Evidence map›Paper›PMID 40063600›Full record

ArticlePloS one2025

Change in address in electronic health records as an early marker of homelessness.

Janet Song, Yu Deng, Yuyang Yang, Lacey Gleason, Abel Kho

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Janet SongFeinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.ORCID 0000-0003-3379-1104
Yu DengFeinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.
Yuyang YangFeinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.
Lacey GleasonFeinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.
Abel KhoFeinberg School of Medicine, Northwestern University, Chicago, Illinois, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHousing stability is a key health determinant and there is a need for early screening for instability with existing electronic health record (EHR) data to improve health outcomes. We aim to establish recorded address changes as a screening variable for housing instability and homelessness and to attempt to define the threshold of high churn.

methodsOur study is a single-center cross-sectional study of EHR data (2018-2024) conducted at a US academic center with eleven sites across Chicago. We include patients 18 years or older with at least three hospital encounters over three different years. We define address churn as the number of address changes recorded in the EHR corrected to three-year intervals. We compare demographic and clinical characteristics of individuals with varying address churn with the student T-test to look at distribution of address churn for patients with and without record of homelessness, ANOVA to evaluate the distribution of ages for different levels of churn, and the chi-square test to evaluate for association between churn and clinical diagnoses. We perform multivariable logistic regression to measure the association between people with a record of homelessness and address changes.

resultsThe study includes 1,068,311 patients with 756,222 having zero address changes, 156,911 having one address change, 137,491 with two address changes, 9,558 with three address changes, and 8,129 with four or more address changes. People with no record of homelessness in the EHR have mean address changes of 0.6 (SD 0.7) whereas people with record of homelessness have mean address changes of 1.8 (SD 1.3). Diagnostic profiles of the varying address change groups show increased prevalence of psychiatric diagnoses (65.2% in the 4 or more-address change group) compared to lower address change (27.7% in the 0-address change group). Address churn is significantly associated with homelessness with an odds ratio (OR) of 1.44 (95% CI =  [1.42-1.47], P < 0.001).

conclusionOur results support a role for residential address churn in screening for housing instability in healthcare systems and reinforce the association between psychiatric disorders and housing instability. Our findings can help public health policy makers in targeting vulnerable populations at risk of homelessness with multiple health comorbidities for housing interventions.

Indexed as

Electronic Health RecordsIll-Housed PersonsAdultAgedChicagoCross-Sectional StudiesFemaleHousingHumansMaleMiddle Aged

Identifiers

PMID40063600
PMCPMC11892818

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.