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Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach
The purchase of medical equipment is a critical issue that should be planned properly. The selection of the most appropriate vendor impacts time, effort, and expenses. Therefore, the challenge is to strike a balance between the available budget and the required equipment. The study aims to select th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406946/ https://www.ncbi.nlm.nih.gov/pubmed/37550351 http://dx.doi.org/10.1038/s41598-023-38902-3 |
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author | Saleh, Neven Gaber, Mohamed N. Eldosoky, Mohamed A. Soliman, Ahmed M. |
author_facet | Saleh, Neven Gaber, Mohamed N. Eldosoky, Mohamed A. Soliman, Ahmed M. |
author_sort | Saleh, Neven |
collection | PubMed |
description | The purchase of medical equipment is a critical issue that should be planned properly. The selection of the most appropriate vendor impacts time, effort, and expenses. Therefore, the challenge is to strike a balance between the available budget and the required equipment. The study aims to select the best vendor for supplying medical equipment based on Emergency Care Research Institute (ECRI) standards. The multi-criteria decision-making approach has been adopted through three methods; Multi-Objective Optimization by Ratio Analysis (MOORA), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The criteria of selection are divided into general, technical, and financial. The criteria are weighted using three methods: CRITIC, entropy, and expert judgment. The Vendor Evaluation Program for Medical Equipment (VEPME) is designed to automatically select the best vendor. Medical imaging equipment is selected to test the program by four modalities: X-ray equipment, CT, MRI, and ultrasound. The best scenario was given by the entropy-TOPSIS. As a result, this methodology was adopted by the program. The results demonstrate the robustness of the proposed methodology by comparing the VEPME output to expert judgment. |
format | Online Article Text |
id | pubmed-10406946 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104069462023-08-09 Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach Saleh, Neven Gaber, Mohamed N. Eldosoky, Mohamed A. Soliman, Ahmed M. Sci Rep Article The purchase of medical equipment is a critical issue that should be planned properly. The selection of the most appropriate vendor impacts time, effort, and expenses. Therefore, the challenge is to strike a balance between the available budget and the required equipment. The study aims to select the best vendor for supplying medical equipment based on Emergency Care Research Institute (ECRI) standards. The multi-criteria decision-making approach has been adopted through three methods; Multi-Objective Optimization by Ratio Analysis (MOORA), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The criteria of selection are divided into general, technical, and financial. The criteria are weighted using three methods: CRITIC, entropy, and expert judgment. The Vendor Evaluation Program for Medical Equipment (VEPME) is designed to automatically select the best vendor. Medical imaging equipment is selected to test the program by four modalities: X-ray equipment, CT, MRI, and ultrasound. The best scenario was given by the entropy-TOPSIS. As a result, this methodology was adopted by the program. The results demonstrate the robustness of the proposed methodology by comparing the VEPME output to expert judgment. Nature Publishing Group UK 2023-08-07 /pmc/articles/PMC10406946/ /pubmed/37550351 http://dx.doi.org/10.1038/s41598-023-38902-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Saleh, Neven Gaber, Mohamed N. Eldosoky, Mohamed A. Soliman, Ahmed M. Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach |
title | Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach |
title_full | Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach |
title_fullStr | Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach |
title_full_unstemmed | Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach |
title_short | Vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach |
title_sort | vendor evaluation platform for acquisition of medical equipment based on multi-criteria decision-making approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406946/ https://www.ncbi.nlm.nih.gov/pubmed/37550351 http://dx.doi.org/10.1038/s41598-023-38902-3 |
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