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Harnessing Big Data to Improve Children’s Mental Health Treatment

NOMIS Project 2019

— 2024

Children’s mental health is an area where new approaches to evaluating clinical practice are urgently needed. Worldwide 10 to 20% of children suffer from some form of mental disorder, which often have more harmful effects on children’s future education and employment prospects than common physical health problems. Hence, identifying the most effective treatments is critical. But there are an overwhelming number of treatments and psychotropic medications on the market that are not well tested in children, or that are not tested in children at all.

The research project, Harnessing Big Data to Improve Children’s Mental Health Treatment, is investigating whether administrative big data can be used to identify those therapies that are most promising for children with diagnoses of mental disorders, as well as those therapies that pose the highest risk of harm. Using big data generated by the health care systems of various countries, the project aims to better understand children’s mental health and ultimately to improve the diagnosis, treatment and prognosis of children with mental health conditions.

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NOMIS Researcher(s)

Henry Putnam Professor of Economics and Public Affairs
Princeton University
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Project News

In a Princeton University news-focused series featuring faculty who present their views on current events, NOMIS Awardee Janet Currie shared her insights into how the global pandemic has impacted mothers […]

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Project Insights

Abstract:

Child health is increasingly understood to be a critical form of human capital, but only recently have we begun to understand how valuable it is and how its development could […]