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ccdakit

Python library for generating HL7 C-CDA clinical documents

License: MIT Python 3.8+ Tests Coverage

Important Disclaimers

This is an independent, community project and NOT an official HL7 product.

  • Not affiliated with, endorsed by, or recognized by HL7 International
  • Developed extensively with AI assistance (Claude Code)
  • Requires thorough testing and validation before production use
  • Always consult official HL7 specifications for regulatory compliance

For official HL7 resources: HL7.org

Overview

ccdakit is a Python library for programmatic generation of HL7 C-CDA (Consolidated Clinical Document Architecture) documents. It provides a type-safe, protocol-oriented, and version-aware approach to creating ONC-compliant clinical documents.

Why ccdakit?

Existing C-CDA solutions have limitations:

  • Template-based (Jinja2, XSLT): Hard to validate, verbose context management
  • String manipulation: Error-prone, no type safety
  • Vendor-specific: Locked to particular EHR systems
  • No version management: Can't easily support multiple C-CDA versions

Key Features

Feature Description
Multi-version Support C-CDA R2.1, R2.0
Build-time validation XSD/Schematron validation during generation
Protocol-oriented No inheritance required, works with any data model
Type-safe Full type hints, IDE autocomplete
Composable Reusable builders for common elements
Pure Python Only dependency: lxml

Quick Example

from ccdakit import (
    ClinicalDocument,
    ProblemsSection,
    MedicationsSection,
    CDAVersion,
)

# Your data models automatically work!
doc = ClinicalDocument(
    patient=my_patient,
    sections=[
        ProblemsSection(problems=problems_list, version=CDAVersion.R2_1),
        MedicationsSection(medications=meds_list, version=CDAVersion.R2_1),
    ],
    version=CDAVersion.R2_1,
)

# Generate valid, ONC-compliant C-CDA R2.1 XML
xml = doc.to_string(pretty=True)

Current Status

Version: 0.1.0-alpha (MVP Complete)

✅ 29 Complete Clinical Sections

✅ 1,903 tests, 94% coverage

✅ XSD validation support

Getting Started

License

MIT License - see License for details.

Disclaimer: This project is not affiliated with HL7 International. HL7® and C-CDA® are registered trademarks of Health Level Seven International. This is an independent implementation developed with extensive AI assistance. Always validate against official specifications before production use.