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Funding mental health innovation: what can the data tell us?

This blog analyses mental health research projects funded through Horizon2020, the European Commission’s largest innovation fund.

Mental health has a funding problem. Though mental health problems represent 28 per cent of the disease burden in the United Kingdom, this area accounts for only 13 per cent of NHS spending. Only one third of people suffering from mental illness receive formal treatment, with a lack of available services playing an important role in creating this care gap. In addition to the  human suffering that lies beneath these numbers, the costs associated with this growing mental health crisis are substantial: the Centre for Mental Health calculates that the UK economy loses over £100 billion each year due to mental health-related sickness and unemployment.

In recent years, mental health funding has also been subject to far-reaching government cuts. In response, remaining resources have often largely been directed to emergency care, with prevention and long-term care receiving much less attention. Local authorities in England are planning to make a further £824m of savings in their social care budgets (out of which much preventative services are resourced) this year, bringing the total cuts since 2010 up to £6bn. The hollowing out of these preventative and support services has had consequences: mental health-related calls to London emergency services went up by a third between 2012 and 2017, a challenge support systems are ill-equipped to deal with.

Despite this growing crisis and increased attention from government, mental health funding is still not prioritised. The issue continues to attract a great deal of social stigma, the general public is either unaware of or holds unjustly negative stereotypes about mental health. Though attitudes towards mental health among the British public have been improving in recent years, 40 per cent still believe people with mental health problems are more prone to violence (even though the opposite is the case - those suffering from mental health problems are more likely to be the victim than the perpetrator). This social stigma has often meant that mental illness is a politically charged issue.

As the financial and resource pressures on the mental health system are unlikely to abate in coming years, we need to learn how to do more with less and identify innovations that can help fill existing gaps or even provide us with new capabilities (particularly around prevention and long-term care). Unfortunately, developing new approaches in mental health is notoriously difficult. Unlike some physical health problems, mental health issues tend to manifest themselves and develop in very different ways from individual to individual, meaning that developing standardised treatments and generating clinically-tested evidence is complex.

Treatment approaches in mental health support also tend to be very siloed: clinical professionals use very different methods and tools to caseworkers, who in turn might engage very little with, for example, biomedical researchers in the field, making it hard to develop interdisciplinary innovations across the whole system. This slows down the adoption of new innovations and implementation of the kinds of integrated solutions that might help relieve some of the resource constraints those working in the field currently face.

Though we know we face similar challenges in funding mental health research - UK funding for mental health research was 22 times lower than cancer - there has been relatively little analysis done on how these dynamics play out in decisions around which types of mental health research projects are being funded. If resources for prevention in mental health problems are limited, is this reflected in the type of research which receives funding ? And do we see a similarly fragmented landscape with siloed research communities, insufficiently focused on prevention and long-term care?

Though this blog won’t attempt to answer all of these questions, we explore whether analysing actual funding data can provide us more insight into these underlying dynamics. To do so, we specifically look at one of the most ambitious research and innovation funds in the world: the European Commission’s Horizon 2020 programme, which is budgeted to spend €80 billion (£71 billion) on funding innovations that could help solve key societal challenges by 2020 (health and wellbeing is a key pillar).

Horizon 2020

There are other large mental health-funding programmes, both on the UK and EU level, but Horizon 2020 is the largest and has specific characteristics that make it of particular relevance. The broad range of countries and stakeholders that can receive funding allow us to study trends across geographical and research domains (researchers and practitioners from all EU and affiliated countries are eligible to apply), which is rare for this kind of funding programme. The H2020 database is also particularly suitable for exploring mental health-related projects specifically: several mental health-related topics, such as the mental wellbeing of young people, have been highlighted as key challenges within the health domain. The comprehensiveness and level of detail provided in the database of H2020 project published by the European Commission also makes this a particularly high quality dataset to analyse.

Studying Horizon 2020 also provides insight into the UK’s mental health research landscape: UK universities, institutions and companies are one of the main recipients of Horizon 2020 funding. Our analysis found that of the slightly over 11,000 projects so far financed through Horizon 2020 (worth a total of €25 billion), nearly 20 per cent have a British organisation as their lead coordinator. If we specifically look at mental-health related projects, that share is even higher: 23 per cent of identified projects include a British lead. The top three is completed by the Netherlands (13 per cent, versus 6.5 per cent overall) and France (11 per cent, versus 10 per cent overall).

Main findings

Within the total set of 11,069 projects, we found exactly 600 projects that either focused on mental health, or the brain and neurology more broadly. These 600 projects received a total of €1,15 billion (£1,03 billion) in funding, or 5.7 per cent of the total- which is not insubstantial.

But when we instead look at just the neurological and psychiatry related projects concerned with mental health problems (mentioning a specific pathology, for example), the number of funded initiatives is reduced significantly: only 118, or about 1 per cent of total funded projects, with most of the other 472 focused on non-mental health related brain issues like traumatic brain injury or Alzheimer’s disease or more research on the inner workings of the brain itself.

However, over the past couple of years, we have seen a growth in the number of mental health projects being funded through Horizon 2020. As the overall number of projects funded through H2020 has picked up (in the first year of the fund, only 367 projects were funded, while 4892 were in 2016) so has the number of mental health projects. As a share of the total we’ve also seen an increase: brain projects have so far made up 7.4 per cent of projects funded in 2017 (6.0 per cent in 2016), up from 4.7 per cent in 2015. The subset of mental health-specific projects have so far made up 1.6 per cent of this year’s total.

