Multiple-criteria Evaluation Model for Medical Professionals Assigned to Temporary SARS-CoV-2 Hospitals
DOI:
https://doi.org/10.31181/dmame2104153mKeywords:
COVID-19 pandemic; health care service; multicriteria decision makingAbstract
Hospitals around the world, as health institutions with a key role in the health system, face problems while providing health services to patients with various types of diseases. Currently, those problems are intensified due to the pandemic caused by SARS-CoV-2 virus. This pandemic has caused an extreme spread of the disease with constantly changing needs of patients which impacts the capacities and overall functioning of hospitals. In order to meet the challenge of the COVID-19 (COronaVIrus Disease- 2019) pandemic, health systems must adjust to new circumstances and establish separate hospitals exclusive for patients infected with SARS-CoV-2 virus. In the process of creating COVID-19 hospitals, health systems face a shortage of medical professionals trained for work in COVID-19 hospitals. Using this as a starting point, this study puts forward a two-phase model for the evaluation and selection of nurses for COVID-19 hospitals. Each phase of the model features a separate multiple-criteria model. In the first phase, a multiple-criteria model with a dominant criterion is formed and candidates who meet the defined requirements are evaluated. In the second phase, a modified multiple-criteria model is formed and used to evaluate medical professionals who do not meet the requirements of the dominant criterion. By applying this model, two groups of medical professionals are defined: 1) medical professionals who completely meet the requirements for working in COVID-19 hospitals and 2) medical professionals who require additional training. The criteria for evaluation of medical professionals in this multiple-criteria model are defined based on research conducted on medical professionals assigned to the COVID-19 Crisis Response Team during the COVID-19 pandemic in the Republic of Serbia. The model was tested on a real example of evaluating medical professionals assigned to the COVID-19 hospital in Sombor. The model for evaluating medical professionals presented in this paper can help decision makers in hospitals and national policy makers to determine the readiness level of hospitals for working in the conditions of the COVID-19 pandemic, as well as underline the areas in which hospitals are not ready to meet the challenges of the pandemic.
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Behzad, M., Hashemkhani Zolfani, S., Pamucar, D., & Behzad, M. (2020). A Comparative Assessment of Solid Waste Performance Management in the Nordic Countries based on BWM-EDAS. Journal of Cleaner Production, 266 122008, https://doi.org/10.1016/j.jclepro.2020.122008.
Ecer, F., & Pamucar, D. (2020). Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo'B) multi-criteria model. Journal of Cleaner Production, 266, 121981. https://doi.org/10.1016/j.jclepro.2020.121981.
Fallah-Aliabadi, S., Ostadtaghizadeh, A., Ardalan, A., Fatemi, F., Khazai, B., & Mirjalili, M. R. (2020). Towards developing a model for the evaluation of hospital disaster resilience: a systematic review. BMC health services research, 20(1), 64-73.
Hosseini, S. M., Bahadori, M., Raadabadi, M., & Ravangard, R. (2019). Ranking hospitals based on the disasters preparedness using the TOPSIS technique in western Iran. Hospital topics, 97(1), 23-31.
Marzaleh, M. A., Rezaee, R., Rezaianzadeh, A., Rakhshan, M., Hadadi, G., & Peyravi, M. (2019). Emergency Department Preparedness of Hospitals for Radiation, Nuclear Accidents, and Nuclear Terrorism: A Qualitative Study in Iran. Iranian Red Crescent Medical Journal, 21(5), 300–306.
Mulyasari, F., Inoue, S., Prashar, S., Isayama, K., Basu, M., Srivastava, N., & Shaw, R. (2013). Disaster preparedness: Looking through the lens of hospitals in Japan. International Journal of Disaster Risk Science, 4(2), 89-100.
Nardo, P.D., Gentilotti, E., Mazzaferri, F., Cremonini, E., Hansen, P., Goossens, H., & Tacconelli, E. (2020). Multi-Criteria Decision Analysis to prioritize hospital admission of patients affected by COVID-19 in low-resource settings with hospital-bed shortage. International Journal of Infectious Diseases, 98, 494-500.
