5 ways AI can help change the future of mental health care

Artificial intelligence (AI) is taking the world by storm and is being used in almost every field to enhance and optimise workloads. What once might have taken hours is simply taking minutes all because AI can help within an instant, which begs the question of what else can AI help with?

Well, there’s a growing pile of research suggesting we perhaps should be using AI in mental health care to help with diagnosing patients, expanding on types of therapy, and improving treatments. Let’s take a look at how AI can potentially change the future of mental health care as we know it. 

5 ways AI can help change the future of mental health care

  1. AI therapists

Some people have suggested that patients might be more willing to talk to a robot about their challenging feelings over a human, as the robot is less likely to judge them and make them feel embarrassed. Before chatbots were a thing, this would’ve been impossible to manage. However, now that chatbots are being used as a line of communication in many mental health treatment plans, it is learning how to offer advice for coping with symptoms, look out for keywords to trigger referrals, and more. 

Even though AI cannot replicate the true feeling of talking to a healthcare professional about mental health, it could be used as an effective starting point to get vital information before the patient is referred to a human professional. 

  2. Wearable AI

We know what you’re thinking – how can you wear artificial intelligence?! Well, there is some research and development being done for AI mental health solutions that can be worn and used to interpret signals from the body with sensors, getting the patient the best help as quickly as possible. 

For example, some wearable AI has been effective in collecting information regarding sleeping patterns, heart rate, physical activity, and more. This information can then be used to analyse and determine the patient’s cognitive state and mood. When compared to data from other patients, it might be useful in knowing when to intervene or change the treatment plan. 

  3. Diagnosing patient outcomes

When inputting patient medical data into an AI system, it might be able to analyse and even diagnose patient outcomes in a fraction of the time humans can. It can also use things like behavioural data, voice recordings, and past medical data to flag warning signs before things escalate to a more troublesome state. 

Not only can this save human professionals time and resources in diagnosing their patients, but it can also help the patients get the treatment they need as quickly as possible. This can cut down on negative outcomes and get patients seen by professionals in a risk-based order. 

  4. Improving patient compliance

Many healthcare professionals will agree that one of the slowest-moving components of treating mental health patients is their compliance. Sometimes patients don’t understand or agree with the treatment plans offered to them, so AI can make sure that they’re complying with taking their medicines and attending therapy. 

AI can be used in a number of ways here, such as reminding patients of appointments and medicine times through texts, emails, and even calls. We might even be able to use AI to determine whether the patient is likely to skip a treatment session, which we can then use to check in on them and prevent them from missing medicine or therapy. 

  5. Personalising treatment plans

Once AI has learned about the patient’s history, symptoms, and personality, there is the potential to use it for personalising treatment plans to make sure they’re getting the best course of action for them. While this might take human professionals days or weeks to learn and use for a personalised treatment plan, AI can do it within a matter of minutes. 

There is the concern of how AI will be able to learn all of these things about patients enough to be trusted with creating treatment plans, but when it’s been used for monitoring symptoms and reactions to treatments, it will have been learning in the background to make sure it’s ready for the task. Human professionals will still need to look over the treatment plans to make sure they agree with them, but using AI in this way could still save a lot of time. 

Final thoughts

We’re still a long way off from using AI solely for mental health care, but the idea certainly is exciting! Plenty of research still needs to be done on the effectiveness of AI and how we understand its inner workings, but with it already being implemented in some areas like wearables and chatbots, the idea of depending on it more heavily in the future doesn’t seem unfathomable.