03. NDPR for Nigerian Healthcare

Nigeria's data protection framework has evolved significantly since the Nigeria Data Protection Regulation (NDPR) of 2019. The Nigeria Data Protection Act (NDPA) of 2023 replaced the original regulation, establishing clearer requirements for healthcare organizations handling Nigerian patient data.

Healthcare data receives heightened protection under Nigerian law. The NHA (National Health Act) imposes specific restrictions on health information disclosure. Patient consent requirements for data processing are more stringent than general commercial contexts. The National Information Technology Development Agency (NITDA) serves as the primary regulatory authority, with Data Protection Officers required for organizations processing significant volumes of personal data.

For AI systems, the consent requirements create specific implementation constraints. Unlike US frameworks that permit processing under treatment relationships, Nigerian law requires explicit consent for secondary uses of health data, including AI processing. This means clinical AI systems must implement consent management that captures patient authorization for AI-assisted analysis.

# consent_manager.py
from datetime import datetime
from enum import Enum
from typing import Optional
from dataclasses import dataclass

class ConsentType(Enum):
    TREATMENT = "treatment"
    AI_ANALYSIS = "ai_analysis"
    RESEARCH = "research"
    THIRD_PARTY_SHARING = "third_party_sharing"

@dataclass
class PatientConsent:
    patient_id: str
    consent_type: ConsentType
    granted: bool
    timestamp: datetime
    version: str  # Consent form version for audit
    expiry_date: Optional[datetime] = None

class NDPRConsentManager:
    def __init__(self, db_connection):
        self.db = db_connection
        
    def record_consent(self, consent: PatientConsent) -> bool:
        """Record patient consent with required NDPR fields."""
        # Verify consent form version matches current legal requirements
        current_version = self._get_current_consent_version()
        if consent.version != current_version:
            raise ValueError(
                f"Consent form version mismatch: "
                f"expected {current_version}, got {consent.version}"
            )
        
        # Store consent with 6-year retention per NDPR requirements
        self._store_consent(consent)
        return True
    
    def verify_consent(self, patient_id: str, 
                       required_consent: ConsentType) -> bool:
        """Verify valid consent exists before data processing."""
        consent = self._get_latest_consent(patient_id, required_consent)
        if not consent or not consent.granted:
            return False
        
        # Check expiry if specified
        if consent.expiry_date and consent.expiry_date < datetime.utcnow():
            return False
            
        return True
    
    def _get_current_consent_version(self) -> str:
        # Returns current approved consent form version
        return "2.1"

The NDPA introduces requirements around data minimization and purpose limitation that align well with local AI deployment. Processing health data locally inherently limits third-party access and creates auditable boundaries around data use.