Aurea Health: Knowledge Architecture & Risk Analysis

PART 1: Knowledge Graph Design

Mapping the Aurea Health ecosystem across the Trinity Graph.

Section 1: Core Entities (Nodes)

• Social Nodes: Patient, Provider, Care Team, Family Member, Referral Network.
• Knowledge Nodes: Symptom, Condition, Treatment Protocol, Diagnostic Criteria, Regulatory Requirement (HIPAA).
• Generative Nodes: Predictive Care Pathway, Risk Stratification Profile, Outcome Forecast.

Section 2: The Triples (Edges/Relationships)

Format: [Subject] → [Predicate] → [Object]

The Knowledge Layer (Clinical Grounding):

1. [Symptom] → maps_to → [Condition]
2. [Condition] → treated_by → [Treatment Protocol]
3. [Treatment Protocol] → constrained_by → [Regulatory Requirement]

The Cross-Graph Traversal (Social → Knowledge → Generative):

4. [Patient] → has_trust_level_with → [Provider]
5. [Provider] → executes → [Treatment Protocol]
6. [Longitudinal Patient Data] → synthesizes_into → [Predictive Care Pathway]

PART 2: "What We Don't Know" (Risk Analysis)

Section 3: The Assumption Ledger

• Data Liquidity Assumption: We are assuming that cross-specialty, longitudinal patient data is actually accessible and not trapped in siloed legacy EHRs.
• Semantic Precision Assumption: We assume that different medical specialties use the exact same clinical ontologies (e.g., a Cardiologist and a Neurologist define and code a specific symptom the exact same way).

Section 4: The Risk Register / Epistemic Gaps

• The Regulatory Bottleneck (Knowledge vs. Generative): The Knowledge Layer strictly maps HIPAA requirements, but the Generative Layer requires synthesizing cross-specialty data. Gap: We do not know how to generate cross-specialty insights without triggering compliance violations in the Knowledge Layer.
• The Hallucination Cascade (Generative Risk): If the AI hallucinates a "predictive care pathway," the liability structure is undefined.
• Trust Degradation (Social Risk): The Social Layer tracks "trust levels." If the Generative Layer surfaces a personalized treatment recommendation that contradicts a provider's human judgment, it may fracture the patient-provider relationship.

Section 5: Mitigation Plan

• Data Liquidity Mitigation: Instead of relying on direct EHR API integration (which hospitals will block), Aurea will use patient-mediated data access (patients legally requesting their own records and granting Aurea access).
• Semantic Precision Mitigation: Implement a strict human-in-the-loop review system during the initial cross-specialty mapping phase before allowing the Generative Layer to synthesize predictive pathways autonomously.

Section 6: Kill Criteria

Conditions under which this specific architecture must be abandoned or radically pivoted.

1. Regulatory Kill Switch: If HIPAA compliance audits determine that synthesizing cross-specialty data in the Generative Layer constitutes a "new medical record" requiring FDA approval as a medical device.
2. Provider Adoption Kill Switch: If provider trust levels in the Social Layer drop below baseline because the Generative Layer produces conflicting or hallucinated treatment recommendations.