Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals
| datacite.rights | http://purl.org/coar/access_right/c_16ec | spa |
| dc.contributor.author | Ortiz-Barrios, Miguel | |
| dc.contributor.author | Gul, Muhammet | |
| dc.contributor.author | López-Meza, Pedro | |
| dc.contributor.author | Yucesan, Melih | |
| dc.contributor.author | Navarro-Jiménez, Eduardo | |
| dc.date.accessioned | 2020-07-27T20:59:09Z | |
| dc.date.available | 2020-07-27T20:59:09Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | 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 ¼ 0.280) when evaluating the hospital preparedness while Flexibility has the greatest prominence (c þ r ¼ 23.09). | eng |
| dc.format.mimetype | spa | |
| dc.identifier.doi | https://doi.org/10.1016/j.ijdrr.2020.101748 | |
| dc.identifier.issn | 22124209 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12442/6239 | |
| dc.identifier.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335495/ | |
| dc.language.iso | eng | eng |
| dc.publisher | Elsevier | spa |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | |
| dc.rights.accessrights | info:eu-repo/semantics/embargoedAccess | eng |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.source | International Journal of Disaster Risk Reduction | eng |
| dc.source | Vol 49, (2020) | |
| dc.subject | Disaster preparedness | eng |
| dc.subject | Fuzzy decision making | eng |
| dc.subject | FAHP | eng |
| dc.subject | FDEMATEL | eng |
| dc.subject | TOPSIS | eng |
| dc.subject | Turkish hospitals | eng |
| dc.title | Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals | eng |
| dc.type.driver | info:eu-repo/semantics/article | eng |
| dc.type.spa | Artículo científico | spa |
| dcterms.references | S.M. Hosseini, M. Bahadori, M. Raadabadi, R. Ravangard, Ranking hospitals based on the disasters preparedness using the TOPSIS technique in western Iran, Hosp. Top. 97 (1) (2019) 23–31. | eng |
| dcterms.references | EM-DAT: The Emergency Events Database - Universite catholique de Louvain (UCL) - CRED, D. Guha-Sapir - www.emdat.be, (Brussels, Belgium). | eng |
| dcterms.references | World Health Organization, Coronavirus disease 2019 (COVID-19) situation report–93, Retrieved from, https://www.who.int/docs/default-source/coronavirus e/situation-reports/20200422-sitrep-93-covid-19.pdf?sfvrsn¼35cf80d7_4, 2020. | eng |
| dcterms.references | M. Gul, A.F. Guneri, Are emergency departments in Istanbul ready for the earthquakes? Past experience and suggestions for future preparedness from employees’ viewpoint and the literature, J. Homel. Secur. Emerg. Manag. 12 (4) (2015) 967–983. | eng |
| dcterms.references | R. Dursun, C.A. G€ormeli, G. Grmeli, M.R. €Oncü, S. Karadas¸, M. Berktas¸, A. S¸ehitogulları, Disaster plan of hospital and emergency service in the van earthquake, J. Acad. Emerg. Med./Akademik Acil Tip Olgu Sunumlari Dergisi 11 (2) (2012). | eng |
| dcterms.references | O. Keskin, M. Kalemoglu, Earthquake and Trıage, Ulusal Travma Dergisi 8 (2002) 108–111. | eng |
| dcterms.references | N. Kurt, H.F. Küçük, G. Çelik, R. Demirhan, €O. Gül, G. Altaca, Evaluation of the earthquake victims: August the 17th, 1999 our experience in the Marmara Earthquake, Turkish J. Trauma Emerg. Surg. 7 (1) (2001) 49–51 | spa |
