Assessing the preparedness of hospitals facing disasters using the rough set theory: guidelines for more preparedness to cope with the COVID-19

Moheimani, Arash; Sheikh, Reza; Hosseini, Seyed Mohammad Hassan; Sana, Shib Sankar

doi:10.1080/23302674.2021.1904301

Cited by 20 publications

(17 citation statements)

References 59 publications

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“…Studies developed for these situations were also discussed with the motivation of “evaluation of disaster preparedness of hospitals”. The topic of disaster preparedness assessment of hospitals is not yet an area in which there are many studies in the literature [ 9 , [44] , [45] , [46] , [47] , [48] , [49] ]. While some of the studies conducted are conceptual or cross-sectional questionnaire-based studies by researchers from medical branches, others are MCDM-based studies where researchers from the field of computer science generally work.…”

Section: Review Of the Literaturementioning

confidence: 99%

A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case

Ortíz‐Barrios

Gül

Yücesan

et al. 2022

International Journal of Disaster Risk Reduction

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The recent increase in the number of disasters over the world has once again brought to the agenda the question of preparedness of the hospitals, which are the most necessary units of healthcare pillar to resist these disasters. The COVID-19 epidemic disease, which has affected the whole world, has caused a large number of people to die in some countries simply because of the inadequate and incomplete planning and lack of readiness of hospitals. For this reason, determining the disaster preparedness level of hospitals is an important issue that needs to be studied and it is important in terms of disaster damage reduction. In this study, a fuzzy hybrid decision-making framework is proposed to assess hospital disaster preparedness. The framework covers three important decision-making methods. For the first phase, Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) is used to assign relative weights for several disaster preparedness criteria considering uncertainty. Secondly, Intuitionistic Fuzzy Decision Making Trial and Evaluation Laboratory (IF-DEMATEL) is applied to identify interrelations among these criteria and feedback. Finally, via the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, priorities of hospitals regarding disaster readiness are obtained. A case study involving the participation of 10 Colombian tertiary hospitals is carried out to show the applicability of this fuzzy hybrid approach.

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Section: Review Of the Literaturementioning

confidence: 99%

A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case

Ortíz‐Barrios

Gül

Yücesan

et al. 2022

International Journal of Disaster Risk Reduction

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show abstract

“…Integration with other methods. e combination of rough set theory and other methods, such as neural networks, genetic algorithms, fuzzy mathematics, and decision trees, can give play to their respective advantages and greatly enhance the efficiency of data mining [20].…”

Section: Rough Set Eory Analysismentioning

confidence: 99%

Aviation and Airspace Management under Rough Set Theory

Zhu

Kan

2022

Mathematical Problems in Engineering

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With the development of aviation industry, a series of problems have appeared in aviation and airspace, among which the most prominent problem is the congestion of aviation and airspace. Airspace congestion has become a major problem in the development of civil aviation in China. Especially in the central and eastern regions of China, airspace congestion is becoming more and more serious. To better solve the problem of airspace congestion, rough set theory and the Fuzzy C-means (FCM) model are first analyzed. By analyzing the temporal and spatial characteristics of traffic congestion in the control sector, a multisector traffic congestion identification model is established based on radar track data. Four multisector congestion characteristics including equivalent traffic volume, proximity, saturation, and traffic density are established. FCM and rough set theory are used to classify and identify sector congestion. Finally, the model based on FCM-rough set theory is compared with other methods based on the data of the regional control sector in northwest China. The experimental results show that the congestion recognition rate of the model is 92.6%, 93.5%, and 94.2%, and the congestion misjudgment rate is 1.5%, 1.2%, and 1.3%, respectively. Hence, the multisector congestion recognition model has a high recognition rate and a low misjudgment rate, and the overall discrimination result is relatively stable. By comparing the proposed method with other methods, it is concluded that the recognition accuracy of the model based on FCM theory is superior to other methods. In summary, the congestion situation of the sector is affected by a variety of macro- and micro-characteristics of the sector, and the congestion identification model is feasible and efficient. Multisector traffic congestion identification has certain application value for airspace planning, air traffic control-assisted decision making, and air traffic flow management. This work can optimize the aviation and airspace management system and provide relevant suggestions for the study of aviation and airspace congestion.

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“…The study was conducted in three hospitals in the Shandong province of China and showed the insufficient capacity of hospitals. Moheimani et al ( 2021a ) examined the preparedness of 25 hospitals against the COVID-19 pandemic in Tehran. The data were collected with 3 doctors who are experts in their fields and who have knowledge of the hospitals' conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

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

2021

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Assessing the preparedness of hospitals facing disasters using the rough set theory: guidelines for more preparedness to cope with the COVID-19

Cited by 20 publications

References 59 publications

A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case

A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case

Aviation and Airspace Management under Rough Set Theory

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

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