Supplementum 292: Abstracts Swiss Anaesthesia 2025, joint annual congress of the Swiss Society for Anaesthesiology and Perioperative Medicine and the Swiss Association for Anaesthesia Care (Lausanne, Switzerland, November 6−8, 2025)

Background: Climate change is a pressing global health threat, with the Swiss healthcare sector contributing approximately 6.7% of national greenhouse gas (GHG) emissions.Volatile anesthetics such as sevoflurane significantly contribute to these emissions.One promising strategy to reduce their environmental impact involves minimizing fresh gas flow rates through automated control systems such as EcoFlow.Objective: This quality control study evaluated the impact of implementing EcoFlow technology -combined with structured staff training -on sevoflurane consumption, associated costs, and CO2-equivalent emissions in a large urban hospital setting.We hypothesized that EcoFlow would reduce sevoflurane use by at least 33%.Methods: A prospective before-during-after (B-D-A) analysis was conducted at Stadtspital Zrich from December 2024 to February 2025.Adult patients undergoing elective surgery under general anesthesia with sevoflurane were included.The intervention involved the use of EcoFlow, a clinical decision support tool integrated into anesthesia machines.Primary outcomes were sevoflurane consumption (mL/min), financial expenditure (CHF), and estimated CO2 emissions based on GWP100 values.Results: A total of 92 patients were analyzed (B: n = 34; D: n = 35; A: n = 23).During the EcoFlow phase, sevoflurane consumption decreased by 37.04%, with corresponding reductions in CO2 emissions (25.56%) and cost (26.09%).After discontinuation, agent use increased slightly but remained below baseline, indicating a sustained behavioral impact.High correlations (r = 0.99) were observed between agent use, emissions, and cost.National extrapolations suggest a potential reduction of 1,783 metric tons of CO2 annually representing a 37% drop in sevoflurane-related emissions. Conclusion:EcoFlow technology significantly reduced sevoflurane use, environmental emissions, and cost without compromising clinical care.Behavioral changes persisted beyond the intervention phase, underscoring the potential for long-term impact.Integrating intelligent automation into anesthesia practice offers a scalable pathway to achieving climate targets within healthcare.