Sergey Avdeychik, Director of Healthcare Technologies at Andersen.
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Deloitte currently projects the global spending on mobile mental health apps alone will amount to almost $500 million in 2022, up from less than $300 million in 2021. And we can anticipate the total market for software solutions for mental conditions will be even larger. The global market for mental health software was estimated to be $1.9 billion in 2020, and it's expected to reach $4.5 billion by 2026.
Key Facts On Mental Health
Mental health is a serious social and economic issue. According to the WHO, approximately 20% of the world’s population currently have a mental health condition, and this number is growing due to the ageing of the population we are seeing almost universally.
The Covid-19 pandemic has also had a detrimental effect on global mental health. Although the overall suicide rate does not seem to have increased so far in high-income countries, the situation in developing countries is different. The International Journal of Mental Health Systems outlines that 85% of people with mental disorders do not receive appropriate care in low- and medium-income countries due to the shortage of professionals and ubiquitous gaps in the infrastructure.
Here are four business solutions to these challenges provided by digital mental health company models.
1. Telemental Health
Telemental health is one essential area to explore. It has been proven effective by multiple studies, such as in these two large meta-analyses conducted both before and during the pandemic. The National Alliance on Mental Health has promoted the use of telemedicine as a tool for improving access to mental health. A 2021 survey of the American Psychiatric Association shows that 38% of Americans approached teleservices for mental issues versus 31% in 2020, indicating the growing rate of satisfaction.
2. The Internet Of Medical Things (IoMT)
Modern wearables and smartphones can report an extensive amount of relevant patient data for clinical purposes. Thus, tracking a person’s location via satellites or accelerometer sensors can help detect sedentary life which may highlight depression. One such tool is Juli.co.
Apps like Embrace and myCareCentric Epilepsy employ wristbands to track heart rate, skin conductance and movements to help people with epilepsy detect seizures earlier.
Another common way to access mental wellness is to track a patient’s interactions with an app. One joint product offered by Takeda Pharmaceuticals and Cognition Kit is an Apple Watch app monitoring the daily mood and cognition of patients with depressive disorders. Most mental health IoMT solutions are not invasive, which opens a great opportunity for businesses focusing on prevention, screening, assessment and treatment of mental disorders.
Probably the most significant among IoMT tools in mental health are devices from Medtronic and Abbott. These are able to obtain brain signals via implanted deep brain stimulation electrodes and transmit comprehensive information about the real-time brain activity to healthcare providers, allowing better management for patients with Parkinson’s disease.
3. Mental Health Data Management And Communication Tools
Since 2005, the WHO has been implementing Mental Health Information Systems (MHIS) for storing relevant information in all possible data layers (episode, facility and system levels). The collection, qualitative analysis and evaluation of big data and statistics on mental disorders can allow healthcare providers to improve patient treatment regimens, increase the accuracy of decisions and reduce costs.
One opportunity here has arisen in cognitive behavioral therapy digital platforms which use evidence-based interactive exercises, audio, videos and questionnaires. One such example of communication with proven effectiveness is Good Days Ahead.
Electronic emotional support programs can also be provided via less expensive text-based services such as a Canadian SaskWell, implemented as a part of a Covid-19 lockdown depression prevention program.
4. AI And ML Solutions
As stated previously, AI and ML in mental health are used for processing data from wearables and mobile devices using big data analysis. But their potential can be used to an even greater extent, as seen in these examples:
• Chatbots and virtual therapists. Woebot, a tool for coping with anxiety and depression, allows patients to assess their moods and receive support 24/7, significantly reducing relapses within 2-3 weeks of use. It has language localization and focuses on multi-topic human-like communication. The virtual therapist Ellie developed by ICT helps veterans cope with depression and post-traumatic stress. This app is able to recognize both verbal and non-verbal reactions of the interlocutor.
• ML algorithms. These can be used to analyze EMR and data of people with depression, allowing healthcare professionals insights to help determine predictions of suicide.
• Social networks monitoring. This can afford specialists information about the mental state of patients. Facebook posts, individual expressions and emoticons could help identify symptoms of depression three months before the need for treatment.
• Detection of eye movement and blinking, speech patterns and voice features. These can give great insights into the mental state of depressed patients.
• Smartphone usage tracking. Useful monitoring tools such as Boston's Cogito Companion app can process call logs, text frequency and geolocation to warn specialists about symptoms of mental disorders.
• The emerging concept of digital therapeutics. Defining the clinical effectiveness and safety of mental health applications allows for their prescription by professionals. One working example of this is in Germany's DiGA Fast Track, whose solutions have been proven effective in clinical trials.
A Few Best Practices
Drawing from my research and experience, here are a few best practices I would like to share with mental health app developers:
• Consider implementing self-monitoring features to help users track their improvements over time.
• Leverage feature customization (font size, color, background, layout, etc.), as these should allow for individual user preferences according to mental health needs.
• Ensure easy verification of the reliability and scientific relevance of the content of your mental health app.
• Offer peer-to-peer support and the opportunity to share experiences.
In Conclusion
As the world continues to struggle with crises and accessibility, a number and variety of mental health tech solutions arises. This may just be the beginning of a new chapter in exciting new mental health tech solutions.
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