What Role Can AI Play in Mental Health?

When it comes to treating mental health issues, care providers and patients face a variety of obstacles, from a lack of treatment options to a lack of available care providers to the stigma surrounding having and being treated for mental illness. However, mental health is just as important as physical health, and the two components often affect each other. In order to address mental health concerns and help keep people healthy, there need to be more accessible care options and better care. 

Fortunately, artificial intelligence (AI) can play a valuable role in mental health. AI can increase the number of resources available for people seeking mental health care and make those resources more easily accessible, as well as support care providers in improving the quality of care to keep patients physically and mentally healthy. Here’s a closer look at some of the ways AI is improving mental health care.

 

Mental Health, AI

Telehealth 

Computers and the internet opened a whole new world of possibilities, including the ability to speak with medical professionals virtually rather than seeing them in person. Telehealth also increases access to care, especially in areas where there isn’t a hospital, doctor’s office, or other care facilities nearby. Having more ways to access healthcare makes it easier for people to get the care they need, which can help keep them healthy. During the height of the COVID-19 pandemic, for example, there was an increase in the use of telehealth, and about 54% of telehealth users were seeking help for behavioral health concerns rather than a chronic physical health condition, a study shows

Telehealth becomes even more beneficial when it’s supported by AI. For example, Lumiata uses AI and machine learning to generate predictions and other helpful insights using a vast dataset. Predictions include acute and chronic disease onset, such as bipolar disorder, dementia, depression, alcohol dependence syndrome, and more, plus medical events like hospitalizations and readmissions. Care providers can then use these insights and increased data precision to improve their telemedicine strategy and operations. Providers can better manage chronic disease regardless of location, intervene earlier and remotely before the patient requires in-person care, and get ahead of patient needs to positively impact outcomes. 

AI is also being used in other forms of telehealth, including training tools and chatbots. The Trevor Project, the world’s largest suicide prevention and crisis intervention organization for LGBTQ youth, partnered with Google to create the Crisis Contact Simulator, an AI-powered counselor training tool that simulates conversations with LGBTQ young in crisis [i]. This enables trainees to practice realistic conversations before interacting with actual people. 

AI-powered chatbots are another form of telehealth that makes care more accessible. Bots can be trained to look at the words someone is using via messaging to gain a sense of how the person is feeling and how the bot should respond to provide care. While bots shouldn’t completely replace human care providers, they can provide support by being available 24/7 and giving people alternative options if they aren’t yet ready to schedule an in-person visit.

AI, Mental Health

Disease Onset Prediction 

The ability to predict the onset of diseases can help care providers offer more personalized care promptly and achieve better outcomes for their patients. This is true regarding mental health as well as physical health. AI can be used to generate such predictions and other actionable insights from healthcare data. Lumiata, for example, can use AI and machine learning to predict the onset of bipolar disorder, depression, and a wide range of other mental and physical conditions within the next 12 months. Care providers can use these predictions to address their patients’ risk factors sooner and with more specialized care. 

Lumiata can also use AI to predict alcohol dependence syndrome, giving care providers the ability to intervene promptly and discuss the associated risk factors with their patients. Excessive alcohol consumption can negatively impact mental health. [ii] So avoiding alcohol dependence syndrome may benefit the patient’s mental health. 

Helping patients avoid diseases can help prevent patients from experiencing the feelings of stress and depression that people may feel after being diagnosed with and while dealing with a chronic illness. Additionally, when patients adopt healthy habits like getting more exercise and eating nutritious meals to help ward off disease, they may find their mental health improves. Aerobic exercises have been shown to reduce anxiety and depression [iii] and eating healthy food can help reduce fluctuations in mood and help ease symptoms of anxiety and depression. [iv]

AI can help healthcare professionals provide personalized preventive care that can lead to improved mental health. 

 

AI, Mental Health

High-Quality Data 

The key to using AI most effectively and generating actionable insights is having high-quality data. The better the data that’s being used with AI, the more accurate and beneficial that telehealth, chatbots, predictive analytics, and other AI-powered solutions

can be. To ensure high-quality data is being used in our AI products, Lumiata transfers your data to our ecosystem and performs data quality assessments. We then normalize, validate and clean your data, removing any data that’s incomplete, incorrect, duplicate, or improperly formatted. We also tag your data using our proprietary disease codes to identify indicators of chronic and/or catastrophic conditions linked to specific individuals. 

Next, we enrich your data with our own propriety data, which we’ve collected from millions of patient records and healthcare data, medical knowledge, clinical IP, tens of thousands of physician curation hours, and millions of published articles. With your data cleaned and enriched, we create Lumiata Person360 objects, optimized data artifacts for machine learning consumption. 

From here, you can use our Lightning AI Model Builder or Spectrum AI Model Catalog to run clinical and financial data models to generate predictions and helpful insights. Informed by the results, you can provide higher quality care to support your patients’ mental health. 

 

AI, Mental Health

Request a Demo 

AI won’t replace the need for human connection, but it can supplement in-person care to make mental health care more easily accessible. To see how Lumiata can play a role in your mental health care efforts, click here to request a demo.