YourPath Data Point: Unhoused populations
We collect an incredible amount of data here at YourPath, and with the help of Yunyang Zhong, a student at Macalester University, we have been able to analyze our data at a level that was previously impossible.
As we continue to leverage our data collection and analysis efforts to improve care not only in our corner of the system — but across populations at large — it will be vital to identify data points which might help to drive systemic improvements. We will be posting periodically about singular data points and what we might learn from them.
housing status and perception of need
While estimates of the rate of substance use disorders among the unhoused population vary considerably, there is widespread agreement that the rates are far higher than in the general population. Having a substance use disorder increases one’s chances of housing instability, and vice versa. Furthermore, housing instability can create significant barriers to accessing treatment, treatment retention, overall health and a host of other issues related to social determinants.
We were curious as to how many of the clients that came to us for help were unhoused:
We use these data to guide our care — the most important intervention being helping individuals find stable housing. This might mean recovery-based housing, Housing First programs, inpatient treatment with stable housing afterwards, connection with Coordinated Entry, or other options. It’s not enough to treat substance use — we must address as many impediments to stability as possible, especially those related to persistent gaps in social determinants of health. Housing is the perhaps the most major — and immediately actionable — determinant.
Other data points that we are collecting relate to a client’s perception of what would be most helpful to them in their recovery. This is significantly actionable and is a core of our person-centered approach. For far too long substance use care has been dominated by the “clinician knows best” ideology, also framed to the client as “your best thinking got you here.” We know this paternalistic approach doesn’t work, and that the client typically (if not always) has the best insight into their particular situation.
We were curious to see how our clients’ perception of what would be helpful for their recovery is related to their housing status. Here’s the breakdown:
This isn’t terribly surprising, but the specifics of these data are very actionable. It makes sense that the client’s perceived needs for housing, residential treatment, employment and medical care would be roughly double for those who are unhoused.
As we help our clients access resources and navigate systems of care, it is imperative that we place their desires for care above any of our preconceived notions of what that care should look like.
So what’s next? All of the above is simply baseline data, collected at the first point of contact. As we move further into a longitudinal care and data collection model, we can starting asking questions like: “How does improving a client’s housing situation relate to their perception of need across the social determinants?” or “How does improving a client’s housing situation relate to emergency room visits?”
It is answers to these types of questions that will help us analyze outcomes and improve care. For everyone.