AI mental health solutions are taking the load off overburdened doctors

AI mental health solutions are taking the load off overburdened doctors


The stress and burden under which we place our workers has been a key focus during and since the Covid-19 pandemic. As the curtains finally seem to have closed on the Covid-19 era, many scars remain.

Not just in terms of the millions of people worldwide who have developed mental health conditions due to the virus or the effects of lockdowns, but in terms of our workplace habits themselves.

In the UK, workers in their fifties, from whom the treasury had been expecting tax receipts for perhaps the next 20 years, left the labour force in their droves. According to the Office of National Statistics (ONS), adults in their 50s were less likely to leave work for retirement (28%, compared with 56% for the over 60s), and more likely to give stress or mental health (19%, compared with 5%) or a change in lifestyle (14%, compared with 7%) as reasons for leaving work.

Perhaps nothing in modern human history has altered attitudes to work and mental health more profoundly and quickly than the pandemic, and certainly since the first world war. Anxiety in the workplace is no longer seen as a price worth paying for a fulfilling or high-end career.

So dramatic is the change in attitude that the only effective tax cut offered by the British Chancellor was a lifting of the pensions cap to encourage the most productive older workers to return to the fold, especially doctors.

The stress and mental anxiety of working in certain environments, including hospitals, has given rise to calls for higher pay, better workplace conditions and mental health support for employees. Yet not only do these come at a time of low fiscal headroom and record high taxation, but at the same time as a record backlog in hospitals across Europe, as people seek treatment they missed during the pandemic.

“Demoralisation syndrome” diagnoses are on the rise, especially amongst hospital workers. The WHO estimates that 12 billion working days are lost every year to mental health problems at a cost of US$ 1 trillion per year in lost global output.

As if in unison, economists, doctors and the taxpayer are beginning to realise that mental health support can no longer be seen as a luxury, or a service offered compassionately to workers. Rather, we are beginning to learn that money not spent on mental health services is truly a false economy.

AI tech solutions, naturally, are beginning to enter the market in a genuinely compelling way, attempting to square the circle of low budgets and high demand by leveraging the power of machine learning. For instance, Kintsugi is an AI-powered screening tool to identify depression and anxiety using short audio clips of someone’s voice. CEO and co-founder, Grace Chang, claims that the technology can identify such conditions 80% of the time. This may at first sound like a useful stop-gap solution, but once one realises that human health practitioners can only identify depression and anxiety in 47% of cases, the true power of these type of solutions is laid bare.

WinningTemp is another start-up firm, designing survey-based and AI powered approaches to monitoring the wellbeing of staff. Designers claim that it is powerful enough to distinguish between temporary tiredness and more chronic burnout. Yet the technology sector is not just working on the diagnostic side. AI systems are also being developed to handle the administrative side of treatment on behalf of doctors, analysing and inputting patient medical records, family histories and relevant treatments and contraindicated medicines so that the practitioner can focus on the patient. Dr Yair Lewis, a senior vice-president at Navina, quips that, counter-intuitively, “We’re bringing in AI in order to bring back humanity.”

By keeping costs as low as possible we can hope to expand provision with the help of AI and not only leave as many resources as possible remaining for treatment, but reduce the total amount of resources required.

Identifying stress and dissatisfaction in workers early can be the difference between the effectiveness of simple treatments such as meditation, chewing gum and stress balls, and the necessity for much more expensive therapeutic options and medicinal treatments.

We must all hope that AI is able to deliver on its incredible promise, and with not a moment to spare.

Image: By Steve Jurvetson – https://www.flickr.com/photos/jurvetson/50280652497/, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=93666208

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