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A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks

Most of the healthcare facilities (HFs) have to face the nosocomial infections (NIs), which increase the rates of morbidity, mortality, and financial burden on the HFs and the patients. The control of the NIs is a global issue and requires additional effort. Because the pathogenic microbes can be tr...

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Autores principales: Parsia, Yasaman, Sorooshian, Shahryar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037869/
https://www.ncbi.nlm.nih.gov/pubmed/32019085
http://dx.doi.org/10.3390/ijerph17030855
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author Parsia, Yasaman
Sorooshian, Shahryar
author_facet Parsia, Yasaman
Sorooshian, Shahryar
author_sort Parsia, Yasaman
collection PubMed
description Most of the healthcare facilities (HFs) have to face the nosocomial infections (NIs), which increase the rates of morbidity, mortality, and financial burden on the HFs and the patients. The control of the NIs is a global issue and requires additional effort. Because the pathogenic microbes can be transmitted among all the HF departments, the layout and design of the HFs (or the department configuration) is considered to play a significant role in control of the NIs. A few of the departments transmit the microbes more than other departments, called ‘cause’, while some other departments are more infected than others, called ‘effect’. Here, the researchers have stated that both the cause and effect departments are risky. This research tried to propose a comprehensive mathematical algorithm for choosing the high-risk department(s) by applying the NI and the managerial criteria to minimize NIs through rearchitecting of the HFs. To develop the algorithm, the researchers applied the multiple criteria decision-making (MCDM) methods. They used Decision-Making Trial and Evaluation Laboratory (DEMATEL) and modified weighted sum method (WSM) methods, and their hybrid, along with a modified nominal group technique (NGT) for data collection. The proposed algorithm was later validated by implementation in a HF as a case study. Based on all results of the algorithm, the high-risk departments in the HF were identified and proposed to be eliminated from the HF in such a way that the facility would retain its functionality. The algorithm was seen to be valid, and the feasibility of the algorithm was approved by the top managers of the HF after the algorithm was implemented in the case study. In conclusion, the proposed algorithm was seen to be an effective solution for minimizing the NIs risk in every HF by eliminating the high-risk departments, which could simplify the HF manager’s decisions.
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spelling pubmed-70378692020-03-10 A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks Parsia, Yasaman Sorooshian, Shahryar Int J Environ Res Public Health Article Most of the healthcare facilities (HFs) have to face the nosocomial infections (NIs), which increase the rates of morbidity, mortality, and financial burden on the HFs and the patients. The control of the NIs is a global issue and requires additional effort. Because the pathogenic microbes can be transmitted among all the HF departments, the layout and design of the HFs (or the department configuration) is considered to play a significant role in control of the NIs. A few of the departments transmit the microbes more than other departments, called ‘cause’, while some other departments are more infected than others, called ‘effect’. Here, the researchers have stated that both the cause and effect departments are risky. This research tried to propose a comprehensive mathematical algorithm for choosing the high-risk department(s) by applying the NI and the managerial criteria to minimize NIs through rearchitecting of the HFs. To develop the algorithm, the researchers applied the multiple criteria decision-making (MCDM) methods. They used Decision-Making Trial and Evaluation Laboratory (DEMATEL) and modified weighted sum method (WSM) methods, and their hybrid, along with a modified nominal group technique (NGT) for data collection. The proposed algorithm was later validated by implementation in a HF as a case study. Based on all results of the algorithm, the high-risk departments in the HF were identified and proposed to be eliminated from the HF in such a way that the facility would retain its functionality. The algorithm was seen to be valid, and the feasibility of the algorithm was approved by the top managers of the HF after the algorithm was implemented in the case study. In conclusion, the proposed algorithm was seen to be an effective solution for minimizing the NIs risk in every HF by eliminating the high-risk departments, which could simplify the HF manager’s decisions. MDPI 2020-01-30 2020-02 /pmc/articles/PMC7037869/ /pubmed/32019085 http://dx.doi.org/10.3390/ijerph17030855 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Parsia, Yasaman
Sorooshian, Shahryar
A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks
title A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks
title_full A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks
title_fullStr A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks
title_full_unstemmed A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks
title_short A Decision-Making Algorithm for Rearchitecting of Healthcare Facilities to Minimize Nosocomial Infections Risks
title_sort decision-making algorithm for rearchitecting of healthcare facilities to minimize nosocomial infections risks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037869/
https://www.ncbi.nlm.nih.gov/pubmed/32019085
http://dx.doi.org/10.3390/ijerph17030855
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