Grantová schéma: Horizon 2020 - Research and Innovation Action
Výzva: Use of Real-World Data to advance research on the management of complex chronic conditions
Vyhlásenie výzvy: 04.07.2019
Ukončenie výzvy: 04.06.2020
Popis:

https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/sc1-dth-12-2020;freeTextSearchKeyword=SC1-DTH-12-2020;typeCodes=0,1;statusCodes=31094501,31094502,31094503;programCode=null;programDivisionCode=null;focusAreaCode=null;crossCuttingPriorityCode=null;callCode=Default;sortQuery=openingDate;orderBy=asc;onlyTenders=false;topicListKey=topicSearchTablePageState

 

Specific Challenge:

The number of people with chronic illness is growing and almost half of them have multiple chronic conditions. Patients with complex chronic conditions (CCCs) have chronic multi-morbidities or chronic disease complications that require the attention of multiple health care providers or facilities as well as home-based care. A patient with CCC presents to the health care system with unique constellation of needs, disabilities, or functional limitations[1].

Managing patients with complex chronic conditions therefore needs approaches that ensure multi-disciplinary, personalised and well accepted by the patient ways of care and monitoring.

The controlled randomised clinical trials on chronic diseases provide important information that can be translated in the daily clinical practice, but they often do not comprise sufficient breadth and depth commensurate to the complexity of diseases, and to the degree of personalisation of treatment needed.

Real World Data (referring specifically to any type of data not collected in a randomised clinical trial) can complement these to fill the knowledge gap between controlled clinical trials results and clinical practice needs in real environments. They can provide new insights into disease patterns and help improve the safety and effectiveness of health interventions.

Tapping into this rich resource of ‘real world data’ issued from daily clinical practice, either collected on a permanent/regular basis by public bodies or through devices and mobile applications, , and smartly assembled in combination with clinical studies, should boost both output and relevance of controlled clinical research results.

Scope:

The topic will support clinical research integrating Real World Data from clinical practice or from patient’s daily life and linking them with data collected with a research purpose if relevant.).

The research focus will be on the use of real world data, either newly acquired or from existing sources (such as data from clinical professional societies/associations, cohorts, registers, biobanks or collected through genome research initiatives) to improve the clinical management of adults with complex chronic conditions. The use of new technologies for data analytics and interpretation such as artificial intelligence and computer modelling are encouraged.

The proposed intervention should allow better treatment or monitoring of the person and thus changes in disease progression and/or therapy response. Quality of life, patient safety, psychosocial aspects and well-being are important determinants of complex health conditions and should be addressed whenever relevant. The research should also assess the potential and use of RWD for different health authorities like regulators of safety and quality or health technology assessment bodies. Nevertheless, research has to take duly into account sex and gender differences.

The proposed intervention must add clinical value as well as societal benefits and show feasibility and sustainability in real-life settings. In order to ensure acceptability and sustainability of the intervention early involvement of patients and care providers in the design of the research is considered essential. Similarly, proposals should duly take into account the diversity of health systems in different regions of Europe.

Data protection, data privacy and ethical issues[2] have to be carefully considered as personal data from different sources are to be linked in the course of the proposed research. Data sets assembled under the project, including the linkage to ‘real world data’ should be preserved in a sustainable and accessible way so as to enable future research on the targeted CCC, thus contributing to the overall imperative of Open Science.

Research that focuses on self-management only is not in the scope of this topic. Research on rare and/or infectious diseases are supported through other sections of the programme and are excluded from the scope of this topic.

The Commission considers that proposals requesting a contribution from the EU of between EUR 4 and 6 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.

Expected Impact:

Demonstrate the potential of the use multi-disciplinary multi-source Real World Data to advance clinical research on complex chronic conditions;

Demonstrate potential and use of RWD, in particular RWD from disease-specific professional societies/associations, by health authorities to understand safety, quality and effectiveness of therapies;

Improve the clinical outcomes as well as quality of life of patients living with CCCs;

Advance the understanding of management of complex diseases including the interdependence of co-morbidities, thus underpinning evidence based therapies and prognostic approaches;

Further development of new technological tools and platforms for advanced data management;

Contribution to the cross-border health data exchange and to the goals of the Digital Single Market[3].

Cross-cutting Priorities:

Open Innovation
Gender

[1]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2150604/

[2]http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/ethics/h2020_hi_ethics-data-protection_en.pdf

[3]https://ec.europa.eu/digital-single-market/en/news/communication-enabling-digital-transformation-health-and-care-digital-single-market-empowering