Post-de-identification summarization¶

OpenMed's clinical summarization stage is generative-last. The public openmed.clinical.summarize() entry point de-identifies a note first, then passes only the de-identified text to a summarizer backend. A deterministic extractive fallback is used when no backend is supplied.

from openmed.clinical import summarize

result = summarize(note)
assert result.leakage_check.passed
print(result.summary)

The leakage guard compares the summary with the source spans identified by the de-identification result. A backend that re-emits a source identifier is rejected before a result is returned. The check exposes counts and digests, not plaintext identifiers.

Pipeline code that already performed de-identification may call summarize_deidentified() with its DeidentificationResult. Passing a plain string to that guarded stage raises an ordering error.

The default path is local and deterministic. A trained SLM backend is a separate task and must be supplied as a local or on-device callable; this stage never selects a cloud model or sends raw PHI to one. Summaries are assistive outputs and require qualified clinical review.