Factors influencing the design of spatial layouts in healthcare buildings

There has been a significant increase in capital building programmes in the National Health Service (NHS) since the publication in 2000 of the Government policy on modernisation of health and care delivery in the UK. With regard to physical capacity, the target was to create over 100 new hospitals by 2010 and 500 new one-stop primary care centres. The initiative was seen as a way to modernise the physical facilities as well as the key health and care delivery activities that take place in and around them. Space layout design is considered as one of the primordial activities in a building’s lifecycle and impacts on the ‘human to environment’ and ‘human to human’ interactions. It is, therefore, essential to understand the factors that influence the design and outcome of space layouts, in particular in healthcare buildings because of the complex functional relationships that exist between the activities. A comprehensive review of the factors related to space layout design in healthcare facilities have been undertaken in this research. The findings suggest that the developments in healthcare and allied fields have implications for the design of space layouts and the resulting buildings and are as important as some of the functional aspects such as efficiency and productivity. The other notable factors can be attributed to the need to mitigate the impacts of, as well as adapt to, the global climate change

Applying desirability functions to preference modelling in low-energy building design optimization

Building performance optimization is a valuable aid to design decision-making. Most existing research takes an ‘a posteriori’ approach, where stakeholder preferences are considered after deriving optimised results. Whilst this approach yields technically optimal solutions, it overlooks sub-optimal solutions that still satisfy stakeholder preferences. This research develops a technique to incorporate preferences into optimization by applying a “desirability function” to each criterion for multiple stakeholders. The approach enables the tradeoffs between decision-makers to be visualised as a Pareto frontier and aids “democratic” decision-making. Hence, incorporating preferences in advance of optimization may increase the likelihood of finding a desirable solution