Standards and Tools for Data Quality Assessments in Observational Health Studies
Health data must be of high quality to enable sound scientific conclusions. This website provides a data quality framework and tools to systematically check data. Our developments are not only relevant to health-related data sources, such as observational epidemiologic studies, registries, and electronic health record data but can also be applied to data collections in adjacent scientific fields such as social sciences and economics.
Please note. This site will be continuously updated based on feedback from the community.
Current status: Beta 0.9.1.
To collaborate, please see the Community page here. The GitLab repository for dataquieR can be found here.
