It has now become an orthodoxy that we are moving into the age of 'Big Data'. This derives from ever increasing processing power and the vast surge in connectedness - with mobile technologies at the forefront and sensors in nearly all appliances, we are set to have 50 billion devices by 2020 connected in the cloud. It is argued that medical decisions can be truly evidence based, combining the most complete medical science with personal data, drawing where appropriate on 24/7 monitoring through mobile devices and patient reported outcome measures. Lifestyle advice and preventive action can be honed with ever greater accuracy. Benefits from treatment, its best timing, lowest cost, better understood risk, and more predictable side-effects should all flow from this data transition, bringing lower costs and higher value.

Corporations are competing in both investment and rhetoric. In 2013 Google launched a new subsidiary, Calico, which Larry Page claimed would represent 'moonshot thinking around health care', and there have been many similar claims. But how is all this justified? And how can we ensure that those advances which do arise from this new control of data truly benefit patients, rather than just the provider - and that this will be a benefit distributed across the social gradient and globally?

What are the risks on the horizon? Data is often siloed and used for competitive advantage. Protocols around privacy could be tested to destruction; for instance, it is possible to reverse engineer anonymized data to identify individuals. Forbes magazine even reports a case of medical data being sold on EBay. How might these risks be best mitigated?

This session reviewed the claims for Big Data and its true potential, and sought to identify the conditions under which it should yield the greatest benefits to patients and populations.