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SC1-PM-18-2016
SC1-PM-18-2016: Big Data supporting Public Health policies
Specific Challenge:A defining characteristic of today’s data-rich society is the collection, storage, processing and analysis of immense amounts of data. This characteristic is cross-sectorial and applies also to healthcare. Big Data is generated from an increasing plurality of sources and offers possibilities for new insights, for understanding human systems at the systemic level to develop personalised medicine, prevent diseases and support healthy life. Primary sources are new eHealth personal solutions, but can be extended also to more generic and commercial instruments, like mobile apps for health and well-being. In addition, social networks can be considered for integrating the social dimension in the analysis of health and well-being scenarios. It is important to assure ethical aspects of data, confidentiality, anonymity of data transfer and engagement of those who collect/ code such data in its analysis and interpretation, in order to avoid misinterpretation and inappropriate conclusions. Greater involvement of those who work within healthcare systems, patients and the public is needed.
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Europeo
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Presentación: Consorcio Consorcio: Esta ayuda está diseñada para aplicar a ella en formato consorcio.
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Esta ayuda financia Proyectos: Objetivo del proyecto:

Specific Challenge:A defining characteristic of today’s data-rich society is the collection, storage, processing and analysis of immense amounts of data. This characteristic is cross-sectorial and applies also to healthcare. Big Data is generated from an increasing plurality of sources and offers possibilities for new insights, for understanding human systems at the systemic level to develop personalised medicine, prevent diseases and support healthy life. Primary sources are new eHealth personal solutions, but can be extended also to more generic and commercial instruments, like mobile apps for health and well-being. In addition, social networks can be considered for integrating the social dimension in the analysis of health and well-being scenarios. It is important to assure ethical aspects of data, confidentiality, anonymity of data transfer and engagement of those who collect/ code such data in its analysis and interpretation, in order to avoid misinterpretation and inappropriate conclusions. Greater involvement of those who work within healthcare systems, patients and the public is needed.


Scope:Rather than improving existing isolated systems, proposals sho... ver más

Specific Challenge:A defining characteristic of today’s data-rich society is the collection, storage, processing and analysis of immense amounts of data. This characteristic is cross-sectorial and applies also to healthcare. Big Data is generated from an increasing plurality of sources and offers possibilities for new insights, for understanding human systems at the systemic level to develop personalised medicine, prevent diseases and support healthy life. Primary sources are new eHealth personal solutions, but can be extended also to more generic and commercial instruments, like mobile apps for health and well-being. In addition, social networks can be considered for integrating the social dimension in the analysis of health and well-being scenarios. It is important to assure ethical aspects of data, confidentiality, anonymity of data transfer and engagement of those who collect/ code such data in its analysis and interpretation, in order to avoid misinterpretation and inappropriate conclusions. Greater involvement of those who work within healthcare systems, patients and the public is needed.


Scope:Rather than improving existing isolated systems, proposals should focus on how to better acquire, manage, share, model, process and exploit the huge amount of data to develop integrated solutions that support public health authorities of Member States and associated countries in particular in healthcare system management, long-term policy making and increase the ability to provide actionable insights at the point of care. Relevant solutions include, for example, systems for determining and monitoring the combined effects of environment, lifestyle and genetics on public health, enabling early identification of effects, both on women and men, that can have large impacts on health including lifestyle and provision of healthcare – both short term and long term as well as when interaction with other public sectors is required (e.g. physical planning). Focus should also be on the governance of Big Data in order to use it proficiently across organisations and at policy levels. Integrated solutions should include suitable approaches towards securing security and privacy issues.

The Commission considers that proposals requesting a contribution from the EU of between EUR 3 and 5 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: Mapping comprehensive big data in a reachable and manageable way by applying principles for sharing and reusability, creating a network of knowledge by linking heterogeneous data sources for public health strategy; Emerging data driven analytics and advanced simulation methods to study causal mechanisms and improve forecasts of spatial and temporal development of ill-health and disease; Develop innovative approaches to improve current risk stratification methodologies; Turning large amounts of data into actionable information to authorities for planning public health activities and implementation of an approach "health in all policies"; Placing prevention strategies on evidence base, evaluation of the efficiency and effectiveness of implemented strategies, feedback of results into the development of methods; Analysing the efficiency of patient pathway management both at primary care level (prevention and early detection) and en route encompassing; Aligning big data and advanced simulation methods in order to provide high-leverage policy analysis for public health officials, across a range of epidemiology challenges; Cross-border and networking coordination and technology integration facilitates interoperability among the components of Big Data value chain.
Cross-cutting Priorities:Gender


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Temáticas Obligatorias del proyecto: Temática principal: Health services health care research Bioinformatics e-Health medical informatics Public health policies

Características del consorcio

Ámbito Europeo : La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Tipo y tamaño de organizaciones: El diseño de consorcio necesario para la tramitación de esta ayuda necesita de:

