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A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters

Hospitals are the first point of contact for people in the face of disasters that interfere with the daily functioning of life and endanger health and social life. All preparations should be made considering the worst possible conditions and the provided service should continue without interruption....

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Detalles Bibliográficos
Autores principales: Saner, Halit Serdar, Yucesan, Melih, Gul, Muhammet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8593641/
https://www.ncbi.nlm.nih.gov/pubmed/34803219
http://dx.doi.org/10.1007/s11069-021-05108-7
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author Saner, Halit Serdar
Yucesan, Melih
Gul, Muhammet
author_facet Saner, Halit Serdar
Yucesan, Melih
Gul, Muhammet
author_sort Saner, Halit Serdar
collection PubMed
description Hospitals are the first point of contact for people in the face of disasters that interfere with the daily functioning of life and endanger health and social life. All preparations should be made considering the worst possible conditions and the provided service should continue without interruption. In this study, a multi-criteria decision-making model was developed to evaluate disaster preparedness of hospitals. This decision model includes Bayesian best–worst method (BBWM), the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and technique for order preference by similarity to ideal solution (TOPSIS) methods. With the proposed decision model, six main criteria and 34 sub-criteria related to disaster preparedness of hospitals were considered. The criteria and sub-criteria evaluated in pairwise comparison manner by the experts were weighted with BBWM. These weight values and the data obtained from the six Turkish hospitals were combined to provide inputs for VIKOR and TOPSIS. In addition, a comparative study and sensitivity analysis were carried out using weight vectors obtained by different tools. BBWM application results show that the “Personnel” criterion was determined as the most important criterion with an importance value of 26%. This criterion is followed by “Equipment” with 25%, “Transportation” with 14%, “Hospital building” and “Communication” with 12%, and “Flexibility” with 11%. Hospital-2 was determined as the most prepared hospital for disasters as a result of VIKOR application. The VIKOR Q value of this hospital was obtained as 0.000. According to the results of the comparative study, Hospital-2 was determined as the most disaster-ready hospital in all six different scenarios. This hospital is followed by Hospital-4 (Q = 0.5661) and Hospital-5 (Q = 0.7464). The remaining rankings were Hospital-6, Hospital-3 and Hospital-1. The solidity of the results was checked with TOPSIS. Based on TOPSIS application results, Hospital-2 was again found the most-ready hospital. The usage of BBWM in this study enabled the expert group’s views to be combined without loss of information and to determine the criteria and sub-criteria weights with less pairwise comparisons in a probabilistic perspective. Via the “Credal ranking”, which is the contribution of BBWM to the literature, the interpretation of the hierarchy between each criterion has been performed more precisely.
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spelling pubmed-85936412021-11-16 A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters Saner, Halit Serdar Yucesan, Melih Gul, Muhammet Nat Hazards (Dordr) Original Paper Hospitals are the first point of contact for people in the face of disasters that interfere with the daily functioning of life and endanger health and social life. All preparations should be made considering the worst possible conditions and the provided service should continue without interruption. In this study, a multi-criteria decision-making model was developed to evaluate disaster preparedness of hospitals. This decision model includes Bayesian best–worst method (BBWM), the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and technique for order preference by similarity to ideal solution (TOPSIS) methods. With the proposed decision model, six main criteria and 34 sub-criteria related to disaster preparedness of hospitals were considered. The criteria and sub-criteria evaluated in pairwise comparison manner by the experts were weighted with BBWM. These weight values and the data obtained from the six Turkish hospitals were combined to provide inputs for VIKOR and TOPSIS. In addition, a comparative study and sensitivity analysis were carried out using weight vectors obtained by different tools. BBWM application results show that the “Personnel” criterion was determined as the most important criterion with an importance value of 26%. This criterion is followed by “Equipment” with 25%, “Transportation” with 14%, “Hospital building” and “Communication” with 12%, and “Flexibility” with 11%. Hospital-2 was determined as the most prepared hospital for disasters as a result of VIKOR application. The VIKOR Q value of this hospital was obtained as 0.000. According to the results of the comparative study, Hospital-2 was determined as the most disaster-ready hospital in all six different scenarios. This hospital is followed by Hospital-4 (Q = 0.5661) and Hospital-5 (Q = 0.7464). The remaining rankings were Hospital-6, Hospital-3 and Hospital-1. The solidity of the results was checked with TOPSIS. Based on TOPSIS application results, Hospital-2 was again found the most-ready hospital. The usage of BBWM in this study enabled the expert group’s views to be combined without loss of information and to determine the criteria and sub-criteria weights with less pairwise comparisons in a probabilistic perspective. Via the “Credal ranking”, which is the contribution of BBWM to the literature, the interpretation of the hierarchy between each criterion has been performed more precisely. Springer Netherlands 2021-11-16 2022 /pmc/articles/PMC8593641/ /pubmed/34803219 http://dx.doi.org/10.1007/s11069-021-05108-7 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Saner, Halit Serdar
Yucesan, Melih
Gul, Muhammet
A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
title A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
title_full A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
title_fullStr A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
title_full_unstemmed A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
title_short A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
title_sort bayesian bwm and vikor-based model for assessing hospital preparedness in the face of disasters
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8593641/
https://www.ncbi.nlm.nih.gov/pubmed/34803219
http://dx.doi.org/10.1007/s11069-021-05108-7
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