The Triple Bottom Line and Stabilization Wedges: A Framework for Perioperative Sustainability

Carbon Footprint of Total Intravenous and Inhalation Anesthesia in the Transcatheter Aortic Valve Replacement Procedure

OBJECTIVES

To quantify and compare the emissions for deep sedation with total intravenous anesthesia (TIVA) and general anesthesia with inhaled agents during the transcatheter aortic valve replacement procedure.

DESIGN

A retrospective study.

SETTING

A tertiary hospital in Boston, Massachusetts.

PARTICIPANTS

The anesthesia records of 604 consecutive patients who underwent the transcatheter aortic valve replacement procedure between January 1, 2018, and March 31, 2022, were reviewed and analyzed.

INTERVENTIONS

Data were examined and compared in the following 2 groups: general anesthesia with inhaled agents and deep sedation with TIVA.

MEASUREMENTS AND MAIN RESULTS

The gases, drugs, airway management devices, and anesthesia machine electricity were collected and converted into carbon dioxide emissions (CO2e). The carbon emissions of intravenous medications were converted with the CO2e data for anesthetic pharmaceuticals from the Parvatker et al. study. For inhaled agents, inhaled anesthetics and oxygen/air flow rate were collected at 15-minute intervals and calculated using the anesthetic gases calculator provided by the Association of Anesthetists. The airway management devices were converted based on life-cycle assessments. The electricity consumed by the anesthesia machine during general anesthesia was estimated from the manufacturer's data (Dräger, GE) and local Energy Information Administration data. The data were analyzed in the chi-squared test or Wilcoxon rank-sum test. There were no significant differences in the patients' demographic characteristics, such as age, sex, weight, height, and body mass index. The patients who received general anesthesia with inhaled agents had statistically higher total CO2e per case than deep sedation with TIVA (16.188 v 1.518 kg CO2e; p < 0.001), primarily due to the inhaled agents and secondarily to airway management devices. For deep sedation with TIVA, the major contributors were intravenous medications (71.02%) and airway management devices (16.58%). A subgroup study of patients who received sevoflurane only showed the same trend with less variation.

CONCLUSIONS

The patients who received volatile anesthesia were found to have a higher CO2e per case. This difference remained after a subgroup analysis evaluating those patients only receiving sevoflurane and after accounting for the differences in the duration of anesthesia. Data from this study and others should be collectively considered as the healthcare profession aims to provide the best care possible for their patients while limiting the harm caused to the environment.

How we can reduce the environmental impact of our operating theatres: a narrative review

Climate change is projected to become the leading cause of adverse health outcomes globally, and the healthcare system is a key contributor. Surgical theatres are three to six times more pollutant than other hospital areas, and produce anywhere from a fifth to a third of total hospital waste. Hospitals are increasingly expected to make operating theatres more sustainable, however guidelines to improve environmental sustainability are lacking, and previous research takes a narrow approach to operative sustainability. This paper presents a narrative review that, following a 'review of reviews' approach, aims to summarize the key recommendations to improve the environmental sustainability of surgical theatres. Key domains of discussion identified across the literature included minimisation of volatile anaesthetics, reduction of operating theatre power consumption, optimisation of surgical approach, re-use and re-processing of surgical instruments, waste management, and research, education and leadership. Implementation of individual items in these domains has seen significant reductions in the environmental impact of operative practice. This comprehensive summary of recommendations lays the framework from which providers can assess the sustainability of their practice and for the development of encompassing guidelines to build an environmentally sustainable surgical service.

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.

Environmental Impact and Cost Savings of Operating Room Quality Improvement Initiatives: A Scoping Review

BACKGROUND

Operating rooms are major contributors to a hospital's carbon footprint due to the large volumes of resources consumed and waste produced. The objective of this study was to identify quality improvement initiatives that aimed to reduce the environmental impact of the operating room while decreasing costs.

STUDY DESIGN

A literature search was performed using PubMed, Scopus, CINAHL, and Google Scholar and included broad terms for "operating room," "costs," and "environment" or "sustainability." The "triple bottom line" framework, which considers the environmental, financial, and social impacts of interventions to guide decision making, was used to inform data extraction. The studies were then categorized using the 5 "Rs" of sustainability-refuse, reduce, reuse, repurpose, and recycle-and the impacts were discussed using the triple bottom line framework.

RESULTS

A total of 23 unique quality improvement initiatives describing 28 interventions were included. Interventions were categorized as "refuse" (n = 11; 39.3%), "reduce" (n = 8; 28.6%), "reuse" (n = 3; 10.7%), and "recycle" (n = 6; 21.4%). While methods of measuring environmental impact and cost savings varied greatly among studies, potential annual cost savings ranged from $873 (intervention: education on diverting recyclable materials from sharps containers; environmental impact: 11.4 kg sharps waste diverted per month) to $694,141 (intervention: education to reduce regulated medical waste; environmental impact: 30% reduction in regulated medical waste).

CONCLUSIONS

Quality improvement initiatives that reduce both cost and environmental impact have been successfully implemented across a variety of centers both nationally and globally. Surgeons, healthcare practitioners, and administrators interested in environmental stewardship and working toward a culture of sustainability may consider similar interventions in their institutions.