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Using publicly available flight data to analyze health disparities in aeromedical retrieval

OBJECTIVES: Specialist healthcare cannot be provided in all locations. Helicopters can help to reduce the inherent geographical inequity caused by long distances or difficult terrain. However, the selective use of aeromedical retrieval could lead to other forms of health disparities. The aim of this...

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Autores principales: Moore, Dylana, Crowley, Brandon M., McCarthy, Sean, Smedley, W. Andrew, Griffin, Russell L., Stephens, Shannon W., Kerby, Jeffrey D., Jansen, Jan O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493491/
https://www.ncbi.nlm.nih.gov/pubmed/33000070
http://dx.doi.org/10.1002/emp2.12121
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author Moore, Dylana
Crowley, Brandon M.
McCarthy, Sean
Smedley, W. Andrew
Griffin, Russell L.
Stephens, Shannon W.
Kerby, Jeffrey D.
Jansen, Jan O.
author_facet Moore, Dylana
Crowley, Brandon M.
McCarthy, Sean
Smedley, W. Andrew
Griffin, Russell L.
Stephens, Shannon W.
Kerby, Jeffrey D.
Jansen, Jan O.
author_sort Moore, Dylana
collection PubMed
description OBJECTIVES: Specialist healthcare cannot be provided in all locations. Helicopters can help to reduce the inherent geographical inequity caused by long distances or difficult terrain. However, the selective use of aeromedical retrieval could lead to other forms of health disparities. The aim of this project was to evaluate such inequities in access to helicopter transport. METHODS: This was a geospatial analysis of publicly available flight tracking data for 18 emergency medical helicopters in the state of Alabama for a 90‐day period between March 2019 and June 2019. Data are presented as the number of incidents attended per population, by population (total, insured, and uninsured), as funnel plots, by county. This method allows the identification of positive and negative outliers. RESULTS: We identified 672 likely scene retrieval flights. Twelve counties were probable (outside of 99% confidence interval [CI]) high outliers (more helicopter retrievals than expected), and 4 were possible (outside of 95% CI) high outliers. There were 5 possible low outliers (fewer helicopter retrievals than expected) and 6 probable low outliers. Analysis by insurance status revealed similar results. However, there was no easily discernible geographic pattern to this variability. CONCLUSION: There is considerable geographical variability in the number of helicopter retrievals, with no easily discernable pattern. Some of this variability may be due to differences in injury epidemiology, but others may be due to case selection. However, the present data are insufficient to come to firm conclusions, and additional study is warranted.
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spelling pubmed-74934912020-09-29 Using publicly available flight data to analyze health disparities in aeromedical retrieval Moore, Dylana Crowley, Brandon M. McCarthy, Sean Smedley, W. Andrew Griffin, Russell L. Stephens, Shannon W. Kerby, Jeffrey D. Jansen, Jan O. J Am Coll Emerg Physicians Open Emergency Medical Services OBJECTIVES: Specialist healthcare cannot be provided in all locations. Helicopters can help to reduce the inherent geographical inequity caused by long distances or difficult terrain. However, the selective use of aeromedical retrieval could lead to other forms of health disparities. The aim of this project was to evaluate such inequities in access to helicopter transport. METHODS: This was a geospatial analysis of publicly available flight tracking data for 18 emergency medical helicopters in the state of Alabama for a 90‐day period between March 2019 and June 2019. Data are presented as the number of incidents attended per population, by population (total, insured, and uninsured), as funnel plots, by county. This method allows the identification of positive and negative outliers. RESULTS: We identified 672 likely scene retrieval flights. Twelve counties were probable (outside of 99% confidence interval [CI]) high outliers (more helicopter retrievals than expected), and 4 were possible (outside of 95% CI) high outliers. There were 5 possible low outliers (fewer helicopter retrievals than expected) and 6 probable low outliers. Analysis by insurance status revealed similar results. However, there was no easily discernible geographic pattern to this variability. CONCLUSION: There is considerable geographical variability in the number of helicopter retrievals, with no easily discernable pattern. Some of this variability may be due to differences in injury epidemiology, but others may be due to case selection. However, the present data are insufficient to come to firm conclusions, and additional study is warranted. John Wiley and Sons Inc. 2020-06-09 /pmc/articles/PMC7493491/ /pubmed/33000070 http://dx.doi.org/10.1002/emp2.12121 Text en © 2020 The Authors. JACEP Open published by Wiley Periodicals LLC on behalf of the American College of Emergency Physicians. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Emergency Medical Services
Moore, Dylana
Crowley, Brandon M.
McCarthy, Sean
Smedley, W. Andrew
Griffin, Russell L.
Stephens, Shannon W.
Kerby, Jeffrey D.
Jansen, Jan O.
Using publicly available flight data to analyze health disparities in aeromedical retrieval
title Using publicly available flight data to analyze health disparities in aeromedical retrieval
title_full Using publicly available flight data to analyze health disparities in aeromedical retrieval
title_fullStr Using publicly available flight data to analyze health disparities in aeromedical retrieval
title_full_unstemmed Using publicly available flight data to analyze health disparities in aeromedical retrieval
title_short Using publicly available flight data to analyze health disparities in aeromedical retrieval
title_sort using publicly available flight data to analyze health disparities in aeromedical retrieval
topic Emergency Medical Services
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7493491/
https://www.ncbi.nlm.nih.gov/pubmed/33000070
http://dx.doi.org/10.1002/emp2.12121
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