exporting-bulk-fhir

仓库创建 2025年10月4日最近提交 3 小时前SkillHot 收录 3 小时前
▸ 精选理由

适合队列化大规模临床文本摄取与去标识化。

▸ 风险提示

需要访问含PHI的FHIR端点并下载数据,涉及敏感权限与合规风险。

这个 Skill 做什么

启动并收集FHIR Bulk Data $export,将NDJSON流入OpenMed批处理管道。

发起并收集 FHIR 的 Bulk Data $export 异步任务,把拿到的 NDJSON 流式导入到批量的 OpenMed 去标识化和 NER 管道里。适合需要整批人群级别的病历文本抽取而不是单病人场景,比如从 EHR 或数据仓库导出大量文档。关键点是处理异步启动、轮询 Content-Location、下载 NDJSON 并按批次喂给去标识化流程,能做大规模自动化入库。

▸ 展开 SKILL.md 英文原文

Kick off and harvest a FHIR Bulk Data $export (system-, group-, or patient-level) and stream the resulting NDJSON into a batch OpenMed de-identification + NER pipeline at cohort scale. Covers the async kickoff (Prefer respond-async) -> poll Content-Location -> download NDJSON flow, the Bulk Data Access IG, _type/_since filters, and feeding DocumentReference/DiagnosticReport notes into openmed.deidentify in batch. Use when the user needs population-scale note extraction from an EHR or data warehouse to feed OpenMed, mentions bulk export, $export, NDJSON, Flat FHIR, or cohort de-identification. Pairs before the OpenMed de-id/NER pipeline.

垂直行业FHIR导出批量数据NDJSON去标识化通用
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# Exporting Bulk FHIR

When you need *cohort-scale* clinical text — not one patient in a UI — you use
the FHIR **Bulk Data Access** (`$export`) operation: an async job that emits
**NDJSON** files of resources you then stream into OpenMed for batch
de-identification and NER. This skill sits **before** the OpenMed pipeline: it is
how the notes arrive.

## When to use

Reach for it when the source is an EHR or FHIR data warehouse and the volume is
a population/group (thousands of patients), the workload is headless (no
clinician UI), and the goal is to batch-feed `openmed.deidentify` /
`openmed.analyze_text`. Triggers: "bulk export", "$export", "NDJSON", "Flat
FHIR", "cohort de-identification",
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