ArticleThe western journal of emergency medicine2018
Use of Fine-scale Geospatial Units and Population Data to Evaluate Access to Emergency Care.
Article in The western journal of emergency medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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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.
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Who cites it
4 citing papers in PubMed.
- Global and local drivers of Echinococcus multilocularis infection in the western Balkan region.Scientific reports · 2023Article
- Access to Pulmonary Rehabilitation among Medicare Beneficiaries with Chronic Obstructive Pulmonary Disease.Annals of the American Thoracic Society · 2023Article
- Spatial accessibility of emergency medical services in Chongqing, Southwest China.Frontiers in public health · 2022Article
- Efficiency of fine scale and spatial regression in modelling associations between healthcare service spatial accessibility and their utilization.International journal of health geographics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionTime to facility is a crucial element in emergency medicine (EM). Fine-scale geospatial units such as census block groups (CBG) and publicly available population datasets offer a low-cost and accurate approach to modeling geographic access to and utilization of emergency departments (ED). These methods are relevant to the emergency physician in evaluating patient utilization patterns, emergency medical services protocols, and opportunities for improved patient outcomes and cost utilization. We describe the practical application of geographic information system (GIS) and fine-scale analysis for EM using Ohio ED access as a case study.
methodsOhio ED locations (n=198), CBGs (n=9,238) and 2015 United States Census five-year American Community Survey (ACS) socioeconomic data were collected July-August 2016. We estimated drive time and distance between population-weighted CBGs and nearest ED using ArcGIS and 2010 CBG shapefiles. We examined drive times vs. ACS characteristics using multinomial regression and mapping.
resultsWe categorized CBGs by centroid-ED travel time in minutes: <10 (73.4%; n=6,774), 10-30 (25.1%; n=2,315), and >30 (1.5%; n=141). CBGs with increased median age, Hispanic and non-Hispanic Black population, and college graduation rates had significantly decreased travel time. CBGs with increased low-income populations (adjusted odds ratio [AOR] [1.03], 95% confidence interval [CI] [1.01-1.04]) and vacant housing (AOR [1.06], 95% CI [1.05-1.08]) had increased odds of >30 minute travel time.
conclusionUse of fine-scale geographic analysis and population data can be used to evaluate geographic accessibility and utilization of EDs. Methods described offer guidance to approaching questions of geographic accessibility and have numerous ED and pre-hospital applications.
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