Comparability in Cross-National Health Research Using Insurance Claims Data: The Cases of Germany and The Netherlands

OBJECTIVE: Comparison is a key method in learning about what works in health and healthcare. We discuss the importance of comparability in cross-national health research using health insurance claims data, develop a framework to systematically asses these threats and apply it to the German (DaTraV) and Dutch (Vektis) national-level insurance claims datasets. METHODS: We propose a framework of threats to the comparability of health insurance claims databases, which includes three domains: (1) representation of populations compared, (2) data sources and data processing and (3) database contents and availability for research purposes. We apply the framework to analyze the comparability of DaTraV and Vektis databases using publicly available information (organization's websites, scientific publications) and our experiences from an interregional project on rare diseases (EMRaDi). RESULTS: Both databases were created for the same purpose (morbidity-based risk adjustment) and use the same underlying sources of data. Differences in population representation and uncertainty about data processing procedures represent potential sources of incomparability. Access for research purposes is feasible in both databases but may be subject to long processing time. CONCLUSIONS: We find important threats to the comparability of the Dutch and German national insurance claims databases and by extension to validity of any comparative health studies that rely on them. Standard adjustment techniques, making more information available about data collection and processing procedures and adding more diagnosis-related descriptors offer ways to overcome the identified threats to comparability