Data Ingestion and Decoupling

Event-Based Data Ingestion

Journl Streamed supports ingestion from HL7 v2, X12 transactions, and Apple HealthKit. Incoming data is parsed, mapped to FHIR resources, and stored automatically. This allows Journl to react to real-time clinical updates, such as ADT messages, lab results, or claims data, which are transformed into structured FHIR resources.

The ingestion pipeline includes configurable adapters and mapping logic. Each HL7 message (e.g., ADT) can trigger the creation or update of a Patient, Encounter, or Observation resource, ensuring the platform remains synchronized with external systems.

Initial Loads and Bulk Import

Journl Streamed supports high-performance data ingestion using asynchronous bulk import APIs. These imports can load historical datasets at scale, accepting both standard FHIR bundles and native formats. Journl Streamed supports bypassing validation and history tracking during import to optimize performance, with optional settings to enable full audit/version logging when required.

Data sources for import may include flat files, Synthea-generated records, or exports from legacy systems. Cloud integrations are also supported.

Decoupling External Systems

Journl Streamed decouples input sources from internal logic. All inbound data is normalized into the FHIR model, regardless of origin format. HL7 messages, custom JSON payloads, and FHIR-native APIs all converge into a unified resource schema. This approach enables a modular architecture where frontend applications and analytics pipelines consume a consistent data model.