New York’s Mount Sinai Health System has announced a new research collaboration with IBM Research, Harvard, Johns Hopkins, Columbia, Carnegie Mellon, and Deliberate AI, using AI and behavioural data to predict outcomes such as treatment discontinuation, hospitalisations, and ED visits for young people seeking mental health evaluation and treatment.
The Phenotypes Reimagined to Define Clinical Treatment and Outcome Research (PREDiCTOR) study, funded by a $20 million grant from the National Institute of Mental Health, will look at the utilisation of “objective, scalable, and cost-effective measurements” to “define novel clinical signatures” to help predict behaviours and support clinical decision-making for mental health.
Cheryl Corcoran, MD and program leader in psychosis risk for Icahn Mount Sinai, talked about how “advancements in computational approaches” can help researchers to gain insight from “a wealth of untapped behavioural data” from clinical visits, as well as “valid behavioural data derived from smartphones” to aid in the developments of “clinical signatures that are indicative of key outcomes”.
The study will focus on patients aged 15 to 30, who present at one of six Mount Sinai outpatient mental health clinics. Patients will be invited to have their clinical visits recorded over the span of one year.
The goal, according to Guillermo Cecchi, director of the computational psychiatry and neuroimaging groups in IBM Research, is to “gain a better understanding” to predict whether young people stay in mental health treatment, as well as of “what predicts whether their symptoms worsen” to a point at which they require acute care.
In other news on digital mental health, three hospitals in Estonia have announced a new pilot which will see the introduction of digital mental health screenings and assessments for patients, with the aim of helping to “standardise and expedite care for individuals with mental illness”.
And on data, the Catharina Hospital in Eindhoven, The Netherlands, has highlighted the importance of data collaboration and “learning together” through the ICUdata project, taking the lead on organising the delivery of data across healthcare organisations utilising the HiX EPR.
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