Evidence map›Paper›PMID 39569088›Full record

ArticlePRiMER (Leawood, Kan.)2024

A Student-Led Patient Navigation Program: Assessing the Goals of Individuals Experiencing Homelessness.

Shannon Teaw, Drupad Annapureddy, Ethan Wang, Shelley Speed, Nora Gimpel

Abstract read
In one paragraph

Article in PRiMER (Leawood, Kan.), 2024. 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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0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Shannon TeawUniversity of Texas Southwestern Medical School, Dallas, TX.
Drupad AnnapureddyUniversity of Texas Southwestern Medical School, Dallas, TX.
Ethan WangUniversity of Texas Southwestern Medical School, Dallas, TX.
Shelley SpeedDepartment of Family and Community Medicine, University of Texas Southwestern Medical Center, Dallas, TX.
Nora GimpelDepartment of Family and Community Medicine, University of Texas Southwestern Medical Center, Dallas, TX.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Homeless populations face higher barriers to health care access. A student-led patient navigation program (PNP) was established pairing groups of trained medical students, who serve as patient navigators, together with an individual experiencing homelessness (IEH) to develop goals tailored to each IEH's needs. The purpose of this study was to collect data pertaining to the goals of IEH centered on the social determinants of health (SDH) domains. Methods: IEH were invited to voluntarily participate in the program and patient navigators met with IEH weekly for a 12-week period to guide and connect patients with resources to accomplish the patients' goals. Manual review of each IEH's goals was performed and categorized according to SDH domains and further categorized into subdomains using qualitative content analysis. Results: A total of 86 goals were categorized for 19 participants, with an average of 4.5 goals per IEH. The most common goals were related to "economic stability" (n=34), followed by "health care access" (n=25), "neighborhood and built environment" (n=11), "social and community context" (n=10), and lastly "education access" (n=6). The most common goals based on subcategories were related to "housing" (n=13) and "employment and career development" (n=10). Conclusion: "Economic stability" and "health care access-related" goals were the most common among IEH participants. Subcategorization analyses revealed that "obtaining identification documentation (ID)" was a common goal that did not easily fit into the Centers for Disease Control and Prevention's (CDC)-defined categories but provided insight into necessary services. Characterizing the goals of IEH permits the development of targeted resources to assist IEH and bridge health care accessibility gaps.

Identifiers

PMID39569088
PMCPMC11578398

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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.