Complexity of biomedical data models in cardiology: the Intranet-based XXXX registry.

@entity1 @entity943 @entity955
@entity955 ( @entity955 ) is the most common @entity943 and is associated with major complications. Ongoing research is focused on new pacing devices for alternative treatment of this disease. The objective of an @entity955 registry is to store prospectively all relevant data covering clinical information, quality of life and device parameters and by this means provide a platform for long-term follow-up. For statistical analysis, categorical and numerical items are required, thus a high-granular data structure must be defined and implemented in the clinical setting. Facing the limits of formalization, we developed an XML-based documentation scheme consisting of 619 items in eight tables and implemented it with state-of-the-art Intranet technology. At present detailed information on 88 @entity1 is recorded. The pacing device generates per @entity1 and follow-up visit a file consisting of approximately 400-500 parameters provided on a floppy disk, which are transferred by means of a specific interface into the database. Success factors for integration of a complex research database into the routine workflow of a busy university hospital are interfaces between data sources to enable non-redundant data entry, intensive fine tuning by iterative software engineering and benefit for the clinical users in form of clinical reports and @entity1 -specific summaries. Data quality must be assured by plausibility checks. To get an overview of this complex dataset we developed a dedicated visualization tool. Due to the high number of items a large @entity1 collective must be recruited for statistical evaluation. Interinstitutional cooperation is required for a consensus on common minimal documentation schemes to enable pooling of data.
