Data Diversity & Fairness Auditor (DDFA)

Independent algorithmic bias detection and data diversity governance for clinical AI systems.

Schedule a DDFA Demonstration Assess AI Maturity (EAMA)

Intersectional Bias Auditing via HL7 FHIR R4 in Minutes

Healthcare AI models frequently inherit historic disparities embedded in clinical training data. DDFA is Synod IntelliCare's core auditing engine, engineered to identify intersectional bias across complex demographic variables including age, gender, race, geography, and socioeconomic determinants in minutes.

Operating via our Sidecar Protocol, DDFA conducts deep retrospective analysis on historical EHR data extracts without requiring live EHR integration queues or IT disruption.

Key Specifications

  • Intersectional Disparity Mapping: Evaluates combined demographic subgroups rather than single-variable metrics.
  • Sidecar Protocol: Operates on de-identified historical data extracts to decouple governance readiness from IT backlogs.
  • Regulatory Alignment: Generates automated compliance reports aligned with ACA Section 1557, Colorado AI Act, and EU AI Act.
  • On-Demand Auditing: Audits care recommendations on demand via HL7 FHIR R4 middleware integration.

DDFA Technical Architecture & Data Pipeline

DDFA Simplified Architecture Diagram - HL7 FHIR R4 Middleware

Figure: HL7 FHIR R4 Middleware & Sidecar Retrospective Audit Architecture.