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The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?

BACKGROUND: The individual factors associated to Frequent Users (FUs) in Emergency Departments are well known. However, the characteristics of their geographical distribution and how territorial specificities are associated and intertwined with ED use are limited. Investigating healthcare use and te...

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Autores principales: Hellmann, Romain, Feral-Pierssens, Anne-Laure, Michault, Alain, Casalino, Enrique, Ricard-Hibon, Agnès, Adnet, Frederic, Brun-Ney, Dominique, Bouzid, Donia, Menu, Axelle, Wargon, Mathias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447576/
https://www.ncbi.nlm.nih.gov/pubmed/34530780
http://dx.doi.org/10.1186/s12889-021-11682-z
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author Hellmann, Romain
Feral-Pierssens, Anne-Laure
Michault, Alain
Casalino, Enrique
Ricard-Hibon, Agnès
Adnet, Frederic
Brun-Ney, Dominique
Bouzid, Donia
Menu, Axelle
Wargon, Mathias
author_facet Hellmann, Romain
Feral-Pierssens, Anne-Laure
Michault, Alain
Casalino, Enrique
Ricard-Hibon, Agnès
Adnet, Frederic
Brun-Ney, Dominique
Bouzid, Donia
Menu, Axelle
Wargon, Mathias
author_sort Hellmann, Romain
collection PubMed
description BACKGROUND: The individual factors associated to Frequent Users (FUs) in Emergency Departments are well known. However, the characteristics of their geographical distribution and how territorial specificities are associated and intertwined with ED use are limited. Investigating healthcare use and territorial factors would help targeting local health policies. We aim at describing the geographical distribution of ED’s FUs within the Paris region. METHODS: We performed a retrospective analysis of all ED visits in the Paris region in 2015. Data were collected from the universal health insurance’s claims database. Frequent Users (FUs) were defined as having visited ≥3 times any ED of the region over the period. We assessed the FUs rate in each geographical unit (GU) and assessed correlations between FUs rate and socio-demographics and economic characteristics of GUs. We also performed a multidimensional analysis and a principal component analysis to identify a typology of territories to describe and target the FUs phenomenon. RESULTS: FUs accounted for 278,687 (11.7%) of the 2,382,802 patients who visited the ED, living in 232 GUs. In the region, median FUs rate in each GU was 11.0% [interquartile range: 9.5–12.5]. High FUs rate was correlated to the territorial markers of social deprivation. Three different categories of GU were identified with different profiles of healthcare providers densities. CONCLUSION: FUs rate varies between territories and is correlated to territorial markers of social deprivation. Targeted public policies should focus on disadvantaged territories.
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spelling pubmed-84475762021-09-17 The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies? Hellmann, Romain Feral-Pierssens, Anne-Laure Michault, Alain Casalino, Enrique Ricard-Hibon, Agnès Adnet, Frederic Brun-Ney, Dominique Bouzid, Donia Menu, Axelle Wargon, Mathias BMC Public Health Research Article BACKGROUND: The individual factors associated to Frequent Users (FUs) in Emergency Departments are well known. However, the characteristics of their geographical distribution and how territorial specificities are associated and intertwined with ED use are limited. Investigating healthcare use and territorial factors would help targeting local health policies. We aim at describing the geographical distribution of ED’s FUs within the Paris region. METHODS: We performed a retrospective analysis of all ED visits in the Paris region in 2015. Data were collected from the universal health insurance’s claims database. Frequent Users (FUs) were defined as having visited ≥3 times any ED of the region over the period. We assessed the FUs rate in each geographical unit (GU) and assessed correlations between FUs rate and socio-demographics and economic characteristics of GUs. We also performed a multidimensional analysis and a principal component analysis to identify a typology of territories to describe and target the FUs phenomenon. RESULTS: FUs accounted for 278,687 (11.7%) of the 2,382,802 patients who visited the ED, living in 232 GUs. In the region, median FUs rate in each GU was 11.0% [interquartile range: 9.5–12.5]. High FUs rate was correlated to the territorial markers of social deprivation. Three different categories of GU were identified with different profiles of healthcare providers densities. CONCLUSION: FUs rate varies between territories and is correlated to territorial markers of social deprivation. Targeted public policies should focus on disadvantaged territories. BioMed Central 2021-09-16 /pmc/articles/PMC8447576/ /pubmed/34530780 http://dx.doi.org/10.1186/s12889-021-11682-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Hellmann, Romain
Feral-Pierssens, Anne-Laure
Michault, Alain
Casalino, Enrique
Ricard-Hibon, Agnès
Adnet, Frederic
Brun-Ney, Dominique
Bouzid, Donia
Menu, Axelle
Wargon, Mathias
The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?
title The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?
title_full The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?
title_fullStr The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?
title_full_unstemmed The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?
title_short The analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?
title_sort analysis of the geographical distribution of emergency departments’ frequent users: a tool to prioritize public health policies?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8447576/
https://www.ncbi.nlm.nih.gov/pubmed/34530780
http://dx.doi.org/10.1186/s12889-021-11682-z
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