extract-clinical-entities-to-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

适合将本地NER结果转换成标准FHIR包以便集成与审计。

▸ 风险提示

处理真实临床文本时需注意PHI与合规性。

这个 Skill 做什么

把OpenMed抽取的临床实体映射为确定性的FHIR R4资源与Bundle。

把 OpenMed 从文本里抽出的临床实体翻成确定性的 FHIR R4 资源和一个 Bundle,方便一键上报到 EHR 或下游系统。适用于把本地或已脱敏的 NER 输出变成 Conditions、MedicationStatement、Observation 等标准资源时使用。输出可重复、结构化,不会凭空发明术语编码。

▸ 展开 SKILL.md 英文原文

Extract clinical entities from synthetic or already de-identified text with OpenMed and map them into deterministic FHIR R4 resources and a Bundle. Use when an agent must turn local clinical NER output into Conditions, MedicationStatements, Observations, or other FHIR resources without inventing terminology codes.

垂直行业实体抽取FHIR Bundle临床编码去标识化通用
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帮我安装这个 skill:https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/extract-clinical-entities-to-fhir/SKILL.md
或 curl 直取 SKILL.md
curl -fsSL "https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/extract-clinical-entities-to-fhir/SKILL.md"
SKILL.MD 节选查看完整文件 ↗
# Extract clinical entities to FHIR

Separate extraction from clinical coding. OpenMed finds spans and supplies the
mechanical FHIR builders; the application decides which resource type and
status are clinically appropriate.

## Procedure

1. Keep the source synthetic, or de-identify it inside the trusted boundary
   before extraction.
2. Run `openmed.analyze_text` with the task-appropriate clinical model.
3. Filter predictions by label and confidence; preserve offsets in a
   PHI-safe audit record.
4. Map each accepted span to the correct FHIR resource type.
5. Add terminology codes only from a user-approved mapping or terminology
   service. Never invent a code.
6. Assemble resources with 
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