Evidence map›Paper›PMID 39285073›Full record

ArticleJournal of general internal medicine2024

Improving Identification of Patients Experiencing Homelessness in the Electronic Health Record: A Curated Registry Approach.

Sarah A Stella, Rebecca Hanratty, Arthur J Davidson, Laura J Podewils, Laura Elliott, Amy Keith, Rachel Everhart

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sarah A StellaDepartment of Medicine, Denver Health, Denver, CO, USA. sarah.stella@dhha.org.ORCID 0000-0002-7071-8910
Rebecca HanrattyDepartment of Medicine, University of Colorado Anschutz Medical Campus School of Medicine, Aurora, CO, USA.
Arthur J DavidsonColorado School of Public Health, Aurora, CO, USA.
Laura J PodewilsOffice of Research, Denver Health, Denver, CO, USA.
Laura ElliottAmbulatory Care Services, Denver Health, Denver, CO, USA.
Amy KeithOffice of Research, Denver Health, Denver, CO, USA.
Rachel EverhartDepartment of Medicine, University of Colorado Anschutz Medical Campus School of Medicine, Aurora, CO, USA.

Funding

Data Analytics to Support the Alignment of High Risk Adult Programs & ServicesR18HS027389 · AHRQ · DENVER HEALTH AND HOSPITAL AUTHORITY · PI EVERHART, RACHEL, HANRATTY, REBECCA · 2019 to 2021
$1.9M
AHRQ HHS R18 HS027389AHRQ HHS R18HS027389
6 · The paper itself

Abstract

backgroundIdentification of persons experiencing homelessness (PEH) within healthcare systems is critical to facilitate patient and population-level interventions to address health inequities.

objectiveWe created an enhanced electronic health record (EHR) registry to improve identification of PEH within a safety net healthcare system.

designWe compared patients identified as experiencing homelessness in 2021, stratified by method of identification (i.e., through registration data sources versus through new EHR registry criteria). MAIN MEASURES: Sociodemographic and clinical characteristics, healthcare utilization, engagement with homeless service providers, and mortality. KEY

resultsIn total, 10,896 patients met the registry definition of a PEH; 30% more than identified through standard registration processes; 78% were identified through only one data source. Compared with those identified only through registration data, PEH identified through new registry criteria were more likely to be female (42% vs. 25%, p < 0.001), Hispanic/Latinx or Black/African American (30% versus 25% and 25% vs. 18%, p < 0.0001), and Medicaid or Medicare beneficiaries (74% vs. 67% and 16% vs.10%, respectively, p < 0.0001). New data sources also identified a higher proportion of patients: at extremes of age (16% < 18 years and 9% ≥ 65 years vs. 2% and 5%, respectively, p < 0.0001), with increased clinical risk (31% with CRG 6-9 vs. 18%, p < 0.0001), and with a mental health diagnosis (56% vs. 42%, p < 0.0001), and a lower proportion of patients with a substance use diagnosis (39% vs. 54%, p < 0.0001) or criminal justice involvement (8% vs. 15%, p < 0.0001). Newly identified patients were more likely to be engaged in primary care (OR 2.03, 95% CI 1.83-2.26) but less likely to be engaged with homeless service providers (OR 0.70, 95% CI 0.63-0.77).

conclusionsCommonly utilized methods of identifying PEH within healthcare systems may underestimate the population and introduce reporting biases. Recognizing alternate identification methods may more comprehensively and inclusively identify PEH for intervention.

Indexed as

Electronic Health RecordsIll-Housed PersonsRegistriesAdultAgedFemaleHumansMaleMiddle AgedUnited StatesYoung Adultelectronic health recordhealth equityhealth-related social needshomelessness

Identifiers

PMID39285073
PMCPMC11618276

What OpenQuestion holds

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Registered trials

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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.