skip to main content

Harnessing Natural Language Processing to Measure Person-Centered Care in Behavioral Health Settings


Graduate School of Social Service Assistant Professor Elizabeth Matthews, Ph.D., is working alongside Principal Investigator (PI) and NYU Silver School of Social Work Professor Victoria Stanhope on a new project using Natural Language Processing to examine Collaborative Documentation.

The project will be funded by a $70,500 inaugural faculty research grant from NYU’s newly established Constance and Martin Silver Center on Data Science and Social Equity. Matthews and Stanhope will also work alongside consultant Dr. Sarah Shugars, of NYU’s Center for Data Science and George Washington University’s School of Media & Public Affairs.

Their study, “Harnessing Natural Language Processing to Measure Person-Centered Care in Behavioral Health Settings”  will use Natural Language Processing, a branch of artificial intelligence, to measure person-centered care using behavioral health visit notes, and test whether training providers in Collaborative Documentation (CD) affects how providers deliver person-centered care in practice.

“Person-centered care, which ensures that care is individualized and that service users are active and empowered partners in their treatment, is widely recognized as a solution to the persistent problem of service disengagement within the mental health system,” Matthews said. “Because person-centered care is so individualized, translating this approach into specific clinical strategies has been challenging, and it is difficult to measure in practice. Our study seeks to address both of these obstacles by using NLP to develop scalable, objective ways to measure person-centered care, and by evaluating whether training behavioral health providers in collaborative documentation, a person-centered approach to recording behavioral health session activities, helps providers adopt more person-centered strategies in practice.” 


Comments are closed.