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We Need More Evidence-based Homeless Interventions

June 27, 2016 / By Daniel Flaming

The Roundtable’s triage tools address the most acute dimension of homelessness – the small number of high-cost individuals who account for the majority of public costs. Other tools are needed to target earlier interventions for individuals with less acute needs who are on the path toward chronic homelessness.

A predictive tool is needed to identify the subgroup within the employable population for whom the cost savings after employment are greater than the cost of employment subsidies to help them re-enter the labor market. For example, $18,000 will subsidize six months of full-time employment at $15 an hour plus benefits, enabling individuals to establish a successful track record with an employer. A predictive tool is needed to identify individuals who are employable and whose public costs when employed are $18,000 less than their costs when homeless and unemployed.

A second predictive tool is needed to identify jail inmates who have a low risk of recidivism if housed, and for whom cost savings from reduced incarceration and use of other public services are likely to be greater than the cost of housing subsidies and mental and behavioral health treatment.

A third predictive tool is needed to identify youth between the ages of 14 and 24 who are in transition from foster care or justice system supervision to emancipated adulthood, who are at risk of high long-term public costs related to homelessness, justice system involvement, use of emergency health services, and dependence on public assistance. The tool will identify youth for whom long-term cost savings from reduced use of public services are likely to offset the costs of intensive mental and behavioral health treatment, employment services including job subsidies, and two or three years of extended housing subsidies.

The 10th decile triage tool is the first of multiple triage tools that are needed to target services that are cost effective in meeting the needs of different segments of the homeless population. Predictive risk models can guide more effective responses to homelessness by matching an array of interventions to the people most likely to benefit from them.