OpenSAFELY

Designed specifically for researchers, ehrQL allows users to create dataset definitions that generate comprehensive datasets with one row per patient, facilitating efficient data extraction from both primary and secondary care sources, as well as organizations like the Office for National Statistics (ONS). With a strong emphasis on reproducibility, transparency, and patient privacy, ehrQL standardizes data management tasks, promoting best practices in health data research.

The documentation for ehrQL is structured into four main sections: tutorials for practical learning, how-to guides for project implementation, reference materials for deeper understanding, and explanatory content to guide users through the language's features. Whether you're looking to resolve specific data queries or improve your workflow, ehrQL offers a variety of tools and resources to enhance your research experience. For feedback or inquiries regarding unsupported features, users can contact the support team directly at the Bennett Institute.