HORIZON EUROPE
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Specific Challenge:The ageing of the population together with the rising burden of chronic conditions (incl. mental diseases) and multi-morbidity bring an ever increasing demand to strengthen disease prevention and integrate service delivery around people's needs for health and social care.
It is widely recognised that health systems must put more emphasis on prevention and adopt a person-centred rather than a disease-centred approach. The goal must be to overcome service fragmentation and to move towards integration and coordination of interventions along the continuum of care.
Personalised early risk prediction models, estimating the probability that a specific event occurs in a given individual over a predefined time, can enable earlier and better intervention, prevent negative consequences on a person’s quality of life and thus result in improved individual health outcomes.
The challenge is to develop and validate these comprehensive models based on AI or other state of the art technologies for prediction, prevention and intervention using multiple available data resources and to integrate them in personalised health and care pathway...
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Specific Challenge:The ageing of the population together with the rising burden of chronic conditions (incl. mental diseases) and multi-morbidity bring an ever increasing demand to strengthen disease prevention and integrate service delivery around people's needs for health and social care.
It is widely recognised that health systems must put more emphasis on prevention and adopt a person-centred rather than a disease-centred approach. The goal must be to overcome service fragmentation and to move towards integration and coordination of interventions along the continuum of care.
Personalised early risk prediction models, estimating the probability that a specific event occurs in a given individual over a predefined time, can enable earlier and better intervention, prevent negative consequences on a person’s quality of life and thus result in improved individual health outcomes.
The challenge is to develop and validate these comprehensive models based on AI or other state of the art technologies for prediction, prevention and intervention using multiple available data resources and to integrate them in personalised health and care pathways that empower individuals to actively contribute to risk mitigation, prevention and targeted intervention.
Scope:Proposals should build on results of projects[1] and the state of the art in ICT for early risk prediction and introduce innovative ICT solutions through data, data analytics, advanced or novel digital technologies, services, products, organisational changes, and citizens data ownership, that lead to more effective health and care systems. These innovative ICT based solutions may address one or multiple conditions and explore ways of inducing adequate personalised preventive measures (e.g. behavioural change, diet, interventions, medication, primary prevention) from advanced predictive models. Sustainable behaviour change refers to efforts to change people's personal habits to prevent disease, stimulate healthy people to monitor their health parameters and thus lowering the risk of developing (chronic) conditions.
Proposals should build on the use of already existing and/or new data generated by individuals, health professionals and other service providers (including but not limited to data collected through IoT enabled devices, wearables, mobile devices, data source networks or data lakes etc. collected outside the controlled environment of clinical trials) by citizens, healthcare professionals, public authorities and industry, with a view to developing personalised early risk prediction, prevention and intervention approaches that meet the needs of individuals while providing them with adequate information to support informed decision making, improve the uptake of preventive approaches and lead to better health outcomes.
Proposals should also include actions aimed at increasing health literacy, including the role of the citizen as owner of his or her own personal data, as well as advancing health and care professionals' proficiency in novel, data-oriented health services through the use of digital solutions to increase knowledge about diseases and help them in the interpretation of symptoms and effects (e.g. with visualisations like dashboards, etc.), notably of early warning signs and medical information. Early warning signs relay to either healthy people monitoring several body parameters e.g. to conduct healthy life styles and increase physical activity levels or to the detection of the deterioration of the condition of already diseased patients. The latter could include advanced prediction models from aggregated patient data of certain health events/complications.
Proposals are expected to be built on realistic scenarios for new health and care pathways, and should integrate multi-disciplinary research involving behavioural, sociological, medical and other relevant disciplines. Stakeholder engagement (esp. considering vulnerable user groups, i.e. persons belonging, or perceived to belong, to groups that are in a disadvantaged position or marginalised, for example, elderly people, persons with special needs or chronic diseases) should be part of the research design for an agile approach to ensuring that relevant user needs (including social, age and gender aspects) are met and solutions find acceptance by users. Full account should be taken of ethical and legal aspects e.g. data protection, privacy and data security. This action should create a clear and coherent set of recommendations or guidelines for public health authorities in Europe together with a strategy to support their implementation.
No large-scale piloting or clinical trials are expected in this Research and Innovation Action. However, proposals should include validation (testing on a prototype and/or proof of concept) and demonstration of feasibility of their respective models, technologies and scenarios.
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. Participation of SMEs is encouraged.
Expected Impact:The proposal should provide appropriate indicators to measure its progress and specific impact in the following areas:
Evidence of the benefits of delivering adequate information regarding personalised risk prediction, prevention and intervention, based on proof of concept and involvement and specified roles of relevant stakeholders.Clear improvements of outcomes for individuals, care systems and wider society from prevention measures and interventions based on personalised early risk prediction in comparison with current practices.Usefulness and effectiveness of integration and coordination of interventions in new health and care pathways based on person-centred early risk prediction, prevention and intervention models.Realise large-scale collection of user-generated data in compliance with data protection, privacy and security rules and principles.Support integration with tools and services under the European Open Science Cloud.
