Experts from the BD4BO programme have some recommendations on how to make the European Health Data Space really work for patients, doctors and researchers
In 2016, IMI launched the Big Data for Better Outcomes (BD4BO) programme to explore new, improved and ethical ways for researchers to unleash the collective power of healthcare datasets, with the ultimate aim of improving real-life outcomes for patients.
In response to the European Commissions’ announcement of their intention to put in place a European Health Data Space (EHDS), experts from BD4BO have offered up some recommendations based on their extensive experience working out the right tools and rules for harnessing and exploiting big data via a multi-themed portfolio of research projects.
Below is a summary of the recommendations. The full document can be found here.
Showing results can build trust
If you want to build trust, the authors say, you have to show that data sharing initiatives can lead to outcomes that regular citizens actually care about, like new therapies for their disease. It should be shown how data generated in the real-world as part of patient care and treatment is feeding scientific research and leading to actual improvements. This kind of transparency helps get people on board.
IMI BD4BO projects are great examples of this. They are asking research questions that researchers, clinicians, commercial and academic researchers want answered, and that have attracted many patients with a vested interest in the outcome, too. Patients are part of the governance of each of the projects and they are deeply involved in drawing up things like patient preference outcomes, which they know best about.
Use what already exists
There is no need for the EHDS to start from scratch. Data sharing infrastructure is already being built and used across Europe through multiple programmes. The new EHDS will be able to make use of these infrastructures, as well as the pan-European and international multi-stakeholder communities and networks made up of patients, clinicians, researchers and health care providers with data scientists, bioinformatics and statisticians that already exist. By continuing to fund these existing initiatives, unnecessary duplication and re-invention can be avoided.
Getting everyone on board will require big investments
Big investments need to be made in developing, and pushing the uptake of, common data models, to tackle the problem of the wildly different health digitalisation practices of different EU countries. Homogenising standards is necessary to make use of existing data for both regular patient care and researchers, and incentives should be used to convince EU countries to get on board.
Ensure interoperable and flexible architecture
There needs to be common, interoperable architectures to facilitate secure data flows for clinical and research use across Europe; a one-size-fits-all infrastructure will limit progress. The EHDS governance structure needs to be flexible enough to cope with and support different national and regional models.
Meaningful codes of conduct will strengthen citizens’ rights
High-level governance models must flow to everyday clinical and research practice. Codes of conduct could be helpful to explain and interpret the EU’s data privacy regulation (the GDPR) to certain sectors, and should be developed by the communities that are responsible for putting them into practice. They need to be meaningful for their use in daily practice and aligned to other relevant regulations where applicable, such as the clinical trial regulation and the ethics approval process.
The BD4BO programme was built around different IMI projects, each centred on a particular disease: Roadmap (Alzheimer’s disease), HARMONY and HARMONY PLUS (haemato-oncology), BigData@Heart (cardiac disease) and PIONEER (prostate cancer). It also incorporates EHDEN, whose objective is to build a European data and health evidence network. It is based on the premise that big data has the potential to have a transformative effect across a board spectrum of areas including healthcare systems, patient stratification and disease treatment, clinical guidelines, trial and product design and patient use of medical technologies. However, the potential of big data will only be unlocked when healthcare systems move beyond the basic collection of large amounts of data.