Intelligent Model of Nursing Shift in Tehran University of Medical Sciences, Tehran, Iran.
Exploitation
Genetic algorithm
Hospital
Nurses
Shift
Journal
Iranian journal of public health
ISSN: 2251-6093
Titre abrégé: Iran J Public Health
Pays: Iran
ID NLM: 7505531
Informations de publication
Date de publication:
May 2022
May 2022
Historique:
received:
10
12
2020
accepted:
05
02
2021
entrez:
21
11
2022
pubmed:
22
11
2022
medline:
22
11
2022
Statut:
ppublish
Résumé
Nurses play a key role in increasing the efficiency of healthcare systems. Given the 24-hour performance of hospitals and the small number of nurses in the field of treatment, it is quintessential to re-shift them in the hospital. This study set out to achieve coherence in nursing shift planning and justice in the order of shifts in hospital. This applied and a developmental study was performed from 2019 to 2020. We used genetic algorithm to provide operational solutions and define flexible shifts and plan nurses' working hours in Yas Hospital, Tehran University of Medical Sciences Hospital, Tehran, Iran. Based on the selection of each nurse and determining the approved shifts of each ward, the possibility of appropriate planning was provided to determine the required shifts per month and to estimate the needs of each department. Using genetic algorithm and nursing shift in office automation console provides useful tools for managers at all organizational levels, according to which a good balance between the hospital's need for nurse and nurses' demands in different time periods.
Sections du résumé
Background
UNASSIGNED
Nurses play a key role in increasing the efficiency of healthcare systems. Given the 24-hour performance of hospitals and the small number of nurses in the field of treatment, it is quintessential to re-shift them in the hospital. This study set out to achieve coherence in nursing shift planning and justice in the order of shifts in hospital.
Methods
UNASSIGNED
This applied and a developmental study was performed from 2019 to 2020. We used genetic algorithm to provide operational solutions and define flexible shifts and plan nurses' working hours in Yas Hospital, Tehran University of Medical Sciences Hospital, Tehran, Iran.
Results
UNASSIGNED
Based on the selection of each nurse and determining the approved shifts of each ward, the possibility of appropriate planning was provided to determine the required shifts per month and to estimate the needs of each department.
Conclusion
UNASSIGNED
Using genetic algorithm and nursing shift in office automation console provides useful tools for managers at all organizational levels, according to which a good balance between the hospital's need for nurse and nurses' demands in different time periods.
Identifiants
pubmed: 36407749
doi: 10.18502/ijph.v51i5.9427
pii: IJPH-51-1125
pmc: PMC9643239
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1125-1133Informations de copyright
Copyright © 2022 Torabi et al. Published by Tehran University of Medical Sciences.
Déclaration de conflit d'intérêts
Conflict of interest The authors declare that there is no conflict of interest.
Références
Acta Med Iran. 2014;52(10):757-63
pubmed: 25369010
Sci Rep. 2019 Mar 15;9(1):4635
pubmed: 30874565
Aust Crit Care. 2019 Sep;32(5):391-396
pubmed: 30262179
Asian Nurs Res (Korean Soc Nurs Sci). 2020 Aug;14(3):178-187
pubmed: 32693032
Hum Resour Health. 2005 Oct 08;3:9
pubmed: 16212672
Appl Nurs Res. 2016 Nov;32:199-205
pubmed: 27969028
Clin J Oncol Nurs. 2006 Aug;10(4):465-71
pubmed: 16927899
AAOHN J. 2009 Dec;57(12):497-502; quiz 503-4
pubmed: 20043622
Int J Occup Med Environ Health. 2013 Aug;26(4):511-21
pubmed: 24057261
Int J Nurs Stud. 2015 Feb;52(2):605-34
pubmed: 25468281
Rev Esc Enferm USP. 2017;51:e03301
pubmed: 29562050
Osong Public Health Res Perspect. 2016 Feb;7(1):56-62
pubmed: 26981344