The beginning of a new era

As we slowly emerge from more than a year of continued economic uncertainty, ongoing lockdowns and restrictions on our abilities to connect with others, we can all feel that the next pandemic to hit will be a mental health one. Everyone I know has been struggling in their own deeply personal ways over the past year. I have been struggling.

A rare silver lining on this COVID-19 crisis, however, is that it is acting as a powerful accelerator for innovation in mental healthcare. Twenty years ago, one of the world’s leading psychiatrists conceded that 21st century psychiatry was still in a “pre-Copernican” stage of maturity—where astronomy was before we knew that the earth orbited the sun, or biology before Darwin’s Theory of Evolution1. Just before the turn of the millennium, he claimed that mental healthcare was stuck in a form of “psychiatric Dark Ages”, with innovation hampered by dogma, false assumptions, stigma, poor data, and even profiteering.

For most people, not much about mental health care changed in the decades after those words were uttered, until 2020 happened. Fuelled by surging and urgent demand from consumers and healthcare systems during the COVID-19 crisis, moves to outcome-contingent mental health spending in major markets2, an empowered public discourse, and the popularisation of self-serve psychological science, in the past year, the rate of innovation in mental health has reached dizzying proportions.

We are now entering a new era: one of humanising, digitising and scaling mental healthcare in ways never seen before.  Many forces are at play in the reshaping of the mental health sector, but the three below are some of the most profound. As they play out over the next decade, the ways that scientists, innovators, businesses, and practitioners, predict, prevent, treat, and cure mental illness will look very different than anything that has come before.

Three forces reshaping mental healthcare

1. Precision: greater precision in diagnostics and treatment will likely enable better health outcomes  

By 2030, society may be moving away from the use of familiar mental health diagnoses such as “Major Depression”, “PTSD”, or “Generalised Anxiety Disorder”.  Instead, some parts of the world may see new “transdiagnostic” systems emerging – ones in which the specific biological, cognitive and social causes of a person’s mental distress can be diagnosed and treated with far greater precision.

This shift is already underway, being led by groups of scientists who believe that our current systems for diagnosing mental illness very broadly may in fact be hindering clinical research and innovation (for example, there are over 600,000 ways a person can qualify for a diagnosis of PTSD3, and 16,400 symptoms profiles that qualify for a diagnosis of Major Depressive Disorder4).

If this trend continues, it’s not impossible that in 2030, patients may hear prognoses such as the following from their care provider: “You’re homozygous for two short alleles of the serotonin transporter gene and you default to a negative interpretation bias, so you’re at higher risk for depressed mood following stressful life events. A resiliency programme coupled with training in cognitive bias modification could help to protect you from severe mental illness later in life.”

Powered by new clinical data lakes that combine biological, psychological, social behavioural data sources, and mined using advanced analytics and artificial intelligence/machine learning (AI/ML), new approaches to precision mental healthcare such as these could take the meaning of personalisation in mental healthcare to new heights and could transform lives in profound ways.

2. Automation: human-computer interactions hold the potential to become a cornerstone of mental health care

According to forecasts by the World Bank, by 2030, the world will be 15 million mental healthcare workers short of the numbers required to meet global mental healthcare demand.5 Because of this, human/computer interactions will likely need to become a cornerstone of mental health intervention, if we are to be able to get mental healthcare to everyone who needs it, when they need it.

If done well, this should not necessarily compromise the patient experience or care quality. Accenture’s 2020 Digital Health Consumer Survey revealed that 54 percent of people in the USA are willing to receive virtual healthcare from traditional medical care providers (rising to 76 percent for millennials), and basic therapies such as Cognitive Behavioural Therapy (CBT) delivered using chatbots are beginning to report very promising outcome data.6

In the future, patient engagement with computer-led psychological interventions may even come to surpass the engagement levels we currently see in human-to-human psychological care. This is because digitally delivered psychological interventions can dissolve some important barriers to care-seeking (such as stigma, cost, time and travel), and in doing so, can pave the way to greater health outcomes at scale.

As clinicians and technologists get better at identifying some critical aspects of mental healthcare that can be successfully automated, providers should be able to free up their scarce human resources to do truly complex work, leaving more routine aspects of psychological intervention to computer companions.

3. Experience: the importance of the patient experience could come to equal the importance of the clinical intervention

There’s a reason some of the world’s most valuable mental health businesses right now are those that have modelled themselves on media companies (e.g., Headspace and Calm, who were among the first to reach valuations of $1Bn each). Mental health treatment journeys are long and so for them to be effective, we have to design products, services and experiences that people fall in love with, and want to stick to, over time. 

Mental health care is not like other types of medicine: relatively quick interventions like surgery or medication don’t get to problems at their root; instead, people need to engage with their bodies and their minds over weeks, months, and years to build resiliency or achieve recovery. This makes delivering impact in global mental health as much a creative challenge as a clinical one.

Those organisations who will lead will be those who can delight users with engaging, accessible, enjoyable and even entertaining experiences – experiences that situate effective clinical interventions within the context of compelling care journeys, and that captivate hearts, minds, attention and time over the long-haul.

Conclusion

Re-imagining mental health care is one of the most important challenges of our time.  However, mental health science is a complex space, and it’s going to take an innovative mix of new capabilities in clinical research, data science, product development, automation, and experience design to go from innovation to true global impact. Knowing what to do is just the first step of the journey—the most exciting part comes next as mental health entrepreneurs and systems shapers bring these capabilities together with confidence, and execute with discipline, to transform this sector for the better, forever. Thankfully, the conditions and capabilities to power this transformation are right in front of us - we just need to know where to look.

As you can tell, I am passionate and excited about what the future of mental healthcare will look like, and how the alchemical mix of technology and human ingenuity will enable us to deliver better health outcomes for all in the next decade. If you think I’ve missed a major force of change, or if you’d like to challenge, endorse or build on any of this thinking, please do share your thoughts.

1Frances, A. J., & Egger, H. L. (1999). Whither psychiatric diagnosis. Australian & New Zealand Journal of Psychiatry33(2), 161-165.
2“Transitioning to Value-Based Payment Models in Behavioral Health”, Healthcare Innovation.
3Isaac R Galatzer-Levy, Richard A Bryant (2013) 636,120 Ways to Have Posttraumatic Stress Disorder, https://pubmed.ncbi.nlm.nih.gov/26173229/ (accessed 06/15/2021)
4 Eiko I. Fried, Randolph M. Nesse (2014) Depression is not a consistent syndrome: an investigation of unique symptom patterns in the STAR*D study, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4397113/ (accessed 06/15/2021)
5 Jenny X. Lui et al (2016), World Bank, Global Health Workforce Labor Market Projections for 2030, https://documents1.worldbank.org/curated/en/546161470834083341/pdf/WPS7790.pdf (accessed 06/15/2021)
6 Fitzpatrick KK, Darcy A, Vierhile M. Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial. JMIR Ment Health. 2017 Jun 6;4(2):e19. doi: 10.2196/mental.7785. PMID: 28588005; PMCID: PMC5478797.

Sarah O'Farrell

Manager – Health, Behavioural and Psychological Sciences Lead

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