The European Health Data Space (EHDS) regulation proposes a framework that would allow for the secure and efficient use of health data for research, innovation, policy-making, and regulatory activities. This type of framework for the ‘secondary use’ of health data has the potential to deliver new and meaningful insights that inform research and innovation, ultimately delivering benefits for people, healthcare providers (HCPs), and healthcare systems.
The healthcare industry is transforming the traditional care delivery model and adopting a more agile, hybrid approach that incorporates remote monitoring and management through digital health technologies (DHTs). Data-driven software can be used to identify care needs, triage patients, automate basic tasks, and streamline follow-up care. Advanced software analytics can identify minor issues before they become major problems requiring urgent attention.
As the adoption of DHTs becomes broader, the positive impact on healthcare innovation grows due to the increasing amount of health data being generated. This data can be securely collected into real-world data (RWD) sets that enable researchers to develop and evaluate healthcare innovations at a faster pace than using traditional research and evaluation methods alone.
RWD alone is of limited value. However, using good statistical methods, RWD can be turned into real-world evidence (RWE). RWE provides important insights for healthcare decisions for all stakeholders: patients, HCPs, and manufacturers of medical technologies. For example, a recent study using RWE from France showed that patients with obstructive sleep apnea (OSA) who continued to use positive airway pressure (PAP) therapy had a remarkably 39% higher chance of survival than those who stopped therapy. In fact, a broad range of studies showcases how much potential there is for novel treatments and life-saving insights when using RWD.
This is especially true when combining such data with data from other sources such as electronic health records (EHRs), administrative payment/claims, pollution and other environmental factors from trusted public agencies, weather forecasts, socio-economic, and other patient-generated data. These types of data sets can be securely combined with health data to alert patients of circumstances that may negatively affect their well-being. Should the EHDS’ secondary use framework meet its aims, in the future, pairing data from DHTs with other data sources will fully unlock prediction, prevention and personalisation.
To achieve the benefits of deployment of RWD & RWE, it is important to create the right enabling environment through the EHDS regulation. The final EHDS regulation needs to include a strong framework for the secondary use of health data that protects patient privacy and data security, while also enabling researchers and innovators to access the data they need to develop new and innovative healthcare solutions. The EHDS will only reach its potential, however, if it includes fully representative datasets coming from a wide variety of data sources and an accurate representation of the population. Non-representative data sets can undermine the purpose of EHDS, preventing the EU from creating an attractive research environment, particularly in Artificial Intelligence (AI) development, indirectly harming EU competitiveness.