Optimized Wayfinding Signage Positioning in Hospital Built Environment through Medical Data and Flows Simulations
Author(s): |
Weihong Guo
Yiwei He |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 16 September 2022, n. 9, v. 12 |
Page(s): | 1426 |
DOI: | 10.3390/buildings12091426 |
Abstract: |
This study argues that medical data should be better utilized and attention should be paid to the patient’s visual experience during their journey to the emergency department (ED). Wayfinding in medical settings remains a challenge for patients. One reason is that decision makers do not adequately understand what the patients have seen and been through during their journey in the ED built environment, which leads to inaccurate selection and misplacement of signage. This study claims that there is still room to optimize existing wayfinding design methods. This study selected a representative large-scale general hospital in China, collected the annual healthcare information system (HIS) data of ED patients in 2021, and reproduced the clinical process of ED patients in the form of a probability treemap through categorical analysis. Furthermore, Massmotion was used to simulate the patient’s journey and obtain their vision focus area (VFA). With the VFA and field observation record, the research targeted 17 wall surfaces in the ED built environment. On the basis of the comparative analysis, we found the misplacement of the current signage system and the direction of future optimization. This method can provide a reference for designers during their decision-making process to aim for an efficient wayfinding system. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10692679 - Published on:
23/09/2022 - Last updated on:
10/11/2022