Hospital energy performance: New indicators for UK National Health Service estate

Abstract

In 1991 the UK Audit Commission produced energy performance indicators for hospitals based on the type of care provided. However, an analysis of over 100 hospitals throughout the United Kingdom has found the type of care provided to have relatively little effect on the energy performance of hospitals. Although other factors influenced energy use to some degree, the major factor affecting performance was found to be the plan of the hospital, as this influenced the amount of mechanical ventilation required. Modem mechanically ventilated hospitals were found to typically use 40% of their total electricity consumption in fan power, equating to 80 kWh m -2 purely due to fans. This paper presents a suggested set of new performance indicators based on the percentage of floor area which is ventilated mechanically.List of symbols YEPI Electricity performance indicator for site YFFPI Fossil fuel performance indicator for site X%.B1V

Environmental sustainability in hospitals – a systematic review and research agenda

“…13 Energy usage per unit area (m 2 ) for hospitals is the second highest for all building types, 14 but varies considerably between hospitals depending on design. 15 Most modern hospitals are built on a deep-plan design (with a large distance from the centre to the periphery), requiring high electricity consumption for ventilation of the building’s core. 15…”

“…15 Most modern hospitals are built on a deep-plan design (with a large distance from the centre to the periphery), requiring high electricity consumption for ventilation of the building’s core. 15…”

Introduction to neural network analysis and its application to building services engineering

“…Williams et al 30 investigated energy consumption in hospitals. Published performance indicators for electricity and fossil fuel for 200 hospitals in the UK suggested that many factors affected fossil fuel and electricity consumption.…”

“…This could be achieved by training neural networks using variables such as the type of building, the age of the building (building fabric), the percentage floor area mechanically ventilated, and also other variables such as type of health facilities provided and other quantities that cannot be factored into a linear regression analysis. Results of the study presented by Williams et al 30 indicated that predictive models using conventional linear regression analysis produce fairly inaccurate predictions with an R 2 value of only 0.47. This may be greatly improved upon by the use of a nonlinear model such as that based on a neural network.…”

Assessment of a Nurse Led Energy Behavior Change Intervention in an NHS Community Hospital Ward

“…A thorough literature review on 'energy in healthcare' highlighted a number of academic publications on the topic [9,11]. These articles predominately focus on direct hospital energy usage from reported healthcare accounts [17][18][19], identification of the highest energy use activities and equipment within hospitals [20][21][22] and, retrofitting and designing sustainable healthcare buildings [7,14,22,23]. There are a number of academic publications that report on the topic of 'pro-environmental behavior in hospitals' [14,24].…”