Los Angeles County, in California, is using predictive modeling to help prevent homelessness for vulnerable residents. The tool the county is using was developed by UCLA researchers; it pulls data from eight L.A. County agencies to help outreach workers focus their attention and assistance on people believed to be at the gravest risk of losing their homes. "You would never have enough money to provide prevention for everyone who appears to be at risk. You really need another strategy to find out who's actually going to become homeless if they don't get immediate assistance," said Janey Roundtree, the founding executive director of the California Policy Lab at UCLA. The predictive model now being used in L.A. County uses an algorithm that incorporates about 500 factors, including data points like who has landed in the emergency room, who has been booked into jail, who has had a psychiatric crisis that led to hospitalization, among others. With this data, the county is doing outreach and providing assistance to people at risk of homelessness that they would never have otherwise found. And they are providing resources that, in many cases, enable people to maintain their housing. So far, roughly 90% of participants have retained their housing while in the program.

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