1 In the rapidly evolving landscape of global healthcare, health data presents a remarkable opportunity to enhance patient outcomes and systemic efficiency. Despite health data’s exponential growth – fuelled by advances in big data, AI and generative AI and constituting about 30% of the world’s data volume1 – its practical use lags dramatically behind its accumulation. The key opportunity lies in collaboration between the public and private sectors to combine multiple data sources to drive new value. While substantial amounts of health data originate from traditional sources such as hospitals and research institutions, these datasets are often not shared or are restricted and lack a common global standard. Although standards such as Fast Healthcare Interoperability Resources (FHIR) exist, offering a foundation for interoperability, they are not yet fully implemented or optimized across all regions and systems. Additionally, a significant volume of data not explicitly tagged as health-related (e.g. ranging from wearables data to weather data to automotive data) still holds immense potential for improving health outcomes; in the new paradigm of digital health, a broad spectrum of data can serve health purposes, provided it is appropriately integrated and analysed. As the volume of health data continues to rise, the gap between data availability and its practical use in healthcare grows even wider, exacerbating these systemic challenges. This underscores the importance of establishing a robust framework for collaborative data integration and use. Numerous stakeholders have been advocating for this; for example, the National Academy of Medicine’s report2 highlights the steps needed to create a learning health system through effective health data sharing, offering a roadmap for overcoming barriers to integration. The Organisation for Economic Co-operation and Development (OECD)’s report Health in the 21st Century3 emphasizes the critical role of digital health systems in improving care delivery, identifying integration and standardization as key enablers for transformative change. The urgency of the need for immediate action on health data collaboration cannot be overstated, and it is highlighted by the potential benefits for improved health outcomes and significant economic savings. By making use of this vast yet largely untapped resource, the healthcare sector could dramatically enhance care quality, reduce mortality rates and cut healthcare costs. Reduction or elimination of patient harm presents an opportunity for systemic data improvements. More than 50% of the harm4 that occurs in healthcare settings is preventable. Inaccurate diagnoses5 frequently arise due to incomplete patient information, while delays in treatment occur when medical histories are not readily accessible between providers. Medication errors6 stem from inconsistent patient data, and opportunities for preventative care are often missed because of fragmented patient records. Poor care coordination, exacerbated by a lack of data sharing, further compounds the complications and increases the risk of harm. These preventable issues highlight the critical impact that better data management, sharing, analytics and insights can have in addressing the gaps in healthcare practices and improved patient outcomes – gaps that have a real impact on lives and costs. Better data collaboration could help lead the way to preventing approximately 3 million deaths7 worldwide each year, which equates to more than five deaths per minute. 1.1 The potential of health data 1.2 Why health systems should act nowA global need for data-driven health There is an urgent need to collaborate on collecting health data to transform the delivery of care. Better Together: Building a Global Health Network Economy through Data Collaboration 5

Better Together 2025