Abstract
ABSTRACT The Simplified Access Metric (SAM) is a new approach for characterizing patterns of homelessness. The goal of SAM is to provide emergency shelter operators and housing staff with an intuitive way to understand a person or group’s pattern of homelessness and/or shelter access that can be implemented by non-technical staff using spreadsheet operations. Client data from a large North American shelter will be used to demonstrate that SAM produces similar results to traditional transitional, episodic and chronic client cluster analysis. Since SAM requires less data than cluster analysis, it is also able to generate a timeline of homelessness patterns that can be updated in real time. Using nine years of shelter data, a shelter access timeline is presented that includes the introduction of Housing First programming and the COVID-19 lockdown. Finally, SAM allows shelter staff to move beyond assigning transitional, episodic and chronic labels and instead use the “soft” output of SAM directly to better understand a person’s experience of homelessness.
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