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.
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http://dx.doi.org/10.1016/j.jth.2022.101331 | DOI Listing |
JAMA Cardiol
January 2025
Department of Emergency Medicine, Rush University Medical Center, Chicago, Illinois.
Importance: Lung ultrasound (LUS) aids in the diagnosis of patients with dyspnea, including those with cardiogenic pulmonary edema, but requires technical proficiency for image acquisition. Previous research has demonstrated the effectiveness of artificial intelligence (AI) in guiding novice users to acquire high-quality cardiac ultrasound images, suggesting its potential for broader use in LUS.
Objective: To evaluate the ability of AI to guide acquisition of diagnostic-quality LUS images by trained health care professionals (THCPs).
Eur Radiol Exp
January 2025
St Vincent's University Hospital, Dublin, Ireland.
Background: The large language model ChatGPT can now accept image input with the GPT4-vision (GPT4V) version. We aimed to compare the performance of GPT4V to pretrained U-Net and vision transformer (ViT) models for the identification of the progression of multiple sclerosis (MS) on magnetic resonance imaging (MRI).
Methods: Paired coregistered MR images with and without progression were provided as input to ChatGPT4V in a zero-shot experiment to identify radiologic progression.
Curr Cardiol Rep
January 2025
Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA.
Purpose Of Review: Significant inequities persist in hypertension detection and control, with minoritized populations disproportionately experiencing organ damage and premature death due to uncontrolled hypertension. Remote blood pressure monitoring combined with telehealth visits (RBPM) is proving to be an effective strategy for controlling hypertension. Yet there are challenges related to technology adoption, patient engagement and social determinants of health (SDoH), contributing to disparities in patient outcomes.
View Article and Find Full Text PDFJ Immigr Minor Health
January 2025
Department of Community Health, Tufts University School of Arts and Sciences, 574 Boston Avenue, Medford, MA, 02155, USA.
Brazilians are a rapidly growing immigrant population in the United States (U.S.), yet little is known about their mental health and access to mental healthcare.
View Article and Find Full Text PDFJ Neurol
January 2025
Department of Sustainable Health, University of Groningen, Campus Fryslân, Wirdumerdijk 34, 8911 CE, Leeuwarden, The Netherlands.
Background: Neurological disorders pose a substantial burden worldwide in healthcare and health research. eHealth has emerged as a promising field given its potential to aid research, with lower resources. With a changing eHealth landscape, identifying available tools is instrumental for informing future research.
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