Big data - using the force for good

By Corin Kelly
Thursday, 12 November, 2015

“What if we, as government, got out of the way and gave consumers full access to their own personalised health data and full control over how they choose to use it?” Health Minister Sussan Ley asked in her recent speech to the National Press Club.
“The great digital health revolution,” the minister concluded, “lies literally in the palms of consumers, rather than government.”
On one level this rings true. There have never been more ways to monitor our personal health and well-being, and share and compare our findings. We can track our activity, diet, exercise, emotions and sleeping habits on our mobiles, Fitbits, Apple watches and apps. We can even have our genomes sequenced.
And with Ley’s announcement we may now start to see a real upswing in people accessing and using their own medical record data. But the availability of data is just the starting point – we then need to make sense of the data.

Opportunities

Conventionally, insights from health data have come from research studies that test hypotheses by systematically collecting and analysing data. Findings are published in scientific journals and pooled to determine the 'bottom line' on any given health topic. This information is then used to create the guidelines and policies that shape health-care practices.
For instance, when pharmaceutical companies develop a new drug, they conduct a set of research studies and estimate the benefits and harms of the drug by combining data from these studies.
But the side effects of drugs are not always apparent at the time of marketing approval. This is because initial studies are often relatively small, with short follow-up times, selected study populations and a modest set of outcomes.
Systems that monitor drug effects in large and diverse populations over time can therefore add a lot to our understanding of a drug’s real effects. An even clearer understanding of a drug’s effect might come from incorporating genetic data.
We can also capture additional data from social platforms where people contribute their own experiences with illnesses and treatments.
Challenges
The greatest value is often generated when different types of data are combined, such as genomic and medical record data. But current systems are not up to the task of combining and making sense of our increasingly rich and diverse data – from genomes to Facebook profiles.
In order for consumers and health professionals to make the most of big health data we need to build systems to efficiently and reliably convert diverse data into knowledge.
Scientists need to work out:

why, when and how to combine different types of data

how each data source’s strengths and weaknesses can be taken into account

the technical systems able to capture the required metadata (data about data)

Bringing big and diverse data together will require new methods and collaborations between computer scientists, health researchers, experts in evidence synthesis and others.
Big data is the new oil of the 21st century. What we are missing are the engines, factories and transport systems. Their digital equivalents are being built now and how we – individuals, corporations, governments and societies – build these systems, products and services will have far-reaching consequences in health.
This article was originally published on The Conversation. Read the original article.