Nekoie-Moghadam, M., Kurland, L., Moosazadeh, M., Ingrassia, P. L., Della Corte, F., & Djalali, A. (2016). Tools and checklists used for the evaluation of hospital disaster preparedness: a systematic review. Disaster medicine and public health preparedness, 10(5), 781-788.
Ortiz‐Barrios, M. A., Aleman‐Romero, B. A., Rebolledo‐Rudas, J., Maldonado‐Mestre, H., Montes‐Villa, L., De Felice, F., & Petrillo, A. (2017). The analytic decision‐making preference model to evaluate the disaster readiness in emergency departments: The ADT model. Journal of Multi‐Criteria Decision Analysis, 24(5-6), 204-226.
Pamucar, D., Behzad, M., Bozanic, D., & Behzad, M. (2020c). Decision making to support sustainable energy policies corresponding to agriculture sector: Case study in Iran’s Caspian Sea coastline. Journal of Cleaner Production, 292, 125302, https://doi.org/10.1016/j.jclepro.2020.125302.
Pamucar, D., Cirovic, G., Zizovic, M.M., & Miljkovic, B. (2020a). A Model for Determining Weight Coefficients by Forming a Non-Decreasing Series at Criteria Significance Levels (NDSL). Mathematics, 8(5), 745.
Pamucar, D., Yazdani, M., Obradovic, R., Kumar, A., & Torres-Jiménez, M. (2020b). A Novel fuzzy hybrid Neutrosophic decision-making approach for the resilient supplier selection problem. International Journal of Intelligent Systems, 35(12), 1934-1986.
Rezaei, F., & Mohebbi-Dehnavi, Z. (2019). Evaluation of the readiness of hospitals affiliated to Isfahan University of Medical Sciences in unexpected events in 2017. Journal of education and health promotion, 8.
Roy, J., Adhikary, K., Kar, S., & Pamucar, D. (2018). A rough strength relational DEMATEL model for analysing the key success factors of hospital service quality. Decision Making: Applications in Management and Engineering, 1(1), 121-142.
Samsuddin, N. M., Takim, R., Nawawi, A. H., & Alwee, S. N. A. S. (2018). Disaster preparedness attributes and hospital’s resilience in Malaysia. Procedia engineering, 212, 371-378.
Sangiorgio, V., & Parisi, P. (2020). A multicriteria approach for risk assessment of Covid-19 in urban district lockdown. Safety Science, 130, 104862, https://doi.org/10.1016/j.ssci.2020.104862.
Sarkar, S. (2020). COVID-19 Susceptibility Mapping Using Multicriteria Evaluation. Disaster Medicine and Public Health Preparedness, 14(4), 1-17.
Shabanikiya, H., Jafari, M., Gorgi, H. A., Seyedin, H., & Rahimi, A. (2019). Developing a practical toolkit for evaluating hospital preparedness for surge capacity in disasters. International journal of disaster risk reduction, 34, 423-428.
Tabatabaei, S. A. N., & Abbasi, S. (2016). Risk assessment in social security hospitals of Isfahan Province in case of disasters based on the hospital safety index. International Journal of Health System and Disaster Management, 4(3), 82.
Verheul, M. L., & Dückers, M. L. (2020). Defining and operationalizing disaster preparedness in hospitals: a systematic literature review. Prehospital and disaster medicine, 35(1), 61-68.
Yildirim, F.S., Sayan, M., Sanlidag, T., Uzun, B., Uzun, D., & Ozsahin, I. (2020). A Clinical Decision Support System for the Treatment of COVID-19 with Multi-Criteria Decision-Making Techniques. JMIR Medical Informatics, 22, 88-106.
Zizovic, M.M, Albijanic, M., Jovanović, V., & Zizovic, M (2019). A New Method of Multi-Criteria Analysis for Evaluation and Decision Making by Dominant Criterion. Informatica, 30(4), 819-832.
Žižović, M., Pamučar, D., Ćirović, G., Žižović, M.M., Miljković, B. (2020). A Model for Determining Weight Coefficients by Forming a Non-Decreasing Series at Criteria Significance Levels (NDSL). Mathematics, 8(5), 745.
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