Data Diversity and Fairness Auditor (DDFA)
Independent algorithmic bias detection and data diversity governance for clinical AI systems.
Retrospective & Point-of-Care Intersectional Bias Auditing
Healthcare AI models frequently inherit historic disparities embedded in clinical training data. The Data Diversity and Fairness Auditor (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.
Operating via our non-disruptive Sidecar Protocol, DDFA conducts deep retrospective analysis on historical EHR data extracts without requiring live EHR integration queues or IT disruption.
Key Features & Specifications
- ✔ Intersectional Disparity Mapping: Evaluates combined demographic subgroups rather than single-variable metrics.
- ✔ Sidecar Audit Architecture: Operates on de-identified historical data extracts to decouple governance readiness from IT backlogs.
- ✔ Regulatory Compliance Alignment: Generates automated compliance reports aligned with ACA Section 1557, Colorado AI Act, and EU AI Act.
- ✔ Synthetic & Real-World Validation: Validated against Synthea clinical datasets and emergency care presentations.
Built for Clinical Risk Officers & Data Scientists
DDFA generates granular technical statistical outputs for data science teams alongside high-level risk heatmaps for clinical governance committees.
Clinical Safety
Detects model under-performance in vulnerable patient cohorts before automated triage decisions lead to clinical harm.
Legal & Regulatory
Provides documented audit trails and ongoing lifecycle monitoring required by federal and provincial AI frameworks.
Vendor Evaluation
Serves as an independent audit layer for health systems evaluating third-party commercial AI vendor claims.