[The impact of primary data quality and interoperability on the analysis of real-world data].

Real-world data is increasingly becoming the focus of healthcare research in the context of digitization. The timely availability of large amounts of data gives hope that research questions can be answered quickly without additional data collection and that a direct benefit for the care of people can be achieved. Especially in acute care situations, such as heat waves or a pandemic, this can be crucial. But real-world data depend quite significantly on the quality and intent of data collection. It is also influenced by determinations on semantic and syntactic standards that are made for primary data - often considering different use cases. In the context of different initiatives on national and international levels, a holistic view on data collection and evaluation and a regular feedback mechanism between data evaluation and specifications for the collection should be established. By including requirements for secondary data evaluation in the definition processes for data collection, the informative value of the data for research can be increased in the long term.In this discussion paper, the activities for standardized data collection in the context of the digitization initiatives and the corresponding European approaches are first presented. After outlining the effects of these activities on the possibilities and difficulties of data consolidation for the analysis of real-world data, the article calls for an ongoing discourse between the different areas.