Cargando…
Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis
BACKGROUND: During a 6-year period, several process changes were introduced at the emergency department (ED) to decrease crowding, such as the implementation of a general practitioner cooperative (GPC) and additional medical staff during peak hours. In this study, we assessed the effects of these pr...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930714/ https://www.ncbi.nlm.nih.gov/pubmed/36792991 http://dx.doi.org/10.1186/s12245-023-00479-z |
_version_ | 1784889089885995008 |
---|---|
author | Van Der Linden, M. Christien Van Loon-Van Gaalen, Merel Richards, John R. Van Woerden, Geesje Van Der Linden, Naomi |
author_facet | Van Der Linden, M. Christien Van Loon-Van Gaalen, Merel Richards, John R. Van Woerden, Geesje Van Der Linden, Naomi |
author_sort | Van Der Linden, M. Christien |
collection | PubMed |
description | BACKGROUND: During a 6-year period, several process changes were introduced at the emergency department (ED) to decrease crowding, such as the implementation of a general practitioner cooperative (GPC) and additional medical staff during peak hours. In this study, we assessed the effects of these process changes on three crowding measures: patients’ length of stay (LOS), the modified National ED OverCrowding Score (mNEDOCS), and exit block while taking into account changing external circumstances, such as the COVID-19 pandemic and centralization of acute care. METHODS: We determined time points of the various interventions and external circumstances and built an interrupted time-series (ITS) model per outcome measure. We analyzed changes in level and trend before and after the selected time points using ARIMA modeling, to account for autocorrelation in the outcome measures. RESULTS: Longer patients’ ED LOS was associated with more inpatient admissions and more urgent patients. The mNEDOCS decreased with the integration of the GPC and the expansion of the ED to 34 beds and increased with the closure of a neighboring ED and ICU. More exit blocks occurred when more patients with shortness of breath and more patients > 70 years of age presented to the ED. During the severe influenza wave of 2018–2019, patients’ ED LOS and the number of exit blocks increased. CONCLUSIONS: In the ongoing battle against ED crowding, it is pivotal to understand the effect of interventions, corrected for changing circumstances and patient and visit characteristics. In our ED, interventions which were associated with decreased crowding measures included the expansion of the ED with more beds and the integration of the GPC on the ED. |
format | Online Article Text |
id | pubmed-9930714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-99307142023-02-16 Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis Van Der Linden, M. Christien Van Loon-Van Gaalen, Merel Richards, John R. Van Woerden, Geesje Van Der Linden, Naomi Int J Emerg Med Research BACKGROUND: During a 6-year period, several process changes were introduced at the emergency department (ED) to decrease crowding, such as the implementation of a general practitioner cooperative (GPC) and additional medical staff during peak hours. In this study, we assessed the effects of these process changes on three crowding measures: patients’ length of stay (LOS), the modified National ED OverCrowding Score (mNEDOCS), and exit block while taking into account changing external circumstances, such as the COVID-19 pandemic and centralization of acute care. METHODS: We determined time points of the various interventions and external circumstances and built an interrupted time-series (ITS) model per outcome measure. We analyzed changes in level and trend before and after the selected time points using ARIMA modeling, to account for autocorrelation in the outcome measures. RESULTS: Longer patients’ ED LOS was associated with more inpatient admissions and more urgent patients. The mNEDOCS decreased with the integration of the GPC and the expansion of the ED to 34 beds and increased with the closure of a neighboring ED and ICU. More exit blocks occurred when more patients with shortness of breath and more patients > 70 years of age presented to the ED. During the severe influenza wave of 2018–2019, patients’ ED LOS and the number of exit blocks increased. CONCLUSIONS: In the ongoing battle against ED crowding, it is pivotal to understand the effect of interventions, corrected for changing circumstances and patient and visit characteristics. In our ED, interventions which were associated with decreased crowding measures included the expansion of the ED with more beds and the integration of the GPC on the ED. Springer Berlin Heidelberg 2023-02-15 /pmc/articles/PMC9930714/ /pubmed/36792991 http://dx.doi.org/10.1186/s12245-023-00479-z Text en © The Author(s) 2023 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 Van Der Linden, M. Christien Van Loon-Van Gaalen, Merel Richards, John R. Van Woerden, Geesje Van Der Linden, Naomi Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis |
title | Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis |
title_full | Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis |
title_fullStr | Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis |
title_full_unstemmed | Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis |
title_short | Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis |
title_sort | effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930714/ https://www.ncbi.nlm.nih.gov/pubmed/36792991 http://dx.doi.org/10.1186/s12245-023-00479-z |
work_keys_str_mv | AT vanderlindenmchristien effectsofprocesschangesonemergencydepartmentcrowdinginachangingworldaninterruptedtimeseriesanalysis AT vanloonvangaalenmerel effectsofprocesschangesonemergencydepartmentcrowdinginachangingworldaninterruptedtimeseriesanalysis AT richardsjohnr effectsofprocesschangesonemergencydepartmentcrowdinginachangingworldaninterruptedtimeseriesanalysis AT vanwoerdengeesje effectsofprocesschangesonemergencydepartmentcrowdinginachangingworldaninterruptedtimeseriesanalysis AT vanderlindennaomi effectsofprocesschangesonemergencydepartmentcrowdinginachangingworldaninterruptedtimeseriesanalysis |