JOURNAL ARTICLE
Daylighting and Patients' Access to View Assessment in the Palestinian Hospitals' ICUs.
Published In: Health Environments Research & Design Journal (HERD) (Sage Publications, Ltd.), 2025, v. 18, n. 2. P. 221 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Amleh, Deema; Halawani, Abdelrahman; Haj Hussein, Muhannad; Alamlih, Laith 3 of 3
Abstract
This article focuses on assessing daylight availability and patients' access to views in intensive care units (ICUs) of Palestinian hospitals, highlighting their importance for patient wellness and healthcare staff satisfaction. The study evaluated five tertiary hospitals using daylight factor (DF) measurements, architectural analysis, and interviews with medical staff, finding that most ICU designs fail to provide adequate natural light or views, with average DF values below the recommended 3% and limited or no access to outside views. These deficiencies are linked to increased patient delirium, sleep disorders, and staff dissatisfaction, reflecting a lack of standardized design guidelines and insufficient involvement of medical experts in ICU planning. The authors recommend establishing binding local standards to optimize window size, placement, glazing, and bed orientation to enhance daylight exposure and views, aligning with international guidelines from the Facilities Guidelines Institute and the Society of Critical Care Medicine.
Additional Information
- Source:Health Environments Research & Design Journal (HERD) (Sage Publications, Ltd.). 2025/04, Vol. 18, Issue 2, p221
- Document Type:Article
- Subject Area:Environmental Sciences
- Publication Date:2025
- ISSN:1937-5867
- DOI:10.1177/19375867251317242
- Accession Number:184910112
- Copyright Statement:Copyright of Health Environments Research & Design Journal (HERD) (Sage Publications, Ltd.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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