Cargando…

Overcrowding analysis in emergency department through indexes: a single center study

INTRODUCTION: Overcrowding in the Emergency Department (ED) is one of the major issues that must be addressed in order to improve the services provided in emergency circumstances and to optimize their quality. As a result, in order to help the patients and professionals engaged, hospital organizatio...

Descripción completa

Detalles Bibliográficos
Autores principales: Colella, Ylenia, Di Laura, Danilo, Borrelli, Anna, Triassi, Maria, Amato, Francesco, Improta, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673888/
https://www.ncbi.nlm.nih.gov/pubmed/36401158
http://dx.doi.org/10.1186/s12873-022-00735-0
_version_ 1784833044293615616
author Colella, Ylenia
Di Laura, Danilo
Borrelli, Anna
Triassi, Maria
Amato, Francesco
Improta, Giovanni
author_facet Colella, Ylenia
Di Laura, Danilo
Borrelli, Anna
Triassi, Maria
Amato, Francesco
Improta, Giovanni
author_sort Colella, Ylenia
collection PubMed
description INTRODUCTION: Overcrowding in the Emergency Department (ED) is one of the major issues that must be addressed in order to improve the services provided in emergency circumstances and to optimize their quality. As a result, in order to help the patients and professionals engaged, hospital organizations must implement remedial and preventative measures. Overcrowding has a number of consequences, including inadequate treatment and longer hospital stays; as a result, mortality and the average duration of stay in critical care units both rise. In the literature, a number of indicators have been used to measure ED congestion. EDWIN, NEDOCS and READI scales are considered the most efficient ones, each of which is based on different parameters regarding the patient management in the ED. METHODS: In this work, EDWIN Index and NEDOCS Index have been calculated every hour for a month period from February 9th to March 9th, 2020 and for a month period from March 10th to April 9th, 2020. The choice of the period is related to the date of the establishment of the lockdown in Italy due to the spread of Coronavirus; in fact on 9 March 2020 the Italian government issued the first decree regarding the urgent provisions in relation to the COVID-19 emergency. Besides, the Pearson correlation coefficient has been used to evaluate how much the EDWIN and NEDOCS indexes are linearly dependent. RESULTS: EDWIN index follows a trend consistent with the situation of the first lockdown period in Italy, defined by extreme limitations imposed by Covid-19 pandemic. The 8:00–20:00 time frame was the most congested, with peak values between 8:00 and 12:00. on the contrary, in NEDOCS index doesn’t show a trend similar to the EDWIN one, resulting less reliable. The Pearson correlation coefficient between the two scales is 0,317. CONCLUSION: In this study, the EDWIN Index and the NEDOCS Index were compared and correlated in order to assess their efficacy, applying them to the case study of the Emergency Department of “San Giovanni di Dio e Ruggi d’Aragona” University Hospital during the Covid-19 pandemic. The EDWIN scale turned out to be the most realistic model in relation to the actual crowding of the ED subject of our study. Besides, the two scales didn’t show a significant correlation value.
format Online
Article
Text
id pubmed-9673888
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-96738882022-11-18 Overcrowding analysis in emergency department through indexes: a single center study Colella, Ylenia Di Laura, Danilo Borrelli, Anna Triassi, Maria Amato, Francesco Improta, Giovanni BMC Emerg Med Research INTRODUCTION: Overcrowding in the Emergency Department (ED) is one of the major issues that must be addressed in order to improve the services provided in emergency circumstances and to optimize their quality. As a result, in order to help the patients and professionals engaged, hospital organizations must implement remedial and preventative measures. Overcrowding has a number of consequences, including inadequate treatment and longer hospital stays; as a result, mortality and the average duration of stay in critical care units both rise. In the literature, a number of indicators have been used to measure ED congestion. EDWIN, NEDOCS and READI scales are considered the most efficient ones, each of which is based on different parameters regarding the patient management in the ED. METHODS: In this work, EDWIN Index and NEDOCS Index have been calculated every hour for a month period from February 9th to March 9th, 2020 and for a month period from March 10th to April 9th, 2020. The choice of the period is related to the date of the establishment of the lockdown in Italy due to the spread of Coronavirus; in fact on 9 March 2020 the Italian government issued the first decree regarding the urgent provisions in relation to the COVID-19 emergency. Besides, the Pearson correlation coefficient has been used to evaluate how much the EDWIN and NEDOCS indexes are linearly dependent. RESULTS: EDWIN index follows a trend consistent with the situation of the first lockdown period in Italy, defined by extreme limitations imposed by Covid-19 pandemic. The 8:00–20:00 time frame was the most congested, with peak values between 8:00 and 12:00. on the contrary, in NEDOCS index doesn’t show a trend similar to the EDWIN one, resulting less reliable. The Pearson correlation coefficient between the two scales is 0,317. CONCLUSION: In this study, the EDWIN Index and the NEDOCS Index were compared and correlated in order to assess their efficacy, applying them to the case study of the Emergency Department of “San Giovanni di Dio e Ruggi d’Aragona” University Hospital during the Covid-19 pandemic. The EDWIN scale turned out to be the most realistic model in relation to the actual crowding of the ED subject of our study. Besides, the two scales didn’t show a significant correlation value. BioMed Central 2022-11-18 /pmc/articles/PMC9673888/ /pubmed/36401158 http://dx.doi.org/10.1186/s12873-022-00735-0 Text en © The Author(s) 2022 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
Colella, Ylenia
Di Laura, Danilo
Borrelli, Anna
Triassi, Maria
Amato, Francesco
Improta, Giovanni
Overcrowding analysis in emergency department through indexes: a single center study
title Overcrowding analysis in emergency department through indexes: a single center study
title_full Overcrowding analysis in emergency department through indexes: a single center study
title_fullStr Overcrowding analysis in emergency department through indexes: a single center study
title_full_unstemmed Overcrowding analysis in emergency department through indexes: a single center study
title_short Overcrowding analysis in emergency department through indexes: a single center study
title_sort overcrowding analysis in emergency department through indexes: a single center study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673888/
https://www.ncbi.nlm.nih.gov/pubmed/36401158
http://dx.doi.org/10.1186/s12873-022-00735-0
work_keys_str_mv AT colellaylenia overcrowdinganalysisinemergencydepartmentthroughindexesasinglecenterstudy
AT dilauradanilo overcrowdinganalysisinemergencydepartmentthroughindexesasinglecenterstudy
AT borrellianna overcrowdinganalysisinemergencydepartmentthroughindexesasinglecenterstudy
AT triassimaria overcrowdinganalysisinemergencydepartmentthroughindexesasinglecenterstudy
AT amatofrancesco overcrowdinganalysisinemergencydepartmentthroughindexesasinglecenterstudy
AT improtagiovanni overcrowdinganalysisinemergencydepartmentthroughindexesasinglecenterstudy