{"categories":[{"label":"Quality Assurance","url":"https://skillfed.io/packages/category/software-development-quality-assurance/3"}],"enrichment":{"capability":"EMRValidator is a data validation library specialized for healthcare datasets, offering built-in validators for medical record numbers, ICD codes, and other clinical data formats alongside general data quality checks.","skillfed_tags":["healthcare-data","data-validation","etl-pipeline"],"use_cases":["Validate patient demographics, MRN formats, and clinical codes in ETL pipelines before loading to a data warehouse","Generate data quality reports and profiling summaries for healthcare datasets to identify missing or malformed records","Define and reuse custom validation rule sets for claims data, encounter records, or revenue cycle management workflows","Run real-time data quality checks on incoming clinical data in Airflow, dbt, or LLM pipeline contexts","Validate ICD-9 and ICD-10 diagnosis codes and other healthcare-specific formats in bulk data migrations"],"what_it_does":"EMRValidator is a Python data validation library designed for healthcare and clinical datasets. It provides a fluent API for chaining validation rules, with built-in support for healthcare-specific formats like MRN and ICD codes, alongside standard checks for nulls, ranges, uniqueness, and date formats. The library depends only on pandas and includes data profiling and HTML/JSON report generation.\n\nIt positions itself as a lighter alternative to Great Expectations, targeting healthcare ETL pipelines, data warehouses, and clinical analytics workflows. The package offers multiple API styles\u2014fluent chaining, expectation suites, and reusable rule sets\u2014and includes pre-built rule sets for common healthcare scenarios like patient demographics and financial data validation.","worth_installing":"Yes, if you are validating healthcare or clinical datasets and want a lightweight, pandas-based alternative to heavier frameworks. The low install friction and healthcare-specific validators make it well-suited for ETL and data warehouse contexts. However, note the aging maintenance status (200 days since last release) and verify Python version support before committing to production use."},"id":"emrvalidator","links":{"html":"https://skillfed.io/packages/emrvalidator","md":"https://skillfed.io/packages/emrvalidator.md","pypi":"https://pypi.org/project/emrvalidator/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2026-01-26","license_spdx":null,"license_treatment":"permissive","name":"emrvalidator","python_support":"unspecified","summary":"A Data Validation Tool for Healthcare Data"},"popularity":{"monthly_downloads":242555,"position":8852,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.2"}