How might big data transform medicine?

Big data is starting to affect every area of our lives and of commerce, but it is also expected to transform how we do medicine.  The first inklings of computers changing medical care have been apparent for some time as GPs increasingly refer to online databases, patients look up their own symptoms before presenting themselves to a doctor and pharma companies use powerful computers to help find new drugs.  But the sheer scale of big data may make that look like child’s play and the growth of medical data is now exponential.  To give one illustration, it used to take two years to sequence one individual’s genome whereas now it can be done in a day; five years ago the commercial cost was $48,000 and now it’s $1,000 …. and dropping.

The definition of big data is use of data sets which are so large and complex that they cannot easily be processed using traditional data applications.  This typically means data with characteristics of the three “V”s – high volume, high velocity and lots of variety.  Some people add a 4th “V” for veracity which is clearly a central question about any data, particularly of a medical sort.

It is said that more medical data was collected worldwide over the last two years than in the whole of previous human history.  Within the medical world collecting and analysing data to improve human health is now a hot topic, illustrated by the Biomedicine conference at Stanford in May 2015, which intends to “identify actionable steps for using large scale computing and data analysis”.

But there are very different challenges which Big Data might be able to address in medicine:

– sequencing the human genome so that patterns of illness and prevention can be established;

– creating a medical history of everyone allowing “predictive medicine” and more effective treatment;

– epidemiological studies will be able to use much larger samples, potentially whole populations;

– accelerating the development of new drugs and antibiotics;

– creating a more efficient system for transplants and organ donors;

– optimising use of drugs and treatments, particularly in areas where causation is poorly understood such as in mental health.

With health budgets squeezed worldwide as a result of ageing populations and the increasing costs of medical treatments, the question stands out as to who will fund the use of big data in medicine.  Certainly the big pharma companies are embracing it: GSK says on its website, “analysis of so-called ‘big data’ is the first of many small steps towards making medicines more targeted to a person’s genetic make-up and the way their bodies tackle disease.”  But patient care groups are already using big data to improve the productivity of doctors – in the US Kaiser is the leader in holding medical health records, with about 30 petabytes of storage and this is doubling every two years.  For example, Kaiser searches the medical charts for the 1,500 individuals it sees each day and produces a report on follow up care such as immunisations and blood tests.  They claim that doctors can see three or four times as many patients each day as a result and that big data can reduce complications, falls, and readmissions.  But more dramatically some have questioned whether big data will change the role of doctors so that their data analytics skills become paramount.