Association Between Anesthesia Provider Education and Carbon Footprint Related to the Use of Inhaled Halogenated Anesthetics

Clinician and health service interventions to reduce the greenhouse gas emissions generated by healthcare: a systematic review

OBJECTIVE

To synthesise the available evidence on the effects of interventions designed to improve the delivery of healthcare that reduces the greenhouse gas (GHG) emissions of healthcare.

DESIGN

Systematic review and structured synthesis.

SEARCH SOURCES

Cochrane Central Register of Controlled Trials, PubMed, Web of Science and Embase from inception to 3 May 2023.

SELECTION CRITERIA

Randomised, quasi-randomised and non-randomised controlled trials, interrupted time series and controlled or uncontrolled before-after studies that assessed interventions primarily designed to improve the delivery of healthcare that reduces the GHG emissions of healthcare initiated by clinicians or healthcare services within any setting.

MAIN OUTCOME MEASURES

Primary outcome was GHG emissions. Secondary outcomes were financial costs, effectiveness, harms, patient-relevant outcomes, engagement and acceptability.

DATA COLLECTION AND ANALYSIS

Paired authors independently selected studies for inclusion, extracted data, and assessed risk of bias using a modified checklist for observational studies and the certainty of the evidence using Grades of Recommendation, Assessment, Development and Evaluation. Data could not be pooled because of clinical and methodological heterogeneity, so we synthesised results in a structured summary of intervention effects with vote counting based on direction of effect.

RESULTS

21 observational studies were included. Interventions targeted delivery of anaesthesia (12 of 21), waste/recycling (5 of 21), unnecessary test requests (3 of 21) and energy (1 of 21). The primary intervention type was clinician education. Most (20 of 21) studies were judged at unclear or high risk of bias for at least one criterion. Most studies reported effect estimates favouring the intervention (GHG emissions 17 of 18, costs 13 of 15, effectiveness 18 of 20, harms 1 of 1 and staff acceptability 1 of 1 studies), but the evidence is very uncertain for all outcomes (downgraded predominantly for observational study design and risk of bias). No studies reported patient-relevant outcomes other than death or engagement with the intervention.

CONCLUSIONS

Interventions designed to improve the delivery of healthcare that reduces GHG emissions may reduce GHG emissions and costs, reduce anaesthesia use, waste and unnecessary testing, be acceptable to staff and have little to no effect on energy use or unintended harms, but the evidence is very uncertain. Rigorous studies that measure GHG emissions using gold-standard life cycle assessment are needed as well as studies in more diverse areas of healthcare. It is also important that future interventions to reduce GHG emissions evaluate the effect on beneficial and harmful patient outcomes.

PROSPERO REGISTRATION NUMBER

CRD42022309428.

Electricity consumption of anesthesia workstations and potential emission savings by avoiding standby

BACKGROUND

Anesthesiology has a relevant carbon footprint, mainly due to volatile anesthetics (scope 1 emissions). Additionally, energy used in the operating theater (scope 2 emissions) contributes to anesthesia-related greenhouse gas (GHG) emissions.

OBJECTIVES

Optimizing the electricity use of medical devices might reduce both GHG emissions and costs might hold potential to reduce anaesthesia-related GHG-emissions and costs. We analyzed the electricity consumption of six different anesthesia workstations, calculated their GHG emissions and electricity costs and investigated the potential to reduce emissions and cost by using the devices in a more efficient way.

METHODS

Power consumption (active power in watt , W) was measured with the devices off, in standby mode, or fully on with the measuring instrument SecuLife ST. Devices studied were: Dräger Primus, Löwenstein Medical LeonPlus, Getinge Flow C, Getinge Flow E, GE Carestation 750 and GE Aisys. Calculations of GHG emissions were made with different emission factors, ranging from very low (0.09 kg CO2-equivalent/kWh) to very high (0.660 kg CO2-equivalent/kWh). Calculations of electricity cost were made assuming a price of 0.25 € per kWh.

RESULTS

Power consumption during operation varied from 58 W (GE CareStation 750) to 136 W (Dräger Primus). In standby, the devices consumed between 88% and 93% of the electricity needed during use. The annual electricity consumption to run 96 devices in a large clinical department ranges between 45 and 105 Megawatt-hours (MWh) when the devices are left in standby during off hours. If 80% of the devices are switched off during off hours, between 20 and 46 MWh can be saved per year in a single institution. At the average emission factor of our hospital, this electricity saving corresponds to a reduction of GHG emissions between 8.5 and 19.8 tons CO2-equivalent. At the assumed prices, a cost reduction between 5000 € and 11,600 € could be achieved by this intervention.

CONCLUSION

The power consumption varies considerably between the different types of anesthesia workstations. All devices exhibit a high electricity consumption in standby mode. Avoiding standby mode during off hours can save energy and thus GHG emissions and cost. The reductions in GHG emissions and electricity cost that can be achieved with this intervention in a large anesthesiology department are modest. Compared with GHG emissions generated by volatile anesthetics, particularly desflurane, optimization of electricity consumption of anesthesia workstations holds a much smaller potential to reduce the carbon footprint of anesthesia; however, as switching off anesthesia workstations overnight is relatively effortless, this behavioral change should be encouraged from both an ecological and economical point of view.

Reducing the carbon footprint of general anaesthesia: a comparison of total intravenous anaesthesia vs. a mixed anaesthetic strategy in 47,157 adult patients

Global warming is a major public health concern. Volatile anaesthetics are greenhouse gases that increase the carbon footprint of healthcare. Modelling studies indicate that total intravenous anaesthesia is less carbon intensive than volatile anaesthesia, with equivalent quality of care. In this observational study, we aimed to apply the findings of previous modelling studies to compare the carbon footprint per general anaesthetic of an exclusive TIVA strategy vs. a mixed TIVA-volatile strategy. This comparative retrospective study was conducted over 2 years in two French hospitals, one using total intravenous anaesthesia only and one using a mixed strategy including both intravenous and inhalation anaesthetic techniques. Based on pharmacy procurement records, the quantity of anaesthetic sedative drugs was converted to carbon dioxide equivalents. The primary outcome was the difference in carbon footprint of hypnotic drugs per intervention between the two strategies. From 1 January 2021 to 31 December 2022, 25,137 patients received general anaesthesia in the hospital using the total intravenous anaesthesia strategy and 22,020 in the hospital using the mixed strategy. The carbon dioxide equivalent footprint of hypnotic drugs per intervention in the hospital using the total intravenous anaesthesia strategy was 20 times lower than in the hospital using the mixed strategy (emissions of 2.42 kg vs. 48.85 kg carbon dioxide equivalent per intervention, respectively). The total intravenous anaesthesia strategy significantly reduces the carbon footprint of hypnotic drugs in general anaesthesia in adult patients compared with a mixed strategy. Further research is warranted to assess the risk-benefit ratio of the widespread adoption of total intravenous anaesthesia.