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Klinische Datenintelligenz

Goals

As a goal of the project the paradigm of “data intelligence” for clinical applications should be made available. By “data intelligence” is meant here is that solutions are developed and validated directly from a typically large data set: data reflect the complexity of reality with all its nuances and developed solutions found by the direct means of validation clinical acceptance.

In a university hospital of maximum care and related research as the Erlangen University Hospital were built in the last 50 years in all fields of medicine very many different databases in the context of digitization represents. The diversity currently makes an integrated visualization or even processing with underlying common ontologies or ordering hierarchies impossible.

Projects with defined medical use case definitions are therefore in all cases, a piece of work and subsequent product development almost impossible. In order to provide a synopsis of the data sources for everyday medical practice but also for subsequent (Remind-) projects or methods of artificial intelligence, is a systematic analysis of the data and diversity of a concept for the ontologically guided work-up and utilization of data aim of this project.

To this end, patient data must be evaluated holistically, ie it must be all “tracks” that leaves a patient in the clinic, collected and processed; we focus not on a particular disease or a particular modality. This holistic view, a feature of the project is to identify at first inconspicuous dependencies across departmental boundaries and evaluate possible. Furthermore, patient data must be supplied in large volumes available, ie the foundation must be a comprehensive data repository as possible. The introduction of the electronic patient record, it is possible for the first time, to systematically create such a data repository with data from different sources!

This data repository is intended to form the basis for that in this, but also in subsequent projects, clinical processes across different clinics and comparative periods can be analyzed, and that solutions can be developed and tested for decision support. The comparative analysis makes it possible to develop after intensive discussion with medical expert clinical concrete proposals for improving patient care, to detect deviations from standard and the reasons for and to recognize trends early. In the best sense, it should be the aim to evaluate the collective knowledge of clinics, which is reflected in the daily decisions concerning the patient (Collective Intelligence).