etl-to-omop-cdm SKILL.md skillA
etl-to-omop-cdm from maziyarpanahi/openmed is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add maziyarpanahi/openmed/etl-to-omop-cdm@v1.0Pins v1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- maziyarpanahi/openmed
- Path
skills/etl-to-omop-cdm/SKILL.md- Versions recorded
- 1
- Latest version
- v1.0, committed Jul 20, 2026
- Size
- 7,608 bytes
- Repository stars
- 5,784
- License
- Apache-2.0
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…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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 *not* a clinical NER skill and *not* a code-linking skill;
it assumes both are done.
## Quick start
```python
import openmed
note = "Assessment: type 2 diabetes mellitus. Started metformin 500 mg PO BID. HbA1c 8.2%."
result = openmed.analyze_text(note, output_format="dict")
# result["entities"] -> [{text,label,confidence,start,end}, ...]
# You then code each entity to a SOURCE concept using the OHDSI vocabulary you
…Read the whole file at its exact version.
How to install
mdr add maziyarpanahi/openmed/etl-to-omop-cdm@sha256:7d9f3bfbc78802d1The line at the top of this page pins the label v1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_qv3oq5wxprd6x675)
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Versions
The registry has recorded 1 version of this file, committed on Jul 20, 2026.
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Source
maziyarpanahi/openmed · 5,784 stars · license Apache-2.0 · pushed 2026-11-07 · branch master
API
GET https://markdownregistry.com/api/v1/artifacts/art_qv3oq5wxprd6x675 GET https://markdownregistry.com/api/v1/resolve?ref=maziyarpanahi/openmed/etl-to-omop-cdm GET https://markdownregistry.com/api/v1/blob/7d9f3bfbc78802d1dc94207dd68f53085cafe748b9274b6a9199fcd419cb20bf
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Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.