From automating administrative tasks to clinical decision support, the use cases for artificial intelligence in healthcare continue to multiply. One unique approach is the use of natural language processing to gauge the risk of suicide among behavioral health patients.
Maker of behavioral health integration software, published the results of a study that found NLP software could discern possible suicidal ideation in more than half of patients that may otherwise have gone undetected.NLP can flag a patient at-risk journaling in NeuroFlow and push crisis resources. The app will also generate an alert that gets sent to their care manager, who can reach out between office visits.
They also facilitates measurement-based care through frequent assessments like the PHQ9 and logs patient data like sleep and mood ratings. While 81% of participants were compliant with their PHQ9—a questionnaire that screens for depression and suicidal ideation—of those, nearly half had not indicated suicidal ideation on their most recent assessments. In total, 58% may not have been identified as being at risk of suicide without NLP.
Because NLP can be deployed remotely and at scale, it is well positioned to support marginalized communities where suicide rates are highest, psychiatric resources are scarce and the social determinants of health persist, the study argued.
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