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Aims and Objectives
There is a scarcity or often even absence to have patient reported outcomes data available in a structured fashion. Where data is digitally recorded they
often reside in well-protected silos. Several processes still rely on manual and paper-based processes. Additionally, patients are plagued with repeating even basics such as giving their medical history from provider to provider.
LeMeDaRT aims to build a ”liquid data” concept to link and digitally support the patient journey from population health over prevention to interaction of rural care including complex interventions. The core goal is to provide the right relevant data in each instance during the patient journey to leverage patient benefit and provider efficiency.
The task of our group is to develop data visualizations for end-users in the digital hub from data in the system, enriched by external or currently available additional information on clinical courses to provide a significant improvement for both decision makers and individuals. From a mathematical point of view, these procedures use Bayes' theorem, translating this into comprehensible information. At a later stage these algorithms can be extended by neural networks and other forms of machine learning.