icd-mappings

What it is and what it does

ICD-Mappings is a Python library that translates between ICD diagnostic code systems and clinical classification ontologies. It provides two main classes: Mapper for converting codes between systems (ICD-9 CM to ICD-10 CM, ICD-9 to CCS, ICD-10 to CCSR, and several others), and Validator for checking whether a code is valid within a given ontology. The library handles both single codes and iterables like lists or pandas Series, returning None for unmapped or invalid codes.

The package bundles pre-computed mappings for multiple clinical classification systems including Clinical Classification Software (CCS and CCSR), Chronic Condition Indicators (CCI and CCIR), and Pediatric Complex Chronic Conditions categories. It supports parent-code inference for certain targets (CCI and CCIR) by default, allowing truncated codes to map when all their children agree. Data was last refreshed on 2026-04-27 for ICD-10 chapter and block ranges.

Use it for:

• Convert ICD-9 diagnostic codes to ICD-10 equivalents for healthcare data migration or compliance with updated coding standards.
• Classify ICD codes into broader clinical categories (CCS) to aggregate diagnoses for epidemiological analysis or quality reporting.
• Identify chronic conditions from diagnostic codes using CCI or CCIR for risk stratification or comorbidity tracking.
• Validate incoming ICD-9 or ICD-10 diagnostic and procedure codes in healthcare data pipelines before processing.
• Map pediatric diagnoses to complex chronic condition categories for specialized pediatric population studies.
• Batch-process healthcare claims or EHR data to standardize coding across multiple ICD versions.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Maps ICD diagnostic codes between versions (ICD-9 to ICD-10 and vice versa) and to clinical classification systems like CCS, CCI, and pediatric complex chronic conditions categories with a single function call.

Yes. The package is actively maintained, has no known vulnerabilities, low install friction, and solves a real problem in healthcare data workflows. It is well-suited for anyone working with ICD codes in Python, from data analysts to healthcare IT teams. The MIT license poses no restrictions for typical use.

Install

icd-mappings on PyPI

pip install icd-mappings

uv add icd-mappings

poetry add icd-mappings

Installing icd-mappings

Before you install

Low friction: pure Python wheel with only importlib-resources as a runtime dependency. Active maintenance with a recent release on 2026-04-27 and last commit on 2026-06-25.

License in practice

MIT license permits commercial and private use, modification, and distribution with minimal restrictions—suitable for most healthcare applications.

Quickstart

pip install icd-mappings

from icdmappings import Mapper

mapper = Mapper()
result = mapper.map('29410', source='icd9', target='ccs')
print(result)  # '653'

Verify before relying

• Whether mappings reflect the most current ICD-10 and clinical classification standards beyond the 2026-04-27 extraction date
• Performance characteristics when mapping large batches of codes (thousands or millions)
• Completeness of coverage for all valid ICD-9 and ICD-10 diagnostic codes in the underlying datasets

Package facts

Evidence: icd_mappings-0.6.2-py3-none-any.whl

Tags

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