Dipak Kalra

Scaling up the value of health Big Data for learning health ecosystems

Developments over the past decade in electronic health records, molecular medicine, cloud computing, high-scale processing and analytics have created the potential for health Big Data to accelerate the realisation of learning healthcare systems. Such potential spans the tracking of care pathways and health outcomes, optimising healthcare services and equity of access to them, comparative treatment effectiveness and the value of new medicines. Pharma clearly sees the value of Real World (big) Data for clinical trials, biomarker discovery and health outcomes research. Regulators now recognise the need for a more flexible approach to marketing authorisation and patient access to new medicines, such as adaptive pathways, which require real-world evidence.

However, our present-day realisation of large scale learning health (eco)-systems is far slower than the accumulation of theoretically available data. This talk will examine three important barriers to this scaling up: accessing data - concerns about patient privacy, especially in the face of a new European Regulation; learning from the data - the quality and interoperability of the data held in multiple different electronic health record systems and other valuable sources of data such as disease registries; and transforming healthcare – the organisational and professional challenges in re-architecting health systems to be more patient and outcomes focused. In each case the talk will draw attention to the solutions and enablers emerging from European projects that can be harnessed to accelerate the value derived by all stakeholders from health Big Data.