Clinical Decision Support to Reduce Greenhouse Gas Emissions

Using Clinical Decision Support Tools to Reduce the Impact of Greenhouse Gas Emissions in Anesthesia

Role of Health Care in Environmental Sustainability

The interaction between environmental pollution and public health has been gaining increasing recognition in recent times, especially in relation to cardiovascular and infectious diseases. (Khraishah, et al., 2022) (Cyril, Marie, & E., 2019) The World Health Organization considers climate change to be “the single biggest health threat facing humanity” and “…threatens to undo the last fifty years of progress in development, global health, and poverty reduction, and to further widen existing health inequalities between and within populations.” (World Health Organization, 2021) Healthcare delivery systems play a significant role in the problem accounting for as much as 5% of greenhouse gas (GHG) emissions globally. (Smith, Zurynski, & Braithwaite, 2022) (Coiera & Magrabi, 2022) The national percentage of GHG emissions resulting from US healthcare is almost 9%. (Sittig, Sherman, Eckelman, Draper, & Singh, 2022) Given these figures, it’s not surprising that greater attention and focus are being placed on ways to reduce the sector’s environmental impact. The field of clinical informatics can play a pivotal role in this mission. The Journal of the American Medical Informatics Association (JAMIA) devoted a special issue to exploring the role that clinical informatics can play in addressing the “climate disaster”. (Coiera & Magrabi, 2022) Operating rooms generate roughly one-third of a hospital’s total waste and inhaled anesthetic gases alone constitute 5% of hospital GHG emissions. (Van Norman & Jackson, 2020) The American Society of Anesthesiology (ASA) has focused efforts on reducing the climate footprint associated with the delivery of anesthesia care. Their Task Force on Environmental Sustainability Committee on Equipment and Facilities created an educational document educating providers on components of a sustainable anesthetic practice. The Inhaled Anesthetic 2023 Challenge seeks to decrease anesthetic carbon emissions by 50% and provides access to a number of resources and tools to accomplish this. (ASA Committee on Equipment and Facilities, 2023)

Anesthesia and Greenhouse Gas Emissions

Although there are different approaches and variations, the base of a general anesthetic technique during the maintenance phase is usually accomplished with the use of anesthetic gases or the infusion of an intravenous medication such as propofol. The environmental impacts of these two approaches are quite different. Sherman, Lammers, and Eckelman performed a lifecycle analysis of anesthetic medications in 2012. Of all the agents, propofol had the best environmental sustainability profile. Unfortunately, volatile anesthetics and nitrous oxide are all very potent GHG. Since anesthetic gases are not significantly metabolized by the body, if they are not sequestered when exhaled, they ultimately get wasted into the atmosphere. (Sherman, Le, Lamers, & Eckelman, 2012) While systems to capture and or destroy anesthetic waste gases do exist, they are still not widely available and may not be cost effective. (Van Norman & Jackson, 2020) The agents with the worst environmental impact are Desflurane and Nitrous Oxide. (Van Norman & Jackson, 2020) (Sherman, Le, Lamers, & Eckelman, 2012) Generally, avoidance of these agents in favor of Sevoflurane or Isoflurane is beneficial. (Van Norman & Jackson, 2020) Various strategies exist to reduce the amount of anesthetic gas waste. One such approach is to utilize a technique called “low flow” anesthesia. “Low flow” refers to the fresh gas flow (FGF) that acts as a carrier, delivering anesthetic gas/agent to the patient. Use of a lower FGF decreases the amount of anesthetic gases utilized and ultimately excreted to the atmosphere. Cost reduction is an added benefit. (Epstein, Dexter, Maguire, Agarwalla, & Gratch, 2016) No standard definition exists for what constitutes a low flow, but generally it refers to FGF less than or equal to 1 L/min. (Shah, et al., 2023) This technique is utilized during the period of the surgical procedure as higher flows are needed to achieve a steady state after anesthetic induction and during emergence from anesthesia. Adoption of this technique requires sustained behavior change on the part of anesthesia providers which has not always been easy to achieve. Contributing factors include items such as a lack of awareness of the environmental impacts of anesthetic gases on the part of anesthesia providers, the convenience of use of nitrous oxide in facilitating a faster emergence from anesthesia, concerns with using low flows due to it being an “off label” use when used with Sevoflurane, habit, and clinical scenarios when higher flows are needed. (Shah, et al., 2023) (Ramaswamy, et al., 2022) The FDA recommendation with respect to gas flows and Sevoflurane relate to a concern regarding the potential for toxicity due to a reaction with Sevoflurane and certain types of CO2 absorbents which are used in anesthesia. These absorbents allow for the recycling of anesthetic gases by reacting with the carbon dioxide produced by the body, removing it from the breathing circuit. When the absorbent is composed of a strong hydroxide base and interacts with Sevoflurane, the creation of a substance referred to as Compound A can be formed as a degradation product. This substance was found to carry a risk for renal toxicity in rats. (Shah, et al., 2023) (Epstein, Dexter, Maguire, Agarwalla, & Gratch, 2016) Notably, a clinically relevant toxicity has not been observed in humans and currently newer CO2 absorbents don’t produce this byproduct. (Epstein, Dexter, Maguire, Agarwalla, & Gratch, 2016) (Shah, et al., 2023)

Influencing Provider Behavior through Education

Effecting long-term behavior change is not easy. The first step is education. An study by Shah et al described the results of a survey sent to anesthesia departmental members at five medical centers in the University of California health system demonstrated some interesting findings. Although most respondents were able to identify Desflurane as the anesthetic agent with the worst environmental impact, 48% of respondents endorsed using this agent at FGF ≥ 1L/min. Also, attending physicians were more aware of the financial issues surrounding the use of anesthetic agents compared to their environmental impact. (Shah, et al., 2023) Educational efforts can significantly impact provider utilization of low flow techniques and the volumes of anesthetic agents utilized. However, these outcomes are not always durable. (Nair, et al., 2013) Attempts to solidify these achievements have led to efforts which leverage the capabilities of clinical decision support tools.

Use of Clinical Decision Support in Changing Provider Behavior

The last decade has seen an evolution in the utilization of clinical decision support to effect the behavior change needed to lessen the environmental impact of anesthetic gases. Initial publications involved the use of custom created decision support programs that worked in conjunction with the institution’s anesthesia information management systems (AIMS). (Nair, et al., 2013) (Epstein, Dexter, & Patel, 2015) For example, the publication by Nair et al utilized a decision support system tool named “Smart Anesthesia Manager” that provided near real-time, “pop-up” alerts beginning ten minutes after surgical incision and incisional closure. Their alert complied with the FDA recommendations regarding Sevoflurane and fired if FGF were greater than 1 L/min. Providers were able to disable the alert if they documented a clinical reason why higher FGF needed to be used. To demonstrate the effect of the CDS system, the alert was cycled. After an initial period of being present it was disabled for two months and later reinstated. The CDS had an impressive effect, producing a significant reduction in FGF in both periods when active. A reversion to towards the initial baseline mean FGF was noted when the CDS tool was inactivated. The use of the system created an estimated ~ $105,000 annual savings in volatile anesthetic costs. (Nair, et al., 2013) CDS tools do not necessarily need to be interruptive or work in real time to be effective. Epstein, Dexter, and Patel also utilized a custom coded solution to interface with their AIMS and effect a reduction in mean weighted FGF utilization. (Epstein, Dexter, & Patel, 2015) Rather than provide interruptive alerts, anesthesia providers received an email at 4 week increments based on the last ten cases they had performed in that period identifