The relevance of empirical health research depends strongly on the quality of data sets. The number of respective frameworks is therefore numerous including public, regulatory, and scientific approaches. A comprehensive literature review served as the starting point for a revision of a German guideline for data quality management. The developed IDEFIM framework consists of five layers: categories, dimensions, quality indicators, quality indicator instances, and quality checks. Additionally to data quality, according to ISO 8000, the framework defines metadata quality, context quality and openness quality as categories. Of 718 different proposals from 99 sources, IDEFIM summarizes 655 in 21 dimensions, 18 covered by ISO/IEC 25012. Further work will include an enhanced structure of quality indicators and an updated indicator set.