| dcterms.references | N. Ishii, S. Nakayama, Emergency medical care following the great Hanshin-Awaji earthquake: practices and proposals (a report from a university hospital located in the damaged region), Kobe J. Med. Sci. 42 (3) (1996) 173–186. | eng |
| dcterms.references | K. Yamauchi, S. Mizuno, Z. Xu, Disaster-readiness of medical facilities in Aichi Prefecture, Nagoya J. Med. Sci. 59 (1996) 121–128 | eng |
| dcterms.references | J.W. Foxell Jr., R.E. McCreight, US disaster recovery readiness for a biological terrorist incident: Part Four, Adv. Pure Math. 24 (4) (2002) 323–337. | eng |
| dcterms.references | K.D. Pitilakis, A.I. Anastasiadis, K.G. Kakderi, M.V. Manakou, D.K. Manou, M. N. Alexoudi, S.D. Fotopoulou, S.A. Argyroudis, K.G. Senetakis, Development of comprehensive earthquake loss scenarios for a Greek and a Turkish city: seismic hazard, geotechnical and lifeline aspects, Earthq. Struct. 2 (3) (2011) 207–232. | eng |
| dcterms.references | G. Zuccaro, F. Cacace, Seismic casualty evaluation: the Italian model, an application to the L’Aquila 2009 event, in: Human Casualties in Earthquakes, Springer, Dordrecht, 2011, pp. 171–184. | eng |
| dcterms.references | W. Fawcett, C.S. Oliveira, Casualty treatment after earthquake disasters: development of a regional simulation model, Disasters 24 (3) (2000) 271–287. | eng |
| dcterms.references | M.A. Ortiz-Barrios, B.A. Aleman-Romero, J. Rebolledo-Rudas, H. Maldonado- Mestre, L. Montes-Villa, F. De Felice, A. Petrillo, The analytic decision-making preference model to evaluate the disaster readiness in emergency departments: the ADT model, J. Multi-Criteria Decis. Anal. 24 (5–6) (2017) 204–226. | eng |
| dcterms.references | M.A. Ortiz-Barrios, B. Kucukaltan, D. Carvajal-Tinoco, D. Neira-Rodado, G. Jiménez, Strategic hybrid approach for selecting suppliers of high-density polyethylene, J. Multi-Criteria Decis. Anal. 24 (5–6) (2017) 296–316. | eng |
| dcterms.references | F. Rezaei, Z. Mohebbi-Dehnavi, Evaluation of the readiness of hospitals affiliated to Isfahan University of Medical Sciences in unexpected events in 2017, J. Educ. Health Promot. 8 (2019). | eng |
| dcterms.references | M. Saeid, H. Khankeh, A. Habibisoola, M. Mohammadali, G. Hamidkolg, B. Dadkhah, Investigating hospital preparedness in Ardabil Province against unexpected accidents, Health Emergencies Disasters 4 (3) (2019) 127–134. | eng |
| dcterms.references | A. Alruwaili, S. Islam, K. Usher, Disaster preparedness in hospitals in the Middle East: an integrative literature review, Disaster Med. Public Health Prep. 13 (4) (2019) 806–816. | eng |
| dcterms.references | S.A.N. Tabatabaei, S. Abbasi, Risk assessment in social security hospitals of Isfahan Province in case of disasters based on the hospital safety index, Int. J. Health Syst. Disaster Manag. 4 (3) (2016) 82. | eng |
| dcterms.references | W.N. Naser, P.L. Ingrassia, S. Aladhrae, W.A. Abdulraheem, A study of hospital disaster preparedness in South Yemen, Prehospital Disaster Med. 33 (2) (2018) 133–138. | eng |
| dcterms.references | N.M. Samsuddin, R. Takim, A.H. Nawawi, S.N.A.S. Alwee, Disaster preparedness attributes and hospital’s resilience in Malaysia, Procedia Eng. 212 (2018) 371–378. | eng |
