The importance of informed decision-making based on real clinical data (Real-World Data – RWD and Real-World Evidence – RWE) has been at the heart of the debate regarding the nexus of digitalization, health and data protection in recent years. RWD come from many real-life sources, such as medical and patient records, biobanks, health surveys, observational studies, health insurance data etc. Consequently, they involve vast amounts of data which are automatically collected, electronically stored, and can then be reused for different purposes. Operationally, they usually come from interoperability and linking of existing databases, aiming at improving the health of the population and the overall efficiency of the health system. RWD are not the only source of digital health information, however; an equally important source is Real-World Evidence (RWE), which is data derived from research on and processing of RWD, and that constitute the actual research evidence about the use and potential benefits or risks of a pharmaceutical product.
The overall process of collecting and utilizing RWD to produce RWE is not straightforward. It inadvertently creates a composite and lengthy value chain, which begins with the patients as the source of primary information and the various organisations that interact with patients. This presupposes patient and caregiver consent along with the development of an appropriate data collection system (sensors, data entry, laboratory measurements, digitization of records, etc.). The stored data then need to be organised, transmitted, and consolidated in order to proceed with the analysis and synthesis of new information and the production of RWD and RWE. Only then it is possible for all stakeholders to utilise them to uncover new information and inform policy decision making, which in turn affects primary patient care and pharmaceutical usage, creating valuable feedback loops on the overall process.
Recognizing these possibilities and the potential ensuing benefits that accompany the utilization of RWD is at the forefront of digital health agenda in various countries. In response, many European countries have created large RWD databases, based on a combined data analysis from patient records, diagnostic and treatment protocols, clinical trials, and electronic patient records. While these health data can be made available in a variety of formats, they are not managed in the same way in all EU member states or within national health systems. Patients, public authorities, healthcare professionals or researchers themselves often do not have access to this data so that they can formulate and provide better diagnosis, treatment, or personalized care. Even when health data is available, they often depend on non-interoperable information systems, preventing their widespread use. Another critical set of challenges relates with confidentiality and privacy issues regarding data-sharing among the various stakeholders of the healthcare ecosystem and, of course, the encompassing issue of patient personal data protection. The roots of these problems can be traced to the lack of relevant regulatory frameworks that provide proper guidelines regarding data collection, validation, standardization, protection, sharing and utilization. These types of regulatory frameworks are still absent or at an infant stage in most national and international digital health strategies.
In order to successfully address some of the above challenges, various countries have developed initiatives related to the storage of RWD through the operation of research centers – repositories or other databases, which operate either independently or as a result of research collaboration and/or partnership of the private and the public sector. Some notable examples are the Department of Epidemiology and Biostatistics of the Karolinska Institute in Sweden, Maccabitech in Israel, and the SNIIRAM database in France. At the international level, the European Medicines Agency (EMA) is establishing a coordination center to provide timely and reliable data on the use, safety, and effectiveness of pharmaceuticals and treatment protocols for human use from real-world healthcare databases across the European Union (EU). This new direction is called the Data Analysis and Real World Interrogation Network (DARWIN-EU, expected to be operational in 2024), with its main purpose being be to provide RWE from across Europe on diseases, populations, uses and performance of pharmaceutical products.
Apart from their obvious uses in medicinal and pharmaceutical studies and trials, RWD/RWE is supported by innovative methods and tools that can transform “big health data” into “smart health data”, as they can have a significant contribution to understanding complex issues related to human health and to the advancement of health sciences. Their most important and unprecedented contribution to medical science is related to their size and scope, as they have the potential to uncover an extensive range of utilization opportunities that were previously impossible due to inherent limitations in smaller datasets, further providing new insights into disease patterns and improve the overall safety and efficacy of medical interventions.
While the potential benefits of integrating the analysis and utilization of RWD and RWE into the digital health ecosystems are multidimensional, often significant gaps exist between high-level strategic planning and their actual utilization. A missing key step is to design a regulatory framework that will ensure the opportunities and prospects for the collection and use of RWD and, at the same time, ensure quality and reliability in both the data collection process and their utilization for RWE production, and the protection of patients’ personal data. This framework will be the basis for the development activities around RWD processing and utilization by creating the appropriate collaborative framework that will mobilize ecosystem to invest in and ensure the best possible utilization of RWD in the future.