  This paper explores how to best identify clients for housing services based
on their homeless shelter access patterns. We focus on counting the number of
shelter stays and episodes of shelter use for a client within a time window.
Thresholds are then applied to these values to determine if that individual is
a good candidate for housing support. Using new housing referral impact
metrics, we explore a range of threshold and time window values to determine
which combination both maximizes impact and identifies good candidates for
housing as soon as possible. New insights are also provided regarding the
characteristics of the "under-the-radar" client group who are typically not
identified for housing support.