Características del Proyecto

Requisitos de diseño: Duración:
Requisitos técnicos: Specific Challenge:A defining characteristic of today’s data-rich society is the collection, storage, processing and analysis of immense amounts of data. This characteristic is cross-sectorial and applies also to healthcare. Big Data is generated from an increasing plurality of sources and offers possibilities for new insights, for understanding human systems at the systemic level to develop personalised medicine, prevent diseases and support healthy life. Primary sources are new eHealth personal solutions, but can be extended also to more generic and commercial instruments, like mobile apps for health and well-being. In addition, social networks can be considered for integrating the social dimension in the analysis of health and well-being scenarios. It is important to assure ethical aspects of data, confidentiality, anonymity of data transfer and engagement of those who collect/ code such data in its analysis and interpretation, in order to avoid misinterpretation and inappropriate conclusions. Greater involvement of those who work within healthcare systems, patients and the public is needed. Specific Challenge:A defining characteristic of today’s data-rich society is the collection, storage, processing and analysis of immense amounts of data. This characteristic is cross-sectorial and applies also to healthcare. Big Data is generated from an increasing plurality of sources and offers possibilities for new insights, for understanding human systems at the systemic level to develop personalised medicine, prevent diseases and support healthy life. Primary sources are new eHealth personal solutions, but can be extended also to more generic and commercial instruments, like mobile apps for health and well-being. In addition, social networks can be considered for integrating the social dimension in the analysis of health and well-being scenarios. It is important to assure ethical aspects of data, confidentiality, anonymity of data transfer and engagement of those who collect/ code such data in its analysis and interpretation, in order to avoid misinterpretation and inappropriate conclusions. Greater involvement of those who work within healthcare systems, patients and the public is needed.
¿Quieres ejemplos? Puedes consultar aquí los últimos proyectos conocidos financiados por esta línea, sus tecnologías, sus presupuestos y sus compañías.
Capítulos financiables: Los capítulos de gastos financiables para esta línea son:
Personnel costs.
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
Purchase costs.
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
Subcontracting costs.
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
Amortizaciones.
Activos.
Otros Gastos.
Madurez tecnológica: La tramitación de esta ayuda requiere de un nivel tecnológico mínimo en el proyecto de TRL 5:. Los elementos básicos de la innovación son integrados de manera que la configuración final es similar a su aplicación final, es decir que está listo para ser usado en la simulación de un entorno real. Se mejoran los modelos tanto técnicos como económicos del diseño inicial, se ha identificado adicionalmente aspectos de seguridad, limitaciones ambiéntales y/o regulatorios entre otros. + info.
TRL esperado:

Características de la financiación

Intensidad de la ayuda: Sólo fondo perdido + info
Fondo perdido:
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Please read carefully all provisions below before the preparation of your application.
 
List of countries and applicable rules for funding: described in part A of the General Annexes of the General Work Programme.
Note also that 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 (follow the links to China, Japan, Republic of Korea, Mexico, Russia, Taiwan, USA).
 
Eligibility and admissibility conditions: described in part B and C of the General Annexes of the General Work Programme.
Proposal page limits and layout: Please refer to Part B of the standard proposal template.
 
Evaluation
3.1  Evaluation criteria and procedure, scoring and threshold: described in part H of the General Annexes of the General Work Programme, with the following expections:
The thresholds for each criterion in a single stage process will be 4, 4 and 3. The cumulative threshold will be 12.
3.2 Submission and evaluation process: Guide to the submission and evaluation process
      
Indicative timetable for evaluation and grant agreement:
Information on the outcome of single-stage evaluation: maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the de...
Please read carefully all provisions below before the preparation of your application.
 
List of countries and applicable rules for funding: described in part A of the General Annexes of the General Work Programme.
Note also that 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 (follow the links to China, Japan, Republic of Korea, Mexico, Russia, Taiwan, USA).
 
Eligibility and admissibility conditions: described in part B and C of the General Annexes of the General Work Programme.
Proposal page limits and layout: Please refer to Part B of the standard proposal template.
 
Evaluation
3.1  Evaluation criteria and procedure, scoring and threshold: described in part H of the General Annexes of the General Work Programme, with the following expections:
The thresholds for each criterion in a single stage process will be 4, 4 and 3. The cumulative threshold will be 12.
3.2 Submission and evaluation process: Guide to the submission and evaluation process
      
Indicative timetable for evaluation and grant agreement:
Information on the outcome of single-stage evaluation: maximum 5 months from the deadline for submission.
Signature of grant agreements: maximum 8 months from the deadline for submission.
 
Provisions, proposal templates and evaluation forms for the type(s) of action(s) under this topic:
Research and Innovation Action:
Specific provisions and funding rates
Standard proposal template
Specific evaluation form (Document not available yet)
H2020 General MGA -Multi-Beneficiary
Annotated Grant Agreement
 
Additional provisions:
Horizon 2020 budget flexibility
Classified information
 
Open access must be granted to all scientific publications resulting from Horizon 2020 actions, and proposals must refer to measures envisaged. 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.
 
Additional documents:
H2020 Work Programme 2016-17: Introduction
H2020 Work Programme 2016-17: Health, demographic change and wellbeing
H2020 Work Programme 2016-17: Dissemination, Exploitation and Evaluation
H2020 Work Programme 2016-17: General Annexes
Legal basis: Horizon 2020 - Regulation of Establishment
Legal basis: Horizon 2020 Rules for Participation
Legal basis: Horizon 2020 Specific Programme
 
Garantías:
No exige Garantías
No existen condiciones financieras para el beneficiario.

Información adicional de la convocatoria

Efecto incentivador: Esta ayuda tiene efecto incentivador, por lo que el proyecto no puede haberse iniciado antes de la presentación de la solicitud de ayuda. + info.
Respuesta Organismo: Se calcula que aproximadamente, la respuesta del organismo una vez tramitada la ayuda es de:
Meses de respuesta:
Muy Competitiva:
No Competitiva Competitiva Muy Competitiva
No conocemos el presupuesto total de la línea
Minimis: Esta línea de financiación NO considera una “ayuda de minimis”. Puedes consultar la normativa aquí.

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