| dcterms.references | M.A. Marzaleh, R. Rezaee, A. Rezaianzadeh, M. Rakhshan, G. Haddadi, M. Peyravi, Developing a model for hospitals’ emergency department preparedness in radiation and nuclear incidents and nuclear terrorism in Iran, Bull. Emergency Trauma 7 (3) (2019) 300. | eng |
| dcterms.references | H. Shabanikiya, M. Jafari, H.A. Gorgi, H. Seyedin, A. Rahimi, Developing a practical toolkit for evaluating hospital preparedness for surge capacity in disasters, Int. J. Disaster Risk Reduct. 34 (2019) 423–428. | eng |
| dcterms.references | M. Yucesan, S. Mete, M. Gul, E. Celik, A fuzzy decision-making model for the key performance indicators of hospital service quality evaluation, in: Computational Intelligence and Soft Computing Applications in Healthcare Management Science, IGI Global, 2020, pp. 42–62. | eng |
| dcterms.references | M. Yucesan, M. Gul, Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS, Soft Comput. 24 (5) (2020) 3237–3255. | eng |
| dcterms.references | E.K. Zavadskas, K. Govindan, J. Antucheviciene, Z. Turskis, Hybrid multiple criteria decision-making methods: a review of applications for sustainability issues, Econ. Res.-Ekonomska istrazivanja 29 (1) (2016) 857–887. | eng |
| dcterms.references | T.L. Saaty, What is the analytic hierarchy process?, in: Mathematical Models for Decision Support Springer, Berlin, Heidelberg, 1988, pp. 109–121. | eng |
| dcterms.references | S. Kumar, A. Haleem, Evaluating bullwhip effect mitigation: an analytical network process (ANP) application, Int. J. Adv. Res. Eng. Sci. Manag. 2 (1) (2015) 1–14. | eng |
| dcterms.references | M. Velasquez, P.T. Hester, An analysis of multi-criteria decision making methods, Int. J. Oper. Res. 10 (2) (2013) 56–66. | eng |
| dcterms.references | L.A. Zadeh, Fuzzy sets, Inf. Contr. 8 (3) (1965) 338–353. | eng |
| dcterms.references | T.L. Saaty, L.T. Tran, On the invalidity of fuzzifying numerical judgments in the Analytic Hierarchy Process, Math. Comput. Model. 46 (7–8) (2007) 962–975. | eng |
| dcterms.references | C. Kahraman, U. Cebeci, Z. Ulukan, Multi-criteria supplier selection using fuzzy AHP, Logist. Inf. Manag. 16 (6) (2003) 382–394. | eng |
| dcterms.references | F.T. Chan, N. Kumar, M.K. Tiwari, H.C. Lau, K. Choy, Global supplier selection: a fuzzy-AHP approach, Int. J. Prod. Res. 46 (14) (2008) 3825–3857. | eng |
| dcterms.references | T.C. Wang, Y.H. Chen, Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP, Inf. Sci. 178 (19) (2008) 3755–3765. | eng |
| dcterms.references | J.J. Buckley, Fuzzy hierarchical analysis, Fuzzy Set Syst. 17 (3) (1985) 233–247. | eng |
| dcterms.references | D.Y. Chang, Applications of the extent analysis method on fuzzy AHP, Eur. J. Oper. Res. 95 (3) (1996) 649–655. | eng |
| dcterms.references | H.K. Chan, X. Wang, Fuzzy extent analysis for food risk assessment, in: Fuzzy | eng |
| dcterms.references | H.K. Chan, X. Wang, Fuzzy extent analysis for food risk assessment, in: Fuzzy Hierarchical Model for Risk Assessment, Springer, London, 2013, pp. 89–114. | eng |
| dcterms.references | G.H. Tzeng, J.J. Huang, Multiple Attribute Decision Making: Methods and Applications, Chapman and Hall/CRC, 2011. | eng |
| dcterms.references | M. Gul, A.F. Guneri, A fuzzy multi criteria risk assessment based on decision matrix technique: a case study for aluminum industry, J. Loss Prev. Process. Ind. 40 (2016) 89–100. | eng |