A limited focus on social innovation

Horizon 2020 does not just fund science and technology-focused research, but also finances projects exploring innovative methods in the social sciences for example. Indeed, numerous social innovation projects in many different fields have been funded through H2020. It is therefore interesting to note that we identified very few social innovation projects related to mental health when compared to the number of research projects looking at medical (neurological, pharmaceutical or psychiatric) interventions given grants. We found only 11 projects that could be considered purely focused on “social mental health” solutions (which we define for this exercise as community-based or interpersonal interventions looking to address economic and social factors linked to mental health problems, such as poverty and social isolation).

Much-hyped technologies such as brain imaging and human-brain interfaces receive more resource than interventions focused on human interactions in the field. Though investment in biomedical solutions is important, particularly in the space of fine-tuning diagnosis and the development of new treatments, social innovations can and do also play a very important role in treating mental health problems, particularly in prevention, through addressing some of the economic and societal factors associated with mental health issues (see the guest blog by the Centre of Mental Health’s Andy Bell on this topic).

The lack of funding of social health innovations for mental health is significant, but could new developments in mental health tech help to bridge the gap?

What’s on the horizon?

In other blogs in this series we have discussed the building momentum around mental health tech-innovations like digital tracking apps, predictive analytics for diagnosis, and VR treatment, which have attracted particular interest and investment in recent years. This new funding wave is not just restricted to the venture capital space: we also see an increase in the numbers of projects looking at these kinds of technologies in the Horizon 2020 data.

To gain a better understanding of the trends in funding within H2020, we classified each of the brain-related projects in the database and identified the key technologies they were concerned with (as many general brain solutions could have direct applications in mental health treatment, we gain more insight by widening our scope to all brain-related projects in this case).

N.B. Distinguishing and categorising new, experimental technologies is sometimes made difficult due to a lack of consistent nomenclature.

From our analysis the technologies receiving most H2020 funding are:

  • Brain imaging: a ground-breaking technology that has greatly enriched our knowledge of the brain. One important emerging application of brain imaging for mental health is the use within precision psychiatry (discussed here by my colleague Jack Pilkington), where it is used to generate biomarkers that could predict which treatment options an individual might respond best to. 68 projects that explicitly mentioned brain imaging have been funded since the beginning of the H2020 programme.

  • Brain-computer interfaces and wearables: devices that can interact directly with the brain and potentially even take over some of its functions (in cases of severe brain damage, for example) have been long anticipated, but are still quite far from actual deployment. Recent years have seen an uptick in interest in this space, particularly for its potential to “augment the brain” (see: Elon Musk’s Neuralink and other similar Silicon Valley-initiatives). 19 projects in this space were funded. 

  • mHealth and eHealth solutions: digital tools - particularly smartphones - have been hailed for their promise in managing and monitoring mental health problems. Currently less than one per cent of mental health apps have any actual clinical evidence underpinning them, but the untapped potential creates an imperative for further research through formalised funding streams such as H2020. We identified 20 mental health projects linked to mHealth and eHealth solutions.

  • Robotics: many of the mental health-focused robotics projects funded through H2020 look at the potential of care robots: can robots function as an ‘always-on’ companion, there to support us when we are in need but no caretakers are around? We identified 28 projects looking at the use of robotics in mental health.

Most of the topics above represent important technology areas that have become well established over the past years or decades, and not surprisingly therefore already have a bigger portfolio of projects exploring them. When funding existing and emerging technology areas, we need to be careful to strike the right balance - a technology with a better evidence base and already more funding behind it, is more likely to receive even more funding, perceived as the safer bet (a self-fulfilling prophecy of sorts). Investing in early-stage technologies is more risky: we don’t yet know if they will take off. Ideally, a research fund would explore a mix of both established and more experimental technology areas.

Many of this new generation of mental health technologies focus on expanding the use of technology and clinical methods beyond the confines of the hospital and the therapist’s office. mHealth apps and other similar digital solutions, for example, allow therapists to connect with patients on a more responsive basis to track progress outside of formal weekly sessions, or allow people with mental health problems to reach out to peers in their community. So rather than replacing social interactions, these technologies can actually help facilitate them (see the guest blog by mHabitat’s Victoria Betton on this topic). Beyond the potential of technological solutions to expand the therapeutic toolbox, mental health tech could thus also play a role in bridging the divide between the parallel (but often distinct) strands of social and medical health.

Investing in cost-effective, multidisciplinary approaches to improve diagnosis, treatment and support for those facing mental health difficulties will be essential as we seek to tackle the mounting mental health crisis. Understanding more about the next generation of mental health technologies (which can sit at this nexus point between ‘social’ and ‘medical’ models) and how these could support the development of more holistic approaches is therefore incredibly important.

To truly reap the benefit of these new solutions that could help bring us a more sustainable mental health care future, we must invest more into their research and development.

Author

Katja Bego

Katja Bego

Katja Bego

Data Scientist

Katja is a data scientist in the technology futures and explorations teams at Nesta. Her work focuses on using novel data sources and techniques to identify and analyse emerging tech...

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