Everyone wins if homeless service providers have insights that help them provide timely and targeted support for their at-risk clients. The fusion of technologies in the pilot described below seems to be a promising step in that direction.
For more than 20 years, the ClientTrack Case Management platform from Eccovia Solutions has been helping homeless services organizations and continuums of care deliver critical services to individuals experiencing homelessness.
Eccovia recently announced it has completed a machine learning pilot with homelessness data to predict recidivism at the time of intake for individuals experiencing homelessness.
The predictive analytics pilot combined the Cortana Intelligence Suite from Council Lead Partner Microsoft with Eccovia's case management platform to deliver cloud-based, real-time, predictive analytics they say not only improves outcomes for individuals experiencing homelessness but also reduces costs for providers.
"The combination of ClientTrack Case Management with the advanced analytics capabilities of Microsoft Cortana Intelligence enables more precise predictions that help service organizations provide more targeted and timely support to homeless individuals at risk of recidivism," explains Herain Oberoi, a Microsoft senior director of product marketing.
Carl Champagne, CEO of Eccovia Solutions, suggests that integrating the company's ClientTrack solution with Microsoft Azure Machine Learning "is a game changer for homeless service organizations and the communities they serve."
This article is from the Council's Compassionate Cities initiative which highlights how city leaders and other stakeholders can leverage smart technologies to end suffering in their communities and give all citizens a route out of poverty. Click the Compassionate Cities box on our registration page to receive our weekly newsletter.
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