We’re continually being told data science will herald a new revolution in healthcare. But what’s the potential for mental health? And how could it help research?
Here are our thoughts:
1. Exploring mental health across the lifespan
By studying large groups of young people, from school through to adulthood, we can better understand how the mind changes during adolescence, and how different life events impact on this.
And we can explore how relationships throughout life affect our mental health by also incorporating data from our digital profiles, such as Facebook, twitter and GPS data.
2. Understanding the causes of mental illness
Vast datasets have already started to show many of the genes that are associated with mental illness. And more genetic data would help us understand more of the mechanisms behind mental illness.
That helps with understanding some of the ‘nature’ aspects – our biology. But what about ‘nurture’ – our environments?
Well we could use data about where we grow up, and our upbringing, to understand how our childhood environment impacts our mental health too. And combining the two could be even more illuminating.
3. Making mental illness preventable
Once we know more about all of the factors affecting mental illness, we hope to be able to better predict who may need help for their mental health. This will allow us to get help to them as early as possible, or even one day prevent them becoming ill in the first place. Essentially, it will help us answer who are the groups most at risk of developing a mental health condition?
In response to this, we can find ways to help protect those that are vulnerable, and find better interventions.
One of MQ’s researchers, Dr Helen Fisher, is already exploring this area via her research into trauma and psychosis during childhood. She’s looking at large sets of data to understand why some children who have psychotic episodes will go on to develop a mental illness, whilst others will live free from a mental health condition.
4. Improving detection, screening and diagnosis
If we can identify early warning signs using health data, we could speed up diagnosis. We could even make diagnoses more accurate by analysing symptom data, just as MQ-funded researcher Dr Martijn van den Heuvel is currently doing.
Ultimately, these improvements in the path to diagnosis will help us to get people the right help faster.
5. Developing new treatments and improve existing ones
What if we could bypass ‘trial and error’ treatments and instead predict the most effective intervention for each patient?
We're currently supporting Dr Rob DuRubeis in addressing this question using data and statistics. And what if we could use NHS data to understand how effective current treatments are for current patients?
6. Living well with a mental health condition
We already use Fitbits, SmartWatches and exercise apps to monitor our lifestyle. What if we could link this information to symptom trackers?
That way we could link our mental, physical and social wellbeing to create person-centred healthcare.
7. Driving improvements in health and social care
We all know that our healthcare systems need more support in order to improve patient access and save money.
What if we could predict demand on healthcare services using demographic data? Maybe we could reduce waiting times, track progress and make the system more cost-effective.
The power of mental health data science
The seven topics explored above provide a flavour of the potential of mental health data science.
What’s clear is that there are many types of data available to researchers, and many of these data types can be linked in order to make a powerful wealth of knowledge.
At MQ we’re driving forward efforts in mental health data-science, including with our Data Science award programme, funding world-leading data scientists across the globe.
And we’ve also been exploring the opportunities and barriers to the field with the MQ Data Science Group. These individuals are focused on championing the field, and highlighting the potential for mental health data science too. You can find out more in this paper in the Lancet Psychiatry, written by the MQ Data Science Group.
Find out more about the MQ data science programme.
Last updated: 4 September 2017