SC1-PM-18-2016 - Big Data supporting Public Health policies
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.
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.
- 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.