Ingesting Clinical Documents
Turn scanned faxes, images, and CSV/CDA exports into clean text ready for OpenMed...
Install
npx skills add maziyarpanahi/openmed --skill ingesting-clinical-documents -g -a claude-code -y- Repository
- maziyarpanahi/openmed5.8k
- Category
- Writing
- Updated
- 4d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 1,808 tokens
- Runs scripts
- No, instructions only
What it does
Turn scanned faxes, images, and CSV/CDA exports into clean text ready for OpenMed de-identification and NER, fully on-device. Use when the user has clinical documents (image scans, photographed/faxed notes, tabular CSV/TSV exports, C-CDA XML) and needs OCR or structured intake before openmed.deidentify and openmed.analyze_text, asks about openmed.multimodal, OCR engines (Tesseract / PaddleOCR), tabular redaction, or layout and reading order. Covers the verified ocr() and redact_document() entry points and the ExtractedDocument contract. Pairs before deidentifying-clinical-text and extracting-clinical-entities.
Ingesting Clinical Documents
Clinical text often arrives as scanned faxes, photographed notes, CSV exports, or
C-CDA XML, not plain text. openmed.multimodal converts these into a normalized
ExtractedDocument (clean text + character-offset → source-location spans) so you
can run de-identification and NER. It runs on-device: OCR backends are local,
no document leaves the machine.
When to use
- You have images / scanned faxes of clinical notes and need text out (OCR).
- You have CSV/TSV patient exports that need column-aware handling.
- You have C-CDA XML to flatten into text.
- You are building the intake stage that feeds
openmed.deidentifyandopenmed.analyze_text.
This is the first stage. After intake, hand off to
deidentifying-clinical-text then extracting-clinical-entities.
What is supported today
redact_document dispatches by file extension. Live handlers:
| Input | Extensions | Path |
|---|---|---|
| Images / scans | .png .jpg .jpeg .tif .tiff .bmp .gif .webp | OCR (ocr() / image handler) |
| Tables | .csv .tsv | column-aware tabular redaction |
| C-CDA | .xml (detected as CDA) | stdlib CDA adapter |
PDF and DOCX have no live handler yet, redact_document("x.pdf") raises
UnsupportedDocumentError. Convert PDFs to page images first (or to text with your
own tool) and feed the images through OCR. See
references/multimodal-ingest.md for the full
contract, engines, and the tabular pipeline.
Install
pip install "openmed[multimodal]" # document intake contract + image deps
pip install "openmed[ocr-paddle]" # add the PaddleOCR engine
# Tesseract engine also needs the system binary, e.g.: brew install tesseract
Quick start: OCR an image, then de-identify
The clean two-step intake path. ocr() lives in the submodule (it is intentionally
not re-exported from openmed.multimodal):
