A new approach for optimal design of intensive care unit

Abstract Planning and budgeting for healthcare facilities necessitate precise estimation and a thoughtful analysis of the required area for each department, as well as extensive knowledge of the most important elements that can influence the design and provide an appropriate environment for staff and patients. A gross conversion factor is influential in calculating the entire area of a department. However, there is no precise standard indicating how this factor should be calculated. To address this problem, quality function deployment (QFD) has been implemented. The intensive care unit (ICU) is one of the highly equipped departments that should be properly planned; therefore, it was selected for application. The five steps of the QFD are used to identify and rank the most important and efficient design features. Only the top factors are considered in calculating the required area for the ICU department. This approach presents a unique method for estimating the gross square area based on calculating the gross conversion factor. To demonstrate the proposed approach’s efficacy, it was applied to two Egyptian public hospitals. The results reveal that 15–16% of the total space of both hospitals can be reduced from the total department space. Moreover, an outstanding reduction in ICU design and preparation expenses has been achieved. The design reduces the required budget for a project while maintaining the same construction material quality and accommodating extra beds. Additionally, the QFD proves its ability to redesign the ICU department while reducing costs.

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Publication Details

Journal
Journal of Engineering and Applied Science
Published
2024-10-07
DOI
https://doi.org/10.1186/s44147-024-00534-3
Primary Topic
Quality Function Deployment in Product Design
Type
article
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article

A new approach for optimal design of intensive care unit

Neven Saleh, Manal Abdel Wahed
Journal of Engineering and Applied Science
Quality Function Deployment in Product Design
article

A new approach for optimal design of intensive care unit

Neven Saleh, Manal Abdel Wahed
article en

Abstract

Abstract Planning and budgeting for healthcare facilities necessitate precise estimation and a thoughtful analysis of the required area for each department, as well as extensive knowledge of the most important elements that can influence the design and provide an appropriate environment for staff and patients. A gross conversion factor is influential in calculating the entire area of a department. However, there is no precise standard indicating how this factor should be calculated. To address this problem, quality function deployment (QFD) has been implemented. The intensive care unit (ICU) is one of the highly equipped departments that should be properly planned; therefore, it was selected for application. The five steps of the QFD are used to identify and rank the most important and efficient design features. Only the top factors are considered in calculating the required area for the ICU department. This approach presents a unique method for estimating the gross square area based on calculating the gross conversion factor. To demonstrate the proposed approach’s efficacy, it was applied to two Egyptian public hospitals. The results reveal that 15–16% of the total space of both hospitals can be reduced from the total department space. Moreover, an outstanding reduction in ICU design and preparation expenses has been achieved. The design reduces the required budget for a project while maintaining the same construction material quality and accommodating extra beds. Additionally, the QFD proves its ability to redesign the ICU department while reducing costs.

Journal of Engineering and Applied ScienceVol. 71(1)
Cairo University (EG), Future University in Egypt (EG)
Openalex Percentile: Top 71%
Quality Function Deployment in Product Design
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A new approach for optimal design of intensive care unit — Neven Saleh, Manal Abdel Wahed · Journal of Engineering and Applied Science (2024) | TGRS Research Map | TGRS