What if a city could help stop homelessness before it happened? Some cities are using predictive analytics and other strategies to identify residents who are at risk.

Ensuring residents stay in their homes can preempt what’s often a traumatic experience. Armed with data, social service agencies can reach out to residents to offer financial assistance or connect them with other resources. In doing so, cities can also potentially reduce costs associated with homelessness, such as the expense of building and operating shelters. Taxpayers spend $30,000 to $50,000 annually to cover the costs of one homeless person, according to the United States Interagency Council on Homelessness.

“Without connections to the right types of care, [people experiencing homelessness] cycle in and out of hospital emergency departments and inpatient beds, detox programs, jails, prisons, and psychiatric institutions — all at high public expense,” the Council said in a brief on supportive housing.

Although homelessness prevention makes financial and humanitarian sense, research in this area is limited, said Janey Rountree, executive director of the California Policy Lab, a nonpartisan organization focused on public policy research.

Each year, Los Angeles County provides 2 million single adult county residents with housing, health and emergency services — about 2% of those receiving assistance become homeless, according to CPL. But it has been difficult to know who is on that trajectory, Rountree says.

Predictive analytics can help identify at-risk individuals. Of the approximately 80,000 stably-housed, single adults and family heads of household who are eligible for services that the county’s Homelessness Prevention Unit provides, the prevalence of homelessness is about 5%. Based on CPL’s models, 30% of those on the high-risk list and who are referred to HPU will become homeless, Rountree says.

For HPU clients who are identified as high-risk, the Los Angeles County Department of Health Services provides single adult participants with either $4,000 or $6,000 in financial assistance, and family participants are offered either $5,000 or $7,000. Of the 54 clients in the initial HPU pilot, 90% self-reported that they kept their housing, Rountree says.

Spikes in service use and greater use of multiple services from a single agency, among other information, signaled a higher risk of users becoming homeless.

Read the full article about using predictive analytics by Karen Kroll at Smart Cities Dive.