exporting-bulk-fhir

You can stream NDJSON files line by line to extract clinical notes from DocumentReference and DiagnosticReport resources during a FHIR bulk export, avoiding loading entire datasets into memory. This approach processes each resource sequentially as the asynchronous download occurs.

SMART Backend Services authentication secures asynchronous FHIR bulk exports by allowing system-level data retrieval and job status polling. It supports downloading NDJSON manifests for group, patient, or system-level EHR exports while maintaining strict clinical data access controls.

Yes, you can run biomedical NER on cohort-scale clinical notes locally by applying de-identification before persistence and using OpenMed biomedical entity recognition. This workflow prevents sending PHI to cloud NLP services while enabling safe clinical analytics and population research.

The correct approach is PHI-safe ordering, where de-identification occurs before persistence of clinical notes extracted from NDJSON streams. This ensures patient data is scrubbed from DocumentReference and DiagnosticReport text before any biomedical NER processing or downstream storage takes place.

Yes, the workflow supports incremental or filtered retrieval for system, group, or patient-level asynchronous FHIR exports. It coordinates bulk export polling, downloads NDJSON manifests, and cleans up completed jobs to manage cohort-scale clinical data extraction efficiently.

Limitations include the necessity of managing asynchronous export polling and streamed resource parsing for large NDJSON files. You must also maintain local infrastructure for PHI-safe de-identification before persistence and handle cohort-scale processing without relying on external cloud NLP services.