Objective
Multi-morbid complex chronic conditions (CCCs) are highly prevalent in patients with Chronic Obstructive Pulmonary Disease (COPD). As they have common risk factors and overlapping symptoms, this easily leads to delay of appropriate treatment. Timely and preventive care is essential, as exacerbations of COPD and CCCs are detrimental to patient, health and social outcomes. RE-SAMPLE will take a giant leap in the field of CCC disease management building upon and going beyond existing initiatives, towards evidence-based, inclusive, preventive care and targeted treatment, enabling to “treat a person, not the disease(s)”. RE-SAMPLE will create a knowledge base of multimodal data from health records, clinical studies, expert and patient knowledge and guidelines, and extend this with state-of-the-art Real World Data collection. Predictive modelling through privacy-preserving Artificial Intelligence (AI), will increase the understanding of CCCs including the interdependence of multi-morbidities, and evidence in effective interventions for CCC disease management. The inclusive design and citizen science approach, provides us with credible and accepted RWD tools and a patient-centred eHealth “companionship programme”. GDPR-compliance is carefully integrated from the beginning, and our platform allows for a strong advancement in secure algorithms using multi-party computation. Our AI approach enables statistical validation following clinical standards and useful explanations to build up clinical evidence and trust by the users. As such RE-SAMPLE will act upon the need for diversified, personalized care to alleviate the overall societal and economic burden of these CCCs. The RE-SAMPLE project significantly impact towards this direction not only through the development of the platform and companionship programme, but also through its implementation throughout Europe, enabling and guiding healthcare organizations its uptake in the privacy-sensitive domain of healthcare.
Field of science
- /natural sciences/computer and information sciences/artificial intelligence
Programme(s)
Call for proposal
H2020-SC1-2020-Single-Stage-RTD
See other projects for this call
Funding Scheme
RIA - Research and Innovation actionCoordinator
7522 NB Enschede
Netherlands
Participants (9)
7513 ER Enschede
185 32 Piraeus
50406 Tartu
00168 Roma
1000 Bruxelles
67663 Kaiserslautern
28760 Tres Cantos Madrid
7522 AH Enschede
1200 Bruxelles
