Whilst we have many similarities in our DNA, there are considerable genetic variations that make each one of us unique. With today's technological advances, it is fast becoming a global imperative to ensure that medicines are tailored to our specific physiology and needs. As a medical doctor, I am convinced that precision medicine holds huge potential for patients, offering better targeted treatment, avoiding medical errors, and reducing adverse reactions to medicines. More research is needed for its successful uptake in our health systems, and a key element in making this happen is to maximise the possibilities of big data in health1.
Big data has enormous potential to advance medical research, bring about greater innovation in healthcare, and improve the overall performance of health systems. However, there are a number of barriers to fully capturing and making full use of the considerable health data we have in the EU, notably fragmentation of data sets and insufficient computing infrastructure to connect Europe's eHealth systems.
We are working together at the EU level to remove these obstacles so that we can help get innovative medicines to patients faster and improve our health systems. Tapping into knowledge repositories to make full use of it for the benefit of patients is mainly a question of architecture. We need interoperable eHealth systems to gather, filter, analyse, and use Europe's health data, in full respect of patients' consent.
In this regard, a promising initiative is the European Reference Networks (ERNs) initiative for rare and complex diseases launched in March 2017. As a starting point, 24 ERNs gathering over 900 highly specialised healthcare units from 26 countries have begun to work together on a wide range of diseases. Joining up the EU's best expertise on this scale will bring about faster diagnoses and more effective treatments for thousands of patients. But beyond this, ERNs can create valuable European data sets for research and development. The opportunities for data generation they provide can lead to better patient registries, better clinical guidelines for treatment, and, crucially, more effective, innovative, and personalised treatments.
The potential of the ERN model has been widely recognised, and I want to do my part to ensure that the practical application of these “virtual” networks runs as smoothly as possible so that they can be scaled up and extended to other diseases. We are supporting the Networks, for example, with European cross-border telemedicine tools and via a range of EU funding mechanisms.
In parallel, the Commission is working to ensure the interoperability of eHealth systems. The eHealth Network, since it was formally set up in 2011, has made great strides. Now, Member States are working together to set up the necessary digital architecture to exchange health data, starting with ePrescriptions and Patient Summaries, across borders. So far 16 EU countries are benefitting from EU financing under the Connecting Europe Facility (CEF) for this purpose, and we expect a number of the remaining countries to apply for financing before the end of 2017.
Also before the end of 2017, the Commission intends to table a Communication specifically on digital health and care, following recommendations laid out in the mid-term review of the Digital Single Market Strategy published this May. Amongst other suggestions, this paper will urge EU countries to support the development of a secure data infrastructure to advance research, disease prevention, and personalised health and care.
I have highlighted two areas where the European Commission is focusing efforts to help ensure that big data can be used to provide more efficient and personalised healthcare for patients. I am certain that many interesting ideas will be explored at the EAPM congress “Personalising Your Health.” I look forward to hearing about the outcomes, and to exploring together how we can further ensure that big data can be used for better care of Europe's patients.
Footnotes
1“Big data in health” refers to large, routinely or automatically collected data sets which are electronically captured and stored. It is reusable in the sense of multipurpose data and comprises the fusion and connection of existing databases for the purpose of improving health and health system performance. It does not refer to data collected for a specific study.