HIPAA Compliance

Understanding HIPAA

The Health Insurance Portability and Accountability Act (HIPAA) is a federal law that establishes national standards for protecting sensitive patient health information. Any system that handles Protected Health Information (PHI) in a clinical setting must comply with HIPAA's Privacy Rule, Security Rule, and Breach Notification Rule.

Our Stance on Privacy and Security

We are deeply committed to the principles of data privacy and security. While the current version of Dimini is a prototype, it has been designed with security best practices in mind, providing a solid foundation for a future, HIPAA-compliant version.

Current Security Measures

Even as a demonstration project, Dimini implements several important security measures:

• Encryption in Transit: All data transmitted between the client, server, and third-party services uses TLS 1.3 encryption
• Encryption at Rest: Database hosted on Supabase with AES-256 encryption for all stored data
• Secure Credential Management: API keys and secrets managed via environment variables, never exposed to frontend
• Authentication: Password hashing using industry-standard bcrypt algorithm
• Database Security: PostgreSQL hosted in SOC 2 Type II certified data centers
• CORS Protection: Strict Cross-Origin Resource Sharing policies to prevent unauthorized access

Steps Required for HIPAA Compliance

For Dimini to be used in a production environment with Protected Health Information (PHI), the following comprehensive measures would need to be implemented:

Administrative Safeguards

• Business Associate Agreements (BAA): Execute BAAs with all third-party vendors that process PHI:
  • Supabase (database and real-time services)
  • OpenAI (GPT-4 and embeddings processing)
  • Any voice transcription service providers
  • Cloud infrastructure providers
• Security Management Process: Establish policies and procedures to prevent, detect, contain, and correct security violations
• Workforce Training: Implement mandatory HIPAA training for all personnel with access to PHI
• Access Management: Implement authorization and supervision procedures for workforce members who access PHI
• Contingency Planning: Develop disaster recovery and business continuity plans with regular testing

Technical Safeguards

• Authentication and Access Control:
  • Multi-factor authentication (MFA) for all users
  • Role-Based Access Control (RBAC) with principle of least privilege
  • Unique user identifiers for audit trail purposes
  • Emergency access procedures with logging
• Audit Controls: Comprehensive logging and monitoring:
  • All PHI access events (read, create, update, delete)
  • Authentication attempts (successful and failed)
  • Administrative actions and configuration changes
  • Logs retained for minimum 6 years
  • Regular log review and anomaly detection
• Data Encryption:
  • TLS 1.3 for all data in transit
  • AES-256 encryption for data at rest
  • Application-level encryption for sensitive fields (transcripts)
  • Encrypted database backups
  • Key management using AWS KMS or similar
• Row-Level Security (RLS): Database-level access controls ensuring users can only access their authorized data
• Session Management:
  • Automatic logout after 15 minutes of inactivity
  • Secure session token management
  • Session invalidation on logout
• Transmission Security: Protect ePHI during transmission over electronic networks

Physical Safeguards

• Data Center Security: Use of SOC 2 Type II certified facilities with physical access controls
• Device and Media Controls: Procedures for disposal and reuse of electronic media containing PHI
• Workstation Security: Policies for securing devices that access PHI

Privacy Rule Requirements

• Patient Consent: Implement clear consent flows for PHI processing and AI analysis
• Notice of Privacy Practices: Provide patients with notice of how their information will be used
• Patient Rights: Enable patients to:
  • Access their PHI
  • Request amendments
  • Receive an accounting of disclosures
  • Request restrictions on uses and disclosures
• Minimum Necessary Standard: Limit PHI use and disclosure to the minimum necessary

Breach Notification

• Incident Response Plan: Procedures for detecting, responding to, and mitigating security incidents
• Breach Notification: Process to notify affected individuals, HHS, and media (if applicable) within required timeframes
• Forensic Capabilities: Tools and procedures to investigate potential breaches

Ongoing Compliance

• Regular Security Assessments: Annual third-party security audits and penetration testing
• Vulnerability Management: Regular scanning and patching of security vulnerabilities
• Privacy Impact Assessments: Evaluate privacy risks for new features
• Policy Review: Annual review and update of all HIPAA policies and procedures

AI-Specific Considerations

Using AI with healthcare data introduces unique compliance challenges:

• Third-Party AI Processing: OpenAI and other AI providers must sign BAAs and agree not to use PHI for model training
• Data Minimization: Consider de-identification or anonymization before sending data to AI services
• Transparency: Patients must be informed that AI is being used to analyze their sessions
• Accuracy and Reliability: Regular validation of AI outputs for clinical accuracy
• Explainability: Ability to explain how AI reached specific insights or connections

Cost and Timeline Estimates

Our Roadmap to Compliance

Achieving full HIPAA compliance is a cornerstone of our long-term vision for Dimini. Our planned approach includes:

• Partnering with HIPAA compliance consultants and legal experts
• Evaluating and selecting vendors with existing BAAs in place
• Implementing comprehensive audit logging and monitoring infrastructure
• Developing robust access control and authentication systems
• Creating detailed security policies and procedures
• Conducting third-party security assessments and penetration tests
• Establishing incident response and breach notification processes

While the current demonstration showcases the technical innovation and potential of AI-assisted therapy visualization, we recognize that patient privacy and data security are paramount for any production deployment in healthcare settings.