{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"}],"enrichment":{"capability":"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.","skillfed_tags":["healthcare-data","medical-coding","icd-classification"],"use_cases":["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."],"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.\n\nThe 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.","worth_installing":"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."},"id":"icd-mappings","links":{"html":"https://skillfed.io/packages/icd-mappings","md":"https://skillfed.io/packages/icd-mappings.md","pypi":"https://pypi.org/project/icd-mappings/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-27","license_spdx":null,"license_treatment":"permissive","name":"icd-mappings","python_support":"supports_current","summary":"This python tool enables a variety of mappings between ICD diagnostic codes (International Classification of Diseases) with a single line of code."},"popularity":{"monthly_downloads":210310,"position":9498,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.6.2"}