Cargando…
Operations management solutions to improve ED patient flows: evidence from the Italian NHS
BACKGROUND: Overcrowding occurs when the identified need for emergency services outweighs the available resources in the emergency department (ED). Literature shows that ED overcrowding impacts the overall quality of the entire hospital production system, as confirmed by the recent COVID-19 pandemic...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338603/ https://www.ncbi.nlm.nih.gov/pubmed/35908053 http://dx.doi.org/10.1186/s12913-022-08339-x |
_version_ | 1784760006219923456 |
---|---|
author | Marsilio, Marta Roldan, Eugenia Tomas Salmasi, Luca Villa, Stefano |
author_facet | Marsilio, Marta Roldan, Eugenia Tomas Salmasi, Luca Villa, Stefano |
author_sort | Marsilio, Marta |
collection | PubMed |
description | BACKGROUND: Overcrowding occurs when the identified need for emergency services outweighs the available resources in the emergency department (ED). Literature shows that ED overcrowding impacts the overall quality of the entire hospital production system, as confirmed by the recent COVID-19 pandemic. This study aims to identify the most relevant variables that cause ED overcrowding using the input-process-output model with the aim of providing managers and policy makers with useful hints for how to effectively redesign ED operations. METHODS: A mixed-method approach is used, blending qualitative inquiry with quantitative investigation in order to: i) identifying and operationalizing the main components of the model that can be addressed by hospital operation management teams and ii) testing and measuring how these components can influence ED LOS. RESULTS: With a dashboard of indicators developed following the input-process-output model, the analysis identifies the most significant variables that have an impact on ED overcrowding: the type (age and complexity) and volume of patients (input), the actual ED structural capacity (in terms of both people and technology) and the ED physician-to-nurse ratio (process), and the hospital discharging process (output). CONCLUSIONS: The present paper represents an original contribution regarding two different aspects. First, this study combines different research methodologies with the aim of capturing relevant information that by relying on just one research method, may otherwise be missed. Second, this study adopts a hospitalwide approach, adding to our understanding of ED overcrowding, which has thus far focused mainly on single aspects of ED operations. |
format | Online Article Text |
id | pubmed-9338603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93386032022-07-31 Operations management solutions to improve ED patient flows: evidence from the Italian NHS Marsilio, Marta Roldan, Eugenia Tomas Salmasi, Luca Villa, Stefano BMC Health Serv Res Research BACKGROUND: Overcrowding occurs when the identified need for emergency services outweighs the available resources in the emergency department (ED). Literature shows that ED overcrowding impacts the overall quality of the entire hospital production system, as confirmed by the recent COVID-19 pandemic. This study aims to identify the most relevant variables that cause ED overcrowding using the input-process-output model with the aim of providing managers and policy makers with useful hints for how to effectively redesign ED operations. METHODS: A mixed-method approach is used, blending qualitative inquiry with quantitative investigation in order to: i) identifying and operationalizing the main components of the model that can be addressed by hospital operation management teams and ii) testing and measuring how these components can influence ED LOS. RESULTS: With a dashboard of indicators developed following the input-process-output model, the analysis identifies the most significant variables that have an impact on ED overcrowding: the type (age and complexity) and volume of patients (input), the actual ED structural capacity (in terms of both people and technology) and the ED physician-to-nurse ratio (process), and the hospital discharging process (output). CONCLUSIONS: The present paper represents an original contribution regarding two different aspects. First, this study combines different research methodologies with the aim of capturing relevant information that by relying on just one research method, may otherwise be missed. Second, this study adopts a hospitalwide approach, adding to our understanding of ED overcrowding, which has thus far focused mainly on single aspects of ED operations. BioMed Central 2022-07-30 /pmc/articles/PMC9338603/ /pubmed/35908053 http://dx.doi.org/10.1186/s12913-022-08339-x 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 Marsilio, Marta Roldan, Eugenia Tomas Salmasi, Luca Villa, Stefano Operations management solutions to improve ED patient flows: evidence from the Italian NHS |
title | Operations management solutions to improve ED patient flows: evidence from the Italian NHS |
title_full | Operations management solutions to improve ED patient flows: evidence from the Italian NHS |
title_fullStr | Operations management solutions to improve ED patient flows: evidence from the Italian NHS |
title_full_unstemmed | Operations management solutions to improve ED patient flows: evidence from the Italian NHS |
title_short | Operations management solutions to improve ED patient flows: evidence from the Italian NHS |
title_sort | operations management solutions to improve ed patient flows: evidence from the italian nhs |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9338603/ https://www.ncbi.nlm.nih.gov/pubmed/35908053 http://dx.doi.org/10.1186/s12913-022-08339-x |
work_keys_str_mv | AT marsiliomarta operationsmanagementsolutionstoimproveedpatientflowsevidencefromtheitaliannhs AT roldaneugeniatomas operationsmanagementsolutionstoimproveedpatientflowsevidencefromtheitaliannhs AT salmasiluca operationsmanagementsolutionstoimproveedpatientflowsevidencefromtheitaliannhs AT villastefano operationsmanagementsolutionstoimproveedpatientflowsevidencefromtheitaliannhs |