Evidence map›Paper›PMID 35036317›Full record

ArticleJournal of transport & health2022

A multicriteria decision analysis framework to measure equitable healthcare access during COVID-19.

Avipsa Roy, Bandana Kar

Abstract read
In one paragraph

Article in Journal of transport & health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
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  5. Article
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

2 authors.

Avipsa RoyDepartment of Urban Planning and Public Policy, University of California, Irvine, CA, USA.
Bandana KarBuilt Environment Characterization Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ongoing novel coronavirus (COVID-19) pandemic has highlighted the need for individuals to have easy access to healthcare facilities for treatment as well as vaccinations. The surge in COVID-19 hospitalizations during 2020 also underscored the fact that accessibility to nearby hospitals for testing, treatment and vaccination sites is crucial for patients with fever or respiratory symptoms. Although necessary, quantifying healthcare access is challenging as it depends on a complex interaction between underlying socioeconomic and physical factors. In this case study, we deployed a Multi Criteria Decision Analysis (MCDA) approach to uncover the barriers and their effect on healthcare access. Using a least cost path (LCP) analysis we quantified the costs associated with healthcare access from each census block group in the Los Angeles metropolitan area (LA Metro) to the nearest hospital. Social vulnerability reported by the Centers for Disease Control and Prevention (CDC), the daily number of COVID-19 cases from the Los Angeles open data portal and built environment characteristics (slope of the street, car ownership, population density distribution, walkability, traffic collision density, and speed limit) were used to quantify overall accessibility index for the entire study area. Our results showed that the census block groups with a social vulnerability index above 0.75 (high vulnerability) had low accessibility owing to the higher cost of access to nearby hospitals. These areas were also coincident with the hotspots for COVID-19 cases and deaths which highlighted the inequitable exposure of socially disadvantaged populations to COVID-19 infections and how the pandemic impacts were exacerbated by the synergistic effect of socioeconomic status and built environment characteristics of the locations where the disadvantaged populations resided. The framework proposed herein could be adapted to geo-target testing/vaccination sites and improve accessibility to healthcare facilities in general and more specifically among the socially vulnerable populations residing in urban areas to reduce their overall health risks during future pandemic outbreaks.

Indexed as

2SFCA, Two-step Floating CatchmentCDC, Centers for Disease Control and PreventionCOVID-19Healthcare accessibilityLADOT, Los Angeles Department of TransportationLA, Los AngelesLA Metro, Los Angeles Metropolitan AreaLCP, Least Cost PathLeast cost pathMCDAMCDA, Multi Criteria Decision AnalysisSocial vulnerabilitySVI, Social Vulnerability IndexWHO, World Health Organization

Identifiers

PMID35036317
PMCPMC8743600

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.