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Primary Submission Category: Health care/services
Bridging data silos to understand homelessness & healthcare
Authors: Paulina Kaiser, Andy Hertel, Stephanie Foster, Truman Ricks, Emily Chang, Carson Mowrer, Cory Hackstedt, Chris Campbell, Barbara Hudson-Hanley, Mark Edwards,
Presenting Author: Paulina Kaiser*
Understanding the relationship between homelessness and health requires integrating information across housing and healthcare systems, yet these data are typically siloed. As a multiagency collaborative representing a 3-county region in Oregon, we merged electronic medical records from two healthcare systems with data from the Homeless Management Information System (HMIS) that captures housing support services (e.g. emergency shelter, rapid rehousing, and homelessness prevention programs) provided by the region’s state-designated Community Action Agency. We used privacy-preserving record linkage to match individuals without the need to share identifying information. The matched dataset included 5,433 individuals who received housing support services and had one or more healthcare encounters in 2023–2024. We examined emergency department (ED) utilization relative to receipt of housing services; among those that stayed at an emergency shelter, adjusted Poisson models showed that ED visits increased in the six months following the first emergency shelter stay compared to the six months prior (RR=1.25, p<0.001). However, ED utilization was higher in the 1-2 months preceding the initial shelter stay compared to previous months, suggesting the possibility of destabilizing events that elevated both ED use and the need for shelter. These patterns highlight challenges in estimating the causal impact of housing services using simple pre/post comparisons, given likely confounding events around the time of service entry. Pending analyses will assess total cost of care before and after service receipt and examine reasons for ED visits. This work advances understanding of healthcare utilization across housing statuses and program types, informing opportunities to refine service models and strengthen cross‑sector coordination.