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ISO - Certivication

Research Area

Model-based medicine

Prof. Dr. Thomas Neumuth

Project Coordination

Alexander Oeser

Partners

    Martin-Luther-University Halle
    MEDIFINA GmbH, Wien
    Wroclaw Medical University, Poland
    KfH Kuratorium für Dialyse und Nierentransplantation e.V., Neu-Isenburg
    HeartBalance GmbH, Wien
    Hospital Universitario Fundación Jiménez Díaz, Madrid

Funder

Förderlogo

headline-markerProDial

Patient-Reported Outcome, Biodata and Process Data to Evaluate Dialysis Tolerability

Hemodialysis treatment affects only 0.1% of the total population. However, this complex, long-term and chronic procedure requires 5 to 10% of the total health care costs in industrialized countries. Although the treatment ensures life-sustaining detoxification, it does not prevent the 5 to 10 times higher mortality of those affected patients with end-stage renal disease compared to the general population.

Nowadays, quality and process control of hemodialysis treatment is based on a general evaluation of biochemical and procedural measures, which does not really influence the individual patient’s outcome in terms of mortality and dialysis tolerance. For this reason, the ProDial project aims to develop an individual analysis of the dialysis treatment and a personalized data generation and handling scheme. For this purpose, time-synchronous data of different dialysis aspects will be collected and evaluated. This includes patient and therapy characteristics, biomedical real-time feedback, process information and patient reported outcomes. Innovative and anonymized data collection methods, including the integration of portable personal devices and sensors, will ensure integrated, searchable and personalized data storage.

Novel mechanisms for finding significant correlations between the referenced data categories should enable the development of personalized real-time dialysis treatment procedures in the long term. These data-based algorithms can then be integrated into modern and intelligent dialysis centers and, thus, facilitate a truly personalized real-time treatment. Such a treatment would respond immediately to the individual co-morbidity and tolerability behavior of the patient.

Link to project page