Evidence map›Paper›PMID 40762912›Full record

ArticleJAMA network open2025

Rapid Access to Emergency Medical Services Within Historically Redlined Areas.

Cherisse Berry, Joseph Obiajulu, N Clay Mann, Dustin T Duncan, Charles DiMaggio, Ashley Pfaff, Spiros Frangos, Jakka Sairamesh, Natalie Escobar, Gbenga Ogedegbe and 1 more

Erratum issuedAbstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Error in Table.JAMA network open · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Cherisse BerryDepartment of Surgery, Rutgers Health, New Jersey Medical School, Newark.
Joseph ObiajuluDepartment of Surgery, New York University Grossman School of Medicine, New York.
N Clay MannNational Emergency Medical Services Information System (NEMSIS) Technical Assistance Center (TAC) University of Utah School of Medicine, Salt Lake City.
Dustin T DuncanColumbia University Mailman School of Public Health, New York, New York.
Charles DiMaggioDepartment of Surgery, New York University Grossman School of Medicine, New York.
Ashley PfaffDepartment of Surgery, New York University Grossman School of Medicine, New York.
Spiros FrangosDepartment of Surgery, New York University Grossman School of Medicine, New York.
Jakka SairameshCapsicoHealth, Inc, Palo Alto, California.
Natalie EscobarDepartment of Surgery, University of California, San Francisco School of Medicine, San Francisco.
Gbenga OgedegbeDepartment of Population Health, Department of Medicine, Institute for Excellence in Health Equity, New York University Grossman School of Medicine, New York.
Ran WeiUniversity of California Riverside School of Public Policy, Riverside.

Funding

Health Equity in Emergency Trauma Care: Analysis of disparities in the pre-hospital emergency trauma care systemR01MD018177 · NIMHD · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI Cherisse Danielle Berry · 2023 to 2026
$2.5M
NIMHD NIH HHS R01 MD018177
6 · The paper itself

Abstract

Importance: Inequities in rapid access to emergency medical services (EMS) represent a critical gap in prehospital care and the first system-level milestone for critically injured patients. As delays in EMS response are associated with increased mortality and known disparities within historically redlined areas are prevalent, this study sought to examine disparities in rapid access to EMS across the United States. Objective: To assess the association between historically redlined areas and rapid EMS access (defined as ≤5-minute response time) across the United States. Design, Setting, and Participants: This retrospective, cross-sectional study analyzed the geographic distribution of EMS centers in relation to 2020 US Census block groups and Home Owners' Loan Corporation (HOLC) residential security maps, classified by grades (A-D). Populations of 236 US cities with publicly available redlining data were included. Travel distance radius (5-minute drive times) was centered on population-weighted block group centroids. Redlining grades include A ("most desirable," green), B ("still desirable," blue), C ("declining," yellow), and D ("hazardous," red). Exposure: HOLC grade classification (A-D). Main Outcomes and Measures: The primary outcome was the proportion of the population with rapid EMS access. Secondary outcomes included the socioeconomic and demographic profiles of populations without rapid access. Results: Of the total US population (N = 333 036 755), 41 367 025 (12.42%) lived in cities with redlining data. Among these, 2 208 269 (5.34%) lacked rapid access to 42 472 EMS stations. Grade D areas had a higher proportion of residents without rapid EMS access compared with grade A areas (7.06% vs 4.36%; P < .001). The odds of having no rapid access to EMS in grade D areas were 1.67 (95% CI, 1.66-1.68) times higher than in grade A areas. Compared with grade A, grade D areas had a lower percentage of non-Hispanic White residents (65.21% [95% CI, 59.43%-70.99%] vs 39.36% [95% CI, 36.99%-41.73%]; P < .001), a higher percentage of non-Hispanic Black residents (10.38% [95% CI, 7.14%-13.62%] vs 27.85% [95% CI, 25.4%-30.3%]; P < .001), and greater population density (7500.72 [95% CI, 4341.26-10 660.18] persons/km2 vs 15 277.87 [95% CI, 13 281.7-17 274.04] persons/km2; P < .001). Conclusions and Relevance: In this cross-sectional study, structural disparities in rapid EMS access were associated with historically redlined areas. Strategic resource allocation and system redesign are warranted to address these inequities in prehospital emergency care.

Indexed as

Emergency Medical ServicesHealthcare DisparitiesHealth Services AccessibilityCross-Sectional StudiesFemaleHumansMaleRetrospective StudiesUnited States

Identifiers

PMID40762912
PMCPMC12326277

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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.