Cross-cutting Priorities:Socio-economic science and humanitiesOpen ScienceGender
[1]For example project outcomes from the H2020 topic PHC-21-2015
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Características del consorcio
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La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Características del Proyecto
Los costes de personal subvencionables cubren las horas de trabajo efectivo de las personas directamente dedicadas a la ejecución de la acción. Los propietarios de pequeñas y medianas empresas que no perciban salario y otras personas físicas que no perciban salario podrán imputar los costes de personal sobre la base de una escala de costes unitarios
Los otros costes directos se dividen en los siguientes apartados: Viajes, amortizaciones, equipamiento y otros bienes y servicios. Se financia la amortización de equipos, permitiendo incluir la amortización de equipos adquiridos antes del proyecto si se registra durante su ejecución. En el apartado de otros bienes y servicios se incluyen los diferentes bienes y servicios comprados por los beneficiarios a proveedores externos para poder llevar a cabo sus tareas
La subcontratación en ayudas europeas no debe tratarse del core de actividades de I+D del proyecto. El contratista debe ser seleccionado por el beneficiario de acuerdo con el principio de mejor relación calidad-precio bajo las condiciones de transparencia e igualdad (en ningún caso consistirá en solicitar menos de 3 ofertas). En el caso de entidades públicas, para la subcontratación se deberán de seguir las leyes que rijan en el país al que pertenezca el contratante
Características de la financiación
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon 2020 projects. See the information in the Online Manual.
2. Eligibility and admissibility conditions: described in Annex B and Annex C of the Work Programme.
Proposal page limits and layout: please refer to Part B of the proposal template in the submission system below.
3. Evaluation:
Evaluation criteria, scoring and thresholds are described in Annex H of the Work Programme.
Submission and evaluation processes are described in the Online Manual.
The thresholds for each criterion will be 4 (Excellence), 4 (Impact) and 3 (Implementation). The cumulative threshold will be 12.
4. Indicative time for evaluation and grant agreements:
Information on the outcome of evaluation (single-stage call): maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
Information on the outcome of evaluation (two-stage call):
For stage 1: maximum 3 months from the deadline for submission.
For stage 2: maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
1. Eligible countries: described in Annex A of the Work Programme.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon 2020 projects. See the information in the Online Manual.
2. Eligibility and admissibility conditions: described in Annex B and Annex C of the Work Programme.
Proposal page limits and layout: please refer to Part B of the proposal template in the submission system below.
3. Evaluation:
Evaluation criteria, scoring and thresholds are described in Annex H of the Work Programme.
Submission and evaluation processes are described in the Online Manual.
The thresholds for each criterion will be 4 (Excellence), 4 (Impact) and 3 (Implementation). The cumulative threshold will be 12.
4. Indicative time for evaluation and grant agreements:
Information on the outcome of evaluation (single-stage call): maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
Information on the outcome of evaluation (two-stage call):
For stage 1: maximum 3 months from the deadline for submission.
For stage 2: maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
5. Proposal templates, evaluation forms and model grant agreements (MGA):
Research and Innovation Action:
Specific provisions and funding rates
Standard proposal template
Specific evaluation form
General MGA - Multi-Beneficiary
Annotated Grant Agreement
6. Additional provisions:
Horizon 2020 budget flexibility
Classified information
Technology readiness levels (TRL) – where a topic description refers to TRL, these definitions apply
Members of consortium are required to conclude a consortium agreement, in principle prior to the signature of the grant agreement.
8. Additional documents:
1. Introduction WP 2018-20
2-Health, demographic change and well-being WP 2018-20
3.Dissemination, Exploitation and Evaluation WP 2018-20
4.Cross-cutting activities WP 2018-20
General annexes to the Work Programme 2018-2020
Legal basis: Horizon 2020 Regulation of Establishment
Legal basis: Horizon 2020 Rules for Participation
Legal basis: Horizon 2020 Specific Programme
7. Open access must be granted to all scientific publications resulting from Horizon 2020 actions.
Where relevant, proposals should also provide information on how the participants will manage the research data generated and/or collected during the project, such as details on what types of data the project will generate, whether and how this data will be exploited or made accessible for verification and re-use, and how it will be curated and preserved.
Open access to research data
The Open Research Data Pilot has been extended to cover all Horizon 2020 topics for which the submission is opened on 26 July 2016 or later. Projects funded under this topic will therefore by default provide open access to the research data they generate, except if they decide to opt-out under the conditions described in Annex L of the Work Programme. Projects can opt-out at any stage, that is both before and after the grant signature.
Note that the evaluation phase proposals will not be evaluated more favourably because they plan to open or share their data, and will not be penalised for opting out.
Open research data sharing applies to the data needed to validate the results presented in scientific publications. Additionally, projects can choose to make other data available open access and need to describe their approach in a Data Management Plan.
Projects need to create a Data Management Plan (DMP), except if they opt-out of making their research data open access. A first version of the DMP must be provided as an early deliverable within six months of the project and should be updated during the project as appropriate. The Commission already provides guidance documents, including a template for DMPs. See the Online Manual.
Eligibility of costs: costs related to data management and data sharing are eligible for reimbursement during the project duration.
The legal requirements for projects participating in this pilot are in the article 29.3 of the Model Grant Agreement.
Información adicional de la convocatoria
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