Medical Classification and Terminology Systems in a Secondary Use Context: Challenges and Perils.

Since the introduction of diagnosis-related groups in the German healthcare system, classifying patient diagnosis and procedures with controlled vocabularies have become mandatory and thus creating a large dataset for secondary use in biomedical research. In this paper we present the analysis of an ICD dataset with regards to potentially reimbursement motivated classification and the effects on precision and recall when considering the change history of ICD codes.

Longitudinal data driven study design.

In this paper we present a method for processing EHR data into a longitudinal data model and examples for using this model to identify patients cross-sectionally and longitudinally as well as testing study designs retrospectively. Our data model describes measurements on four dimensions: the associated patient, observed feature, data source and time of survey. The transformation of structured source data into our model is defined by rules written in XML. To showcase the flexibility of the proposed longitudinal data model, we present an evolution of a retrospective study design as well as an example for interpreting biomarkers in emergency situations. With the proposed longitudinal data model complex queries can be performed, study designs tested and optimized.