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Overcrowding Management and Patient Safety: An Application of the Stabilization Model
BACKGROUND: Emergency department is among the most crowded hospital units. The function of this department considerably affects the functions of other hospital units as well as patient satisfaction. The Stabilization Model is a strategy with potential effectiveness in managing overcrowding in emerge...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737840/ https://www.ncbi.nlm.nih.gov/pubmed/33344208 http://dx.doi.org/10.4103/ijnmr.IJNMR_254_19 |
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author | Babatabar-Darzi, Hosein Jafari-Iraqi, Iman Mahmoudi, Hosein Ebadi, Abbas |
author_facet | Babatabar-Darzi, Hosein Jafari-Iraqi, Iman Mahmoudi, Hosein Ebadi, Abbas |
author_sort | Babatabar-Darzi, Hosein |
collection | PubMed |
description | BACKGROUND: Emergency department is among the most crowded hospital units. The function of this department considerably affects the functions of other hospital units as well as patient satisfaction. The Stabilization Model is a strategy with potential effectiveness in managing overcrowding in emergency department. This study aimed to determine the effects of overcrowding management based on the stabilization model on patient safety in emergency department. MATERIALS AND METHODS: This pretest-posttest quasi-experimental was conducted in 2015 in the emergency department of a teaching hospital located in Tehran, Iran. Primarily, the perceived safety of 35 patients was assessed using the Patient Safety Assessment Questionnaire. Then, an overcrowding management intervention was implemented based on the stabilization model. Finally, the perceived safety of 35 newly recruited patients was assessed after the intervention. The SPSS software (v. 16.0) was employed for data analysis through the Chi-square, the Kolmogorov-Smirnov, and the independent-sample t tests. RESULTS: The mean (SD) score of patient safety was 27.45 (8.43) in the control group and 34.45 (4.04) in the intervention group and the between-group difference was statistically significant (t(34) = 50.37, p < 0.001). The rate of patient safety increased from 65% at baseline to 82% after the intervention. CONCLUSIONS: Overcrowding management based on the stabilization model can significantly enhance patients' perceived safety. Therefore, this strategy can be used to ease emergency department overcrowding and enhance patient safety and care quality. |
format | Online Article Text |
id | pubmed-7737840 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-77378402020-12-18 Overcrowding Management and Patient Safety: An Application of the Stabilization Model Babatabar-Darzi, Hosein Jafari-Iraqi, Iman Mahmoudi, Hosein Ebadi, Abbas Iran J Nurs Midwifery Res Original Article BACKGROUND: Emergency department is among the most crowded hospital units. The function of this department considerably affects the functions of other hospital units as well as patient satisfaction. The Stabilization Model is a strategy with potential effectiveness in managing overcrowding in emergency department. This study aimed to determine the effects of overcrowding management based on the stabilization model on patient safety in emergency department. MATERIALS AND METHODS: This pretest-posttest quasi-experimental was conducted in 2015 in the emergency department of a teaching hospital located in Tehran, Iran. Primarily, the perceived safety of 35 patients was assessed using the Patient Safety Assessment Questionnaire. Then, an overcrowding management intervention was implemented based on the stabilization model. Finally, the perceived safety of 35 newly recruited patients was assessed after the intervention. The SPSS software (v. 16.0) was employed for data analysis through the Chi-square, the Kolmogorov-Smirnov, and the independent-sample t tests. RESULTS: The mean (SD) score of patient safety was 27.45 (8.43) in the control group and 34.45 (4.04) in the intervention group and the between-group difference was statistically significant (t(34) = 50.37, p < 0.001). The rate of patient safety increased from 65% at baseline to 82% after the intervention. CONCLUSIONS: Overcrowding management based on the stabilization model can significantly enhance patients' perceived safety. Therefore, this strategy can be used to ease emergency department overcrowding and enhance patient safety and care quality. Wolters Kluwer - Medknow 2020-09-01 /pmc/articles/PMC7737840/ /pubmed/33344208 http://dx.doi.org/10.4103/ijnmr.IJNMR_254_19 Text en Copyright: © 2020 Iranian Journal of Nursing and Midwifery Research http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Babatabar-Darzi, Hosein Jafari-Iraqi, Iman Mahmoudi, Hosein Ebadi, Abbas Overcrowding Management and Patient Safety: An Application of the Stabilization Model |
title | Overcrowding Management and Patient Safety: An Application of the Stabilization Model |
title_full | Overcrowding Management and Patient Safety: An Application of the Stabilization Model |
title_fullStr | Overcrowding Management and Patient Safety: An Application of the Stabilization Model |
title_full_unstemmed | Overcrowding Management and Patient Safety: An Application of the Stabilization Model |
title_short | Overcrowding Management and Patient Safety: An Application of the Stabilization Model |
title_sort | overcrowding management and patient safety: an application of the stabilization model |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737840/ https://www.ncbi.nlm.nih.gov/pubmed/33344208 http://dx.doi.org/10.4103/ijnmr.IJNMR_254_19 |
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