Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals

MakaleAçık ErişimScopus SJRQ1
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Özet

Considering the unexpected emergence of natural and man-made disasters over the world and Turkey, the importance of preparedness of hospitals, which are the first reference points for people to get healthcare services, becomes clear. Determining the level of disaster preparedness of hospitals is an important and necessary issue. This is because identifying hospitals with low level of preparedness is crucial for disaster preparedness planning. In this study, a hybrid fuzzy decision making model was proposed to evaluate the disaster preparedness of hospitals. This model was developed using fuzzy analytic hierarchy process (FAHP)-fuzzy decision making trial and evaluation laboratory (FDEMATEL)-technique for order preference by similarity to ideal solutions (TOPSIS) techniques and aimed to determine a ranking for hospital disaster preparedness. FAHP is used to determine weights of six main criteria (including hospital buildings, equipment, communication, transportation, personnel, flexibility) and a total of thirty-six sub-criteria regarding disaster preparedness. At the same time, FDEMATEL is applied to uncover the interdependence between criteria and sub-criteria. Finally, TOPSIS is used to obtain ranking of hospitals. To provide inputs for TOPSIS implementation, some key performance indicators are established and related data is gathered by the aid of experts from the assessed hospitals. A case study considering 4 hospitals from the Turkish healthcare sector was used to demonstrate the proposed approach. The results evidenced that Personnel is the most important factor (global weight = 0.280) when evaluating the hospital preparedness while Flexibility has the greatest prominence (c + r = 23.09).

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/3754Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.ijdrr.2020.101748Yayıncı resmi DOI adresi
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87
WoS
69
OpenAlex
97
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorOrtiz-Barrios, Miguel
dc.contributor.authorGul, Muhammet
dc.contributor.authorLópez-Meza, Pedro
dc.contributor.authorYucesan, Melih
dc.contributor.authorNavarro-Jiménez, Eduardo
dc.date.accessioned2026-10-28T14:57:04.693413373Z
dc.date.available2026-10-28T14:57:04.693413373Z
dc.date.issued2020
dc.description.abstractConsidering the unexpected emergence of natural and man-made disasters over the world and Turkey, the importance of preparedness of hospitals, which are the first reference points for people to get healthcare services, becomes clear. Determining the level of disaster preparedness of hospitals is an important and necessary issue. This is because identifying hospitals with low level of preparedness is crucial for disaster preparedness planning. In this study, a hybrid fuzzy decision making model was proposed to evaluate the disaster preparedness of hospitals. This model was developed using fuzzy analytic hierarchy process (FAHP)-fuzzy decision making trial and evaluation laboratory (FDEMATEL)-technique for order preference by similarity to ideal solutions (TOPSIS) techniques and aimed to determine a ranking for hospital disaster preparedness. FAHP is used to determine weights of six main criteria (including hospital buildings, equipment, communication, transportation, personnel, flexibility) and a total of thirty-six sub-criteria regarding disaster preparedness. At the same time, FDEMATEL is applied to uncover the interdependence between criteria and sub-criteria. Finally, TOPSIS is used to obtain ranking of hospitals. To provide inputs for TOPSIS implementation, some key performance indicators are established and related data is gathered by the aid of experts from the assessed hospitals. A case study considering 4 hospitals from the Turkish healthcare sector was used to demonstrate the proposed approach. The results evidenced that Personnel is the most important factor (global weight = 0.280) when evaluating the hospital preparedness while Flexibility has the greatest prominence (c + r = 23.09).
dc.identifier.articlenumber101748
dc.identifier.doi10.1016/j.ijdrr.2020.101748
dc.identifier.issn2212-4209
dc.identifier.pmcidPMC7335495
dc.identifier.pmid32834973
dc.identifier.scopus2-s2.0-85087481432
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/3754
dc.identifier.volume49
dc.identifier.wosWOS:000572973300013
dc.language.isoen
dc.publisherElsevier Ltd
dc.relation.ispartofInternational Journal of Disaster Risk Reduction
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectDisaster preparedness
dc.subjectFAHP
dc.subjectFDEMATEL
dc.subjectFuzzy decision making
dc.subjectTOPSIS
dc.subjectTurkish hospitals
dc.subject.classificationGeosciences, Multidisciplinary
dc.subject.classificationMeteorology & Atmospheric Sciences
dc.subject.classificationWater Resources
dc.subject.classificationGeology
dc.subject.otherSERVICE QUALITY
dc.subject.otherFUZZY
dc.subject.otherCRITERIA
dc.subject.otherPERCEPTIONS
dc.subject.otherRESILIENCE
dc.subject.otherHEALTH
dc.subject.otherMODEL
dc.titleEvaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals
dc.typeArticle
rdl.citation.openalex97
rdl.citation.scopus87
rdl.citation.wos69
rdl.departmentDepartment of Industrial Management, Agroindustry and Operations, Universidad de la Costa CUC, 58th St # 36 - 66, Barranquilla, Colombia
rdl.departmentDepartment of Industrial Engineering, Munzur University, Tunceli, Turkey
rdl.departmentDepartment of Industrial Engineering, Institución Universitaria ITSA, Barranquilla, Colombia
rdl.departmentDepartment of Mechanical Engineering, Munzur University, Tunceli, Turkey
rdl.departmentFaculty of Health Sciences, Universidad Simon Bolívar, Barranquilla, Colombia
rdl.oa.statusgreen
rdl.oa.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/7335495
rdl.scopus.quartileQ1
rdl.sdgSDG03
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)