| dcterms.references | L. Pecchia, N. Pendleton, S. Jackson, C. Clarke, P. Briggs, L. Mcinnes, M. Bracale, The Use of Analytic Hierarchy Process for the Prioritization of Factors Affecting Wellbeing in Elderly, 2011, pp. 1–4. Sorrento, Naples, Italy. | eng |
| dcterms.references | M.J. IJzerman, J.A. Van Til, J.F. Bridges, A comparison of analytic hierarchy process and conjoint analysis methods in assessing treatment alternatives for stroke rehabilitation, Patient-Patient-Centered Outcomes Res. 5 (1) (2012) 45–56. | eng |
| dcterms.references | A. Gabus, E. Fontela, World Problems, an Invitation to Further Thought within the Framework of DEMATEL, Battelle Geneva Research Center, Geneva, Switzerland, 1972, pp. 1–8. | eng |
| dcterms.references | E. Akyuz, E. Celik, A fuzzy DEMATEL method to evaluate critical operational hazards during gas freeing process in crude oil tankers, J. Loss Prev. Process. Ind. 38 (2015) 243–253. | eng |
| dcterms.references | M. Gul, A.F. Guneri, B. Derin, Evaluation of service quality criteria for a private medical center by using SERVQUAL and DEMATEL methods, Sigma 32 (2014) 240–253. | eng |
| dcterms.references | W.W. Wu, Y.T. Lee, Developing global managers’ competencies using the fuzzy DEMATEL method, Expert Syst. Appl. 32 (2) (2007) 499–507. | eng |
| dcterms.references | M. Gul, Emergency department ergonomic design evaluation: a case study using fuzzy DEMATEL-focused two-stage methodology, Health Pol. Technol. 8 (4) (2019) 365–376. | eng |
| dcterms.references | T.J. Ross, Fuzzy Logic with Engineering Applications, John Wiley & Sons, 2005. | eng |
| dcterms.references | S.L. Si, X.Y. You, H.C. Liu, P. Zhang, DEMATEL technique: a systematic review of the state-of-the-art literature on methodologies and applications, Math. Probl Eng. (2018), 2018. | eng |
| dcterms.references | M. Oussalah, On the compatibility between defuzzification and fuzzy arithmetic operations, Fuzzy Set Syst. 128 (2) (2002) 247–260. | eng |
| dcterms.references | S.L. Si, X.Y. You, H.C. Liu, J. Huang, Identifying key performance indicators for holistic hospital management with a modified DEMATEL approach, Int. J. Environ. Res. Publ. Health 14 (8) (2017) 934. | eng |
| dcterms.references | L. Zhang, R. Liu, S. Jiang, G. Luo, H.C. Liu, Identification of key performance indicators for hospital management using an extended hesitant linguistic DEMATEL approach, in: Healthcare, vol. 8, Multidisciplinary Digital Publishing Institute, 2020, March, p. 7. No. 1. | eng |
| dcterms.references | C.L. Hwang, K. ve Yoon, Multiple Attribute Decision Making-Methods and Applications: A State of the Art Survey, Springer, New York, 1981. | eng |
| dcterms.references | L. Pecchia, J.L. Martin, A. Ragozzino, C. Vanzanella, A. Scognamiglio, L. Mirarchi, S.P. Morgan, User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner, BMC Med. Inf. Decis. Making 13 (1) (2013) 2. | eng |
| dcterms.references | M.A. Ortiz-Barrios, Z. Herrera-Fontalvo, J. Rúa-Mu~noz, S. Ojeda-Gutierrez, F. De Felice, A. Petrillo, An integrated approach to evaluate the risk of adverse events in hospital sector, Manag. Decis. (2018). | eng |
| dcterms.references | S. Zhong, X. Hou, M. Clark, Y. Zang, L. Wang, L. Xu, G. Fitzgerald, Disaster resilience in tertiary hospitals: a cross-sectional survey in shandong province, China, BMC Health Serv. Res. 14 (2014), https://doi.org/10.1186/1472-6963-14- 13. | eng |
