Emily Putnam-Hornstein thought there had to be a better way to protect kids.

The USC professor of social work had seen the statistics: roughly 7 million children come to the attention of child welfare authorities every year in the United States; one in three American kids will be the subject of maltreatment investigations in their lifetimes.

“Do we really think a third of American children are so endangered they need the intervention of the child welfare system?” she said in a recent interview. “When you flood the system with that many calls of potential abuse and neglect, what you have a very hard time doing is detecting the signal from the noise and identifying which children do need protection.”

So she started researching how data might be utilized to predict which kids were most at risk and in need of services. We live in a world of big data: There’s more information known about every man, woman and child in the United States than ever before, in digital form. Why not use it to protect those youngest, most vulnerable members of society?

She got her chance to put her theory into practice three years ago, when she was invited by Allegheny County, Pennsylvania, to develop a predective analtyics tool there to help screen allegations of child abuse and neglect. That Pittsburgh-based agency — the Office of Children, Youth and Families — had recently come under scrutiny for failing to investigate kids who ultimately died from maltreatment.