etl-to-omop-cdm
把NLP结果标准化入OMOP以便ATLAS/分析使用
术语映射和时间戳错误可能影响下游研究结论。
将OpenMed提取并映射的临床实体加载到OMOP CDM v5.4的事件表中。
把 OpenMed 提取并编码好的临床事实加载进 OMOP CDM v5.4 的事件表（如 condition_occurrence、drug_exposure、measurement），以便 OHDSI/ATLAS 做分析。用于把 NLP 从病历里挖到的事实标准化并入库，涵盖 source→standard 映射、必填/可选 CDM 字段和 NLP 专用类型概念，需配合你提供的 OHDSI 词典。
▸ 展开 SKILL.md 英文原文
Map OpenMed-extracted, terminology-coded conditions, drugs, and measurements into OMOP CDM v5.4 clinical tables (condition_occurrence, drug_exposure, measurement) for OHDSI/ATLAS analytics. Use when the user wants to load NLP-derived facts into an OMOP database, build an OHDSI ETL from clinical notes, populate condition_occurrence or drug_exposure from text, or standardize note-derived findings to OMOP standard concepts. Covers the source-to-standard concept mapping pattern, required vs optional CDM fields, type concepts for NLP-derived rows, and the user-supplied OHDSI vocabulary (CONCEPT/CONCEPT_RELATIONSHIP). Consumes coded OpenMed analyze_text output (after SNOMED/RxNorm/LOINC linking) and produces OMOP-conformant rows.
帮我安装这个 skill：https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/etl-to-omop-cdm/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/maziyarpanahi/openmed/master/skills/etl-to-omop-cdm/SKILL.md"# ETL to OMOP CDM The OMOP Common Data Model (CDM) is the OHDSI standard for observational health data. This skill maps **OpenMed-derived clinical facts** — entities from `analyze_text` that you have already linked to a source terminology — into the OMOP clinical event tables `condition_occurrence`, `drug_exposure`, and `measurement`. The NLP runs **on-device**; OMOP loading is a downstream, deterministic transform. ## When to use this skill After you have (a) extracted entities with OpenMed and (b) coded them to a source vocabulary (ICD-10-CM / SNOMED for conditions, RxNorm for drugs, LOINC for labs — see the linking skills). Use this skill to turn those coded facts into OMOP rows. It is