Evidence map›Paper›PMID 42005837›Full record

ReviewAEM education and training2026

Bringing Medical Care to the Streets: Lessons Learned in Launching a Street Medicine Outreach.

Christine Shaw, Hanin Ali, Chase Palisch, Catherine Weaver, Erin F Shufflebarger

Abstract readReview
In one paragraph

Review in AEM education and training, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Christine ShawDepartment of Emergency Medicine The University of Alabama at Birmingham Birmingham Alabama USA.ORCID https://orcid.org/0009-0002-1702-532X
Hanin AliAlix School of Medicine The Mayo Clinic Rochester Minnesota USA.
Chase PalischVanderbilt University Nashville Tennessee USA.
Catherine WeaverUniversity of California, Los Angeles Los Angeles California USA.
Erin F ShufflebargerDepartment of Emergency Medicine The University of Alabama at Birmingham Birmingham Alabama USA.ORCID https://orcid.org/0000-0003-0067-4788

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Street Medicine, where healthcare is provided in non-traditional settings, provides care to people experiencing homelessness (PEH). Street medicine has been shown to improve patients' health and decrease Emergency Department visits, making it a cost effective way to provide medical care to PEH. Methods: This paper is based on the SAEM25 didactic session as conducted in Philadelphia, where a panel of providers who are directly involved in street medicine clinics shared their experiences and perspectives on the various designs in practice. These topics included key logistical challenges and solutions, barriers to care and trust building, strategies for fostering sustainable partnerships with community organizations, and options for medical student or resident involvement. Results: The design and unique approach of four different universities across the country was compared and contrasted by a panel of experts, all with experiences working directly with PEH. There are similarly identified barriers to providing care to PEH including location and transportation, financial and food insecurity, and trust between the community and the healthcare system. Conclusion: There are multiple options that exist to provide a framework to create a clinic to support populations of PEH.

Indexed as

health serviceshomelessnesshousing insecuritysocial emergency medicinestreet medicine

Identifiers

PMID42005837
PMCPMC13083216

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.