Workflow Orchestration

• Visual workflow designer compatible
• Event-driven triggers
• Human task management
• Error handling and retries
• Parallel and sequential execution

Legacy System Support

• HL7v2 messaging
• DICOM integration
• X12 transactions
• Custom adapter framework

📚 Documentation

Full documentation available at: https://pyheart.readthedocs.io

Quick Links

• API Reference
• Workflow Guide
• Integration Patterns
• Security Best Practices

🧪 Testing

# Run tests
pytest

# With coverage
pytest --cov=pyheart

# Integration tests
pytest tests/integration --integration

🚀 Deployment

Docker

docker run -p 8000:8000 brainsait/pyheart:latest

Kubernetes

apiVersion: apps/v1
kind: Deployment
metadata:
  name: pyheart
spec:
  replicas: 3
  selector:
    matchLabels:
      app: pyheart
  template:
    spec:
      containers:
      - name: pyheart
        image: brainsait/pyheart:latest
        ports:
        - containerPort: 8000

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

PyHeart is licensed under the Apache License 2.0. See LICENSE for details.

🌟 Acknowledgments

Built with ❤️ by the BrainSAIT Healthcare Innovation Lab

Special thanks to:

• The FHIR community for excellent standards
• FastAPI for the amazing web framework
• All our contributors and users

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Together with PyBrain, PyHeart is building the future of connected healthcare.