Why AI in healthcare is essential for improving mental health and wellbeing

Last month, I wrote a Forbes article on Why AI and Healthcare Will Make Our World a Better Place, and it was so popular that I continued this talk. However, in this article, I want to focus on mental health and wellbeing and the value of AI approaches that can help in this growing segment.

First, how big is the mental health and wellness market segment focused on employee wellness?

According to Allied Market Research, the global mental health market was valued at over $383 billion in 2020 and is expected to reach nearly $550 billion by 2030. This market segment is characterized by lack of emotion positive and low mood, and a range of associated cognitive, physical, emotional or behavioral symptoms. These conditions affect 1 in 5 people in an organization.

What is the main mental health problem?

Depression is the leading cause of disability worldwide and the leading risk factor for disease. What is most worrying is that depression and anxiety are on the rise. The World Health Organization (WHO) reports that around 4% of the world’s population suffers from depression. Interestingly, the United States is also the most depressed country in the world.

In addition to these realities, the global pandemic has triggered a more than 25% increase in the prevalence of depression and growing anxiety.

“The information we currently have on the impact of COVID-19 on mental health around the world is just the tip of the iceberg,” says Dr Tedros Adhanom Ghebreyesus, WHO. “This is a wake-up call for all countries to pay more attention to mental health and do a better job of supporting the mental health of their populations.”

What are the signs of depression?

The Diagnostic and Statistical Manual of Mental Disorders defines a major depressive episode as at least two weeks of depressed mood or loss of interest or pleasure in almost all activities, plus at least five other symptoms, such as:

• Sleep problems on an almost daily basis (difficulty sleeping or sleeping too much)
• Changes in appetite and weight (more than 5% change in body weight in a month) or decrease or increase in appetite almost every day
• Decreased energy or fatigue almost every day
• Difficulty concentrating, making decisions and thinking clearly
• Restlessness or psychomotor slowing observable by others (slow physical movements or involuntary or aimless movements)
• Recurrent thoughts of death or suicide Suicide attempt or specific suicide plan

Mental health is a board issue

The latest WHO mental health report indicates that in 2020, governments around the world spent on average just over 2% of their health budgets on mental health and many low-income countries reported have less than one mental health worker per 100,000 people.

This is clearly insufficient.

With the great downturn underway across North America that began during COVID and has continued to impact and disrupt global supply chains. Many of these employees don’t leave because of their salary or the company’s role per se, but many leave because of indifferent bosses, which continues to be a major thorn in leadership. Unhappy people are 4 times more likely to be depressed and finding ways to identify these risks early on is a boardroom problem.

According to McKinsey research, two-fifths of people are unhappy at work and plan to quit their job in the near future, according to a new McKinsey survey. Many of these resources also do not return to their industry, so the havoc in talent search operations causes considerable pain.

Therefore, administrators and all C-levels need to think very seriously about improving their focus on mental health and wellbeing. This is a serious problem that will require daily attention to stem the tides and avoid higher tsunami risks.

Highlights:

Statistics show that workers continue to leave or at least consider leaving their jobs. More than 4 million people in the United States quit their jobs in June. More than 11 million job vacancies remain unfilled, according to the US Bureau of Labor Statistics. There are nearly 900,000 vacancies in Japan, with a job-to-application ratio of 1.27. In the UK, there are more vacancies available than unemployed for the first time since records began. And in the EU, almost 3% of jobs on average remain vacant.

Value of AI Solutions to Meet Healthcare Needs

(IA) is increasingly popular with mental health care patients. AI can be used not only to detect depression risk, but also to treat depression with tools to manage depression symptoms by collecting feedback, providing personalized recommendations, delivering the right content, being a surrogate companion and, most importantly, ensuring that employee voices are heard and information resolves any systemic working conditions or leadership behavior issues.

Privacy and Access

An AI app can provide a safe place for an employee to share how they are feeling and be able to track their mood as an insight into a healthier life. It can also provide recommendations on how to improve an organization’s work practices and raise issues of abuse or inappropriate leadership, behaviors such as diversity and inclusion, or sexual harassment. Operate in a safe environment AI can create a safe place to express feelings, or even express yourself and know that you are safe, because the data about your experiences can be 100% anonymous.

Plus, AI applications can be there for your employees day and night, 365 days a year. Most mental health apps also provide easy access to resources anywhere supporting various resources: mobiles, laptops, etc. Complete convenience on your terms.

Insightful mood patterns

What AI can do is that when the employee becomes more engaged in using the application, the AI ​​models can learn more not about the user, but about all the users and train statistical happiness risk models, guiding management to predict future risks or help mitigate current risks more quickly. More privately aggregated data can also form overlay patterns in areas such as email science combined with natural language processing can be used to examine emails or voice speech over time and analyze how language changes over time in the way an employee or team communicates. , sending tips to each employee to protect their anonymity. It will be imperative for privacy to ensure patterns are vetted at 20 cues in a leadership team, so early patterns can be safely analyzed creating new conversations, educating employees about health benefits and well-being of a business or planning for early intervention. for team communication.

Regardless of the approach taken with AI, anonymity and privacy should be carefully considered before selecting an AI software tool focused on health and wellness.

Relevance of AI content

AI-powered depression resources can also be helpful to management and peers so that feelings of fear, guilt, or shame don’t get in the way of employees having a conversation and supporting talent when needed. of need. For example, if a mood AI app sees you feeling sad for 7 days or more, the app can send interesting resources to the end user, all without anyone else knowing – apart from the person who might need it. Aggregated information can inform management of new resource needs to support trends found in the data. Natural language processing (NLP) analyzing all verbatim can also be used to inform the creation of an AI content strategy.

Sense of belonging with a connection buddy

In today’s fast-paced world, the ability to see a private counselor is increasingly complex and often engages with an app that asks you questions about how you are feeling and guides you to a relevant content stimulating ideas that you can act on privately. is a very profitable alternative to private advisors. Private apps can create a safe space to express emotions and discuss difficult situations.

Being able to forge a connection and feel genuinely heard is part of the process of healing from depression.

AI can also advise on who to talk to when certain situations arise and find relevant experts or content that they wouldn’t easily find in a large organization.

Conclusion

AI in healthcare will continue to create new solutions that are not only relevant, timely, private and secure, they will provide access to many underserved populations who cannot access or afford counseling support services. , therefore, private AI software solutions with strong diagnostics and support for mood and happiness monitoring systems will become more and more commonplace like the office water cooler, or with office employees. working from home today, perhaps the ease of access to a refrigerator is a more apt analogy.

What is clear is that as board directors and C-suite leaders, it is imperative to understand that happiness is key and that depression and sadness are on the rise, to new mental health and wellness toolkits will be needed and many of them will focus squarely on mood and many will use innovative AI methods for more robust and intelligent sense-making.

My next blog will focus on AI health apps that focus on mental health, mindfulness, and can provide support for depression.