Lessons Learnt from Testing Three Spatial Observation Tools in a Hospital Ward.

Abstract

Observation tools are increasingly important in healthcare building design research. They enable us to understand how the design of healthcare buildings affects users' health and organisational outcomes. Observations are used in case studies and pre- and post-occupancy evaluations. However, these case studies often struggle to pinpoint the specific design features responsible for observed outcomes. Additionally, harnessing collective knowledge from multiple cases can be challenging. This underscores the need for structured observations. The paper describes the lessons learnt from using three spatial observation tools as part of a study to assess a hospital ward design. Its goal is to reflect on the purpose, usability, advantages, disadvantages, and future improvements of these tools and to offer insights into their potential to support research on hospital ward design. The first tool, by the Centre for Health Design, utilizes a checklist-style matrix to evaluate the design of patient rooms, assessing 17 Evidence Based Design goals, including patient safety, worker safety and effectiveness, quality of care, patient experience, and organizational performance. The second tool is a one-time observation tool, a structured spatial inventory aimed at documenting design features throughout the entire hospital ward, covering elements such as room size, access to daylight, natural elements, furniture, safety measures, and more. It can be combined with the third tool; the recurring observation tool, which focuses on monitoring usage, users, their activities, and behaviour across various types of environments, including patient, staff, care, and supportive spaces. The last two observation tools were developed for the research project, adapting the Smart Sustainable Offices method for healthcare environments. This paper emphasizes the importance of selecting suitable observation tools for specific research objectives, providing guidance for working with observations and conducting pre-and post-studies. While not aimed at validating observation tools, it offers reflections to aid in development and use of observation tools. Finally, documenting spatial contexts enhances understanding of study findings, and reusing observation tools enables cross-study comparisons, with future potential for leveraging artificial intelligence.