This article is part of a series in which OECD experts and thought leaders — from around the world and all parts of society — address the COVID-19 crisis, discussing and developing solutions now and for the future. Aiming to foster the fruitful exchange of expertise and perspectives across fields to help us rise to this critical challenge, opinions expressed do not necessarily represent the views of the OECD.
Join the Forum Network for free using your email or social media accounts to share your own stories, ideas and expertise in the comments.
Data are the foundation of knowledge in healthcare. They fuel digital health, forming the basis of research and discovery of novel treatments, empowering the personalisation of medicines and demonstrating the value of treatments to powering artificial intelligence (AI) and machine learning algorithms. And importantly, data enables healthcare providers and policymakers to make informed decisions about allocating resources.
The past five years has seen more scientific data generated than ever before; health data alone make up 30% of the world’s stored data. Many notable efforts are being made in developing diverse and robust health databases to better inform decision-making but, despite much advancement in the field, the evidence suggests that we are not there yet. Widespread barriers still prevent innovators from using data more efficiently and effectively in health. The COVID-19 crisis has exposed these data gaps even further.
Read the latest OECD report on digital health: Empowering the health workforce: Strategies to make the most of the digital revolution
Crucial health data is often still inaccessible to patients themselves, which also means it is unavailable to national decision-makers. As a result of incomplete or low-quality data, policymakers may actually be misled in their attempts to allocate resources effectively. Data are often siloed and locked within institutions, and countries are grappling with being able to link different data sources and use the data for secondary research. For example, an OECD survey found that the vast majority of countries still do not have the ability to extract and harness the information they need to deliver better public health outcomes. Electronic health record data for research, statistics and other secondary uses would inform better delivery of care, and support greater national health research goals.
Data interoperability remains a key challenge. Within a country, data is often not portable from one institution to the next, hindering the ability to combine different sources, leading to less diverse datasets that may not be representative of the entire patient population. In addition, it could create data gaps in the patient pathway. Interoperability and standardised data sets between countries are also fundamental if we wish to build rich, global health databases and seamlessly exchange information between institutions and across borders. COVID-19 has demonstrated this need, and that we are far from having systems that enable the timely transfer of data between countries.
Another challenge we experience is that much of the healthcare data we have are unstructured, making it difficult to compile and analyse in a uniformed way—as a result, it remains largely untapped. The rise and ubiquity of wearables and digital health devices provide the ability to capture and leverage valuable real-world data (RWD) as a supplement to our clinical data. AI and machine learning are becoming more important to analyse the sheer volumes of data that we possess, with key breakthroughs solving complex problems in healthcare previously thought unattainable. We also now have the opportunity to leverage RWD to provide a more complete and holistic understanding of the whole patient, including the impact of social determinants of health.
Underlying all these advances and issues is an increasing need for strong policies that enable us to leverage and use data. Data governance frameworks and privacy laws can help ensure the equitable and appropriate use of data, building trust among all stakeholders. Public trust is fundamental for people to be willing to share their data.
Research shows that the public are more hesitant to share health data than other types of personal data—but the vast majority of citizens would share their health data on the precondition that data is secure and only accessible by authorised parties. Ongoing public dialogues can help to build this relationship of trust, alongside transparency in data use and protective policies. The Data Saves Lives initiative is leading a public dialogue across the EU on this topic.
Trust among industry and regulators is equally as important: in pharmaceutical research and development processes, solutions to these challenges involve greater alignment between them. Through enhanced communication, agreement can be reached on topics such as “approved” methodologies and endpoints, integrity and transparency.
At the top-level, countries need to focus on developing strong digital health and data strategies, building robust data governance frameworks, and investing sufficiently in the national data infrastructure. Globally, we need greater collaboration—including cross-country solutions and sharing of best practices—and to work together to develop common policies that enable data sharing to tackle our most complex healthcare challenges. Yet we must also not lose sight of the importance of engaging with patients and caregivers to seek their perspectives and earn their trust.
Whether you agree, disagree or have another point of view, join the Forum Network for free using your email or social media accounts and tell us what's happening where you are. Your comments are what make the network the unique space it is, connecting citizens, experts and policy makers in open and respectful debate.