| dcterms.references | E.B. Leksono, S. Suparno, I. Vanany, Integration of a balanced scorecard, DEMATEL, and ANP for measuring the performance of a sustainable healthcare supply chain, Sustainability 11 (13) (2019) 3626. | eng |
| dcterms.references | G.P. Cimellaro, A.M. Reinhorn, M. Bruneau, Seismic resilience of a hospital system, Struct. Infrastruct. Eng. 6 (1–2) (2010) 127–144, https://doi.org/10.1080/ 15732470802663847. | eng |
| dcterms.references | M. Loosemore, A. Chand, Barriers to building resilience to extreme weather events in australian hospitals, in: Paper Presented at the Proceedings of the 32nd Annual ARCOM Conference, vol. 2016, ARCOM, 2016, pp. 1201–1210. | eng |
| dcterms.references | L. Arlym, D. Hermon, D. Lanin, O. Oktorie, A. Putra, A policy model of preparedness the general hospital in reducing victims of earthquake and tsunami disasters in siberut mentawai island, Indonesia, Int. J. Recent Technol. Eng. 8 (3) (2019) 89–93, https://doi.org/10.35940/ijrte.C3890.098319. | eng |
| dcterms.references | M. Acar, O. Kaya, A healthcare network design model with mobile hospitals for disaster preparedness: a case study for istanbul earthquake, Transport. Res. E Logist. Transport. Rev. 130 (2019) 273–292, https://doi.org/10.1016/j. tre.2019.09.007. | eng |
| dcterms.references | J.L. de Jong, W.C. Benton, Dependence and power in healthcare equipment supply chains, Health Care Manag. Sci. 22 (2) (2019) 336–349, https://doi.org/10.1007/ s10729-018-9440-z. | eng |
| dcterms.references | K. Ertugay, S. Argyroudis, H.T. Düzgün, Accessibility modeling in earthquake case considering road closure probabilities: a case study of health and shelter service accessibility in thessaloniki, Greece, Int. J. Disaster Risk Reduct. 17 (2016) 49–66, https://doi.org/10.1016/j.ijdrr.2016.03.005. | eng |
| dcterms.references | M.A. Al Khalaileh, E. Bond, J.A. Alasad, Jordanian nurses’ perceptions of their preparedness for disaster management, Int. Emerg. Nurs. 20 (1) (2012) 14–23, https://doi.org/10.1016/j.ienj.2011.01.001. | eng |
| dcterms.references | A. Simonetti, H. Ezzeldin, M. Walderhaug, S.A. Anderson, R.A. Forshee, An interregional US blood supply simulation model to evaluate blood availability to support planning for emergency preparedness and medical countermeasures, Disaster Med. Public Health Prep. 12 (2) (2018) 201–210, https://doi.org/ 10.1017/dmp.2017.48. | eng |
| dcterms.references | C. Huang, Y. Wang, X. Li, L. Ren, J. Zhao, Y. Hu, B. Cao, Clinical features of patients infected with 2019 novel coronavirus in wuhan, China, Lancet 395 (10223) (2020) 497–506, https://doi.org/10.1016/S0140-6736(20)30183-5. | eng |
| dcterms.references | Y.T. Xin, K.Y. Xu, Hospital emergency management research in China: trends and challenges, Emerg. Med. J. 29 (5) (2012) 353–357. | eng |
| dcterms.references | M. Akdere, M. Top, S. Tekingündüz, Examining patient perceptions of service quality in Turkish hospitals: The SERVPERF model. Total Quality Management & Business Excellence 31 (3–4) (2020) 342–352, https://doi.org/10.1080/ 14783363.2018.1427501. | eng |
| oaire.version | info:eu-repo/semantics/publishedVersion | eng |
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