Unique Individuals & Length of Stay

My mind has been blown twice this month looking at shelter data.

The push that many of us have been trying to make is to know the people touching in your system of care by name, and to cross reference those same people by shelters, outreach, and other services, as well as your By Name List or Priority List. In the case of assembling priority lists for coordinated entry, as David Tweedie on the OrgCode team has pointed out before, once you dig into the data to look at it by people that touch your system rather than people on your list, you will quickly see that there are a number of people in your shelters or served by outreach that have not been assessed and therefore are unlikely to end up on a priority list for housing. Who you are serving and who you are housing may be two different groups.

But back to having my mind blown with shelter data.

In Community A - a city of over 500,000 people - as is the case of many communities, they ran their shelter data by shelter stays in 2017. What did they find?

Number of shelter stays 3,695
Average length of stay 12 days
Median length of stay 3 days
% people who leave before 14 days 79%
% people who stay 180+ days 0.4%

Then they ran the SAME data but by unique individuals, and a whole different picture emerged. What did it show?

Number of unique individuals with shelter stays 408
Average length of stay cumulatively 114 days
Median length of stay cumulatively 87.5 days
% people who leave before 14 days cumulatively 9%
% people who stay 180+ days cumulatively 21%

Say what? Shelter stays painted a picture we are all familiar with - a large volume of short stays. Unique individuals resulted in a completely different understanding of the data. Once you started to understand cumulative engagement the world of sheltering looked completely different.

Bewildered, I had the chance to have Community B - a city of just shy of 300,000 people - run the same type of report just to make sure Community A was not an anomaly. What did they find?

Number of shelter stays 1,888
Average length of stay 14 days
Median length of stay 4.5 days
% people who leave before 14 days 83%
% people who stay 180+ days 0.8%

Like Community A, Community B then ran the data by unique individuals, and again a whole different picture emerged. What did it show?

Number of unique individuals with shelter stays 211
Average length of stay cumulatively 106
Median length of stay cumulatively 91.5 days
% people who leave before 14 days cumulatively 8%
% people who stay 180+ days cumulatively 26%

I am scratching my head. I want to see more data on unique shelter users versus shelter stayers. Is it coincidence that two communities in a row that I had contact with this month ran data that runs contrary to how we generally think shelters operate? Or were these legitimately outliers and the norm is something different? Would love to know what happens in your community when you run your data by unique individuals...let me know. We may be on to something here.

About Iain De Jong

Leader. Edutainer. Coach. Consultant. Professor. Researcher. Blogger. Do-gooder. Potty mouth. Positive disruptor. Relentless advocate for social justice. Comedian. Dad. Minimalist. Recovering musician. Canadian citizen. International jetsetter. Living life in jeans and a t-shirt. Trying really hard to end homelessness in developed countries around the world, expand harm reduction practices, make housing happen, and reform the justice system. Driven by change, fuelled by passion. Winner of a shit ton of prestigious awards, none of which matter unless change happens in how we think about vulnerability, marginality, and inclusion.


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