A S Pollard1, J J Paddle2, T J Taylor3, A Tillyard2. 1. European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, RCH Treliske, Truro TR1 3HD, UK; Royal Cornwall Hospitals NHS Trust, Truro TR1 3LJ, Cornwall, UK; Pollard Systems Ltd, Mevagissey, Cornwall PL26 6TL, UK. 2. Royal Cornwall Hospitals NHS Trust, Truro TR1 3LJ, Cornwall, UK. 3. European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, RCH Treliske, Truro TR1 3HD, UK. Electronic address: timothy.j.taylor@exeter.ac.uk.
Abstract
OBJECTIVES: Climate change has the potential to threaten human health and the environment. Managers in healthcare systems face significant challenges to balance carbon mitigation targets with operational decisions about patient care. Critical care units are major users of energy and hence more evidence is needed on their carbon footprint. STUDY DESIGN: The authors explore a methodology which estimates electricity use and associated carbon emissions within a Critical Care Unit (CCU). METHODS: A bottom-up model was developed and calibrated which predicted the electricity consumed and carbon emissions within a CCU based on the type of patients treated and working practices in a case study in Cornwall, UK. RESULTS: The model developed was able to predict the electricity consumed within CCU with an error of 1% when measured against actual meter readings. Just under half the electricity within CCU was used for delivering care to patients and monitoring their condition. CONCLUSIONS: A model was developed which accurately predicted the electricity consumed within a CCU based on patient types, medical devices used and working practice. The model could be adapted to enable it to be used within hospitals as part of their planning to meet carbon reduction targets.
OBJECTIVES: Climate change has the potential to threaten human health and the environment. Managers in healthcare systems face significant challenges to balance carbon mitigation targets with operational decisions about patient care. Critical care units are major users of energy and hence more evidence is needed on their carbon footprint. STUDY DESIGN: The authors explore a methodology which estimates electricity use and associated carbon emissions within a Critical Care Unit (CCU). METHODS: A bottom-up model was developed and calibrated which predicted the electricity consumed and carbon emissions within a CCU based on the type of patients treated and working practices in a case study in Cornwall, UK. RESULTS: The model developed was able to predict the electricity consumed within CCU with an error of 1% when measured against actual meter readings. Just under half the electricity within CCU was used for delivering care to patients and monitoring their condition. CONCLUSIONS: A model was developed which accurately predicted the electricity consumed within a CCU based on patient types, medical devices used and working practice. The model could be adapted to enable it to be used within hospitals as part of their planning to meet carbon reduction targets.