Healthcare Semantic Ontology Layer¶

The Semantic Ontology Layer sits between the Data Plane and the Application Catalogue, providing a unified, standards-aligned knowledge graph that resolves entities across EHR/EMR, Revenue Cycle/Billing, Hospital Information System (HIS), Medical Imaging & Lab, Clinical Notes, and Population & External Data sources.

Industry Standards Alignment¶

The healthcare ontology is aligned to global healthcare interoperability and coding standards.

HL7 FHIR (Fast Healthcare Interoperability Resources)¶

The HL7 FHIR standard provides the interoperability framework for clinical data exchange. Every domain in this ontology maps to FHIR resource types:

FHIR Resource	Scope	Ontology Coverage
Patient	Demographics, identifiers, contacts	All 8 apps — Patient_Master
Encounter	Visit/admission/episode tracking	Patient 360, Operational Efficiency, Revenue Cycle
Condition	Diagnoses, problem list	Patient 360, Clinical Decision Support, Population Health
MedicationRequest / MedicationAdministration	Prescriptions, MAR	Clinical Decision Support, Supply Chain & Pharmacy
Observation	Lab results, vitals, assessments	Clinical Decision Support, Clinical Quality
Claim / ExplanationOfBenefit	Billing, reimbursement	Revenue Cycle, Population Health
Procedure	Surgical and clinical procedures	Revenue Cycle, Operational Efficiency

Clinical Coding Standards¶

Standard	Purpose	Ontology Entity
ICD-10-CM/PCS	Diagnosis and procedure coding	`Diagnosis.ICD10_Code`, `Procedure_Record.ICD10_PCS`
CPT / HCPCS	Procedure and service billing codes	`Claim.CPT_Code`, `Charge.HCPCS_Code`
SNOMED CT	Clinical terminology standardization	`Diagnosis.SNOMED_Code`, `Allergy.SNOMED_Code`
LOINC	Lab test identification	`Lab_Result.LOINC_Code`
NDC	Drug identification	`Medication_Order.NDC`, `Pharmacy_Inventory.NDC`
RxNorm	Normalized drug naming	`Medication_Order.RxNorm_CUI`

Regulatory & Quality Frameworks¶

Framework	Purpose	Ontology Entity
HIPAA	Privacy and security of PHI	`PHI_Access_Log`, `Patient_Consent`, privacy policies
CMS Quality Programs	MIPS, IQR, VBP, Promoting Interoperability	`Quality_Measure`, `Regulatory_Return`
HEDIS	Health plan quality measures	`Care_Gap`, `Quality_Measure`
TJC / DNV	Hospital accreditation standards	`Accreditation_Standard`

Architecture¶

graph TD
    subgraph DataPlane [Data Plane - 6 Source Systems]
        EHR["EHR / EMR"]
        RCM["Revenue Cycle / Billing"]
        HIS["Hospital Information System"]
        IMAGING["Medical Imaging & Lab"]
        NOTES["Clinical Notes"]
        POP["Population & External Data"]
    end

    subgraph OntologyLayer [Semantic Ontology Layer]
        SCHEMA["Schema<br/><i>12 Domains · ~50 Tables</i>"]
        WF["Workflows<br/><i>10 FHIR/CMS-aligned</i>"]
        POL["Policies<br/><i>8 Governance Rules</i>"]
        INT["Integrations<br/><i>6 System Mappings</i>"]
    end

    subgraph Apps [Application Catalogue - 8 Apps]
        P360["Patient 360"]
        CDS["Clinical Decision Support"]
        REV["Revenue Cycle"]
        OPS["Operational Efficiency"]
        PHM["Population Health"]
        SUPPLY["Supply & Pharmacy"]
        QUALITY["Clinical Quality"]
        REG["Regulatory Compliance"]
    end

    EHR --> SCHEMA
    RCM --> SCHEMA
    HIS --> SCHEMA
    IMAGING --> SCHEMA
    NOTES --> SCHEMA
    POP --> SCHEMA

    SCHEMA --> WF
    POL --> WF
    INT --> SCHEMA

    WF --> P360
    WF --> CDS
    WF --> REV
    WF --> OPS
    WF --> PHM
    WF --> SUPPLY
    WF --> QUALITY
    WF --> REG

Ontology Components¶

The ontology consists of four interconnected layers, all stored in enterprise-knowledge/:

Layer	Files	Format	Purpose
Schema	`healthcare-schema.yaml`	YAML	12 domains, ~50 tables with fields, types, risk levels, constraints, and relationships
Workflows	`workflows/*.yaml` (10 files)	YAML	Triggered process flows with steps, rules, SLAs, and dependencies
Policies	`policies/*.md` (8 files)	Markdown	Business rules, thresholds, approval chains, and compliance constraints
Integrations	`integrations/*.yaml` (6 files)	YAML	Field-level sync mappings between source systems with conflict resolution

Relationship Types¶

Entities in the schema are connected via typed relationships that form a knowledge graph:

Relationship	Meaning	Example
`triggers`	Entity event initiates a workflow	`Lab_Result` critical flag triggers `Critical Result Management` workflow
`syncs_to`	Entity data flows to another system	`Encounter` syncs_to `Claim` via EHR-RCM integration
`constrained_by`	Entity operations governed by a policy	`Medication_Order` constrained_by `clinical-safety-policy`
`depends_on`	Entity requires a parent/related entity	`Lab_Result` depends_on `Lab_Order`
`validates`	Entity validates another in a clinical process	`Lab_Result` validates `Diagnosis` for clinical confirmation

Cross-Application Entity Heatmap¶

Shows how many of the 8 healthcare apps require each entity. Higher usage = more foundational.

Entity	Count	Applications
`Patient_Master`	8	All apps
`Encounter`	7	All except Supply Chain
`Diagnosis`	6	Patient 360, CDS, Revenue Cycle, Population Health, Quality, Regulatory
`Medication_Order`	4	CDS, Supply/Pharmacy, Quality, Patient 360
`Lab_Result`	4	CDS, Quality, Patient 360, Population Health
`Claim`	3	Revenue Cycle, Population Health, Regulatory
`Vital_Sign`	3	CDS, Quality, Operational Efficiency
`Bed_Census`	2	Operational Efficiency, Patient 360
`Quality_Measure`	2	Quality, Regulatory
`Supply_Inventory`	1	Supply Chain & Pharmacy

Patient_Master is the most connected entity in the healthcare ontology — equivalent to Customer_Master in Banking or Material_Master in Supply Chain.

Schema Statistics¶

Metric	Count
Domains	12
Tables	~50
Source Systems	6 (EHR, RCM, HIS, Imaging/Lab, Notes, Population/External)
Workflows	10
Policies	8
Integrations	6
Relationship Types	5 (triggers, syncs_to, constrained_by, depends_on, validates)
FHIR Resources Covered	12+ (Patient, Encounter, Condition, Medication*, Observation, Claim, Procedure, etc.)

Documentation¶

Document	Description
Schema Reference	Complete domain and table reference with fields, types, and relationships
Workflows	All 10 AI workflow definitions with triggers, steps, and dependencies
Policies	All 8 governance policies with rules, thresholds, and approval chains
Integrations	All 6 system integration mappings with field-level detail
App-Object Mapping	Minimum required objects per application with relationship matrix
Mapping Architecture	Schema-first architecture, Semantic RAG pipeline, and ReAct tools

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