The University of Michigan received a 17.9 million dollar grant from the National Institute of Mental Health June 25th to study mental health treatment. The study, called COMPASS, aims to improve first-time mental health treatment and better predict what treatment methods or combination of treatment methods work best for patients.
In an interview with The Michigan Daily, Amy Bohnert, one of the three principal investigators of the study and a professor of anesthesiology, psychiatry and epidemiology, said the study aims to develop an algorithm that uses patient data to generate the ideal treatment plan for them.
“We will use machine learning and related modeling techniques to develop algorithms that match each patient, based on their data, to the treatments that are predicted to result in the greatest level of symptom relief,” Bohnert said. “We will do analyses to look at a whole range of patient characteristics including behavioral factors and genetics, and if we build this algorithm it would say for this person, they’re going to have the greatest success if they start with this treatment or combination of treatments.”
Researchers intend to use questionnaires, wearable trackers and other methods to collect data on genomics, social data, demographics, psychological data, family history, behavioral data, cognitive data and medical history.
In an interview with The Daily, Srijan Sen, psychiatry and neuroscience professor and another principal investigator of the study, said the technology the study will use to record patient data has only recently been developed, making this study unique in its usage of these new tools.
“We haven’t before had the mobile technology such as Fitbits and Apple Watches for example that are collecting a lot of data about people’s behaviors in an objective real-time way,” Sen said. “Then in genomics, we have much more in-depth and granular data than we have ever had before. This question of matching treatment has been there for a while but now we have these new tools to make progress in a way that we haven’t before.”
Sen said instead of having to try many different types of treatment such as cognitive therapy, medication and transcranial magnetic stimulation to find the best fit, the study aims to generate an algorithm that can find the right plan for an individual right away.
“Whereas now a lot of patients have to go through lots of trial and error and several trials of treatment often taking years to get to the one that works, we hope to get them to that one right away,” Sen said. “If we get people to the treatment that works much more effectively then that will help reduce the backlog of people looking for care which will also open up providers to see more people. This will hopefully lead us to a point where there is no waitlist and if you need help you can see someone right away.”
Business rising junior Maya Lindsley, board member of the CAPS student advisory board, said she felt the study could play an important role in working to cater to an individual’s specific treatment needs.
“This study is cool in that they are using data collection to see what would be best for an individual,” Lindsley said. “Beforehand we had marketed the same common treatment methods broadly and consistently because it was harder to be specific about it. This study is more catered to different individuals.”
Daily Staff Reporter Alyssa Tisch can be reached at tischaa@umich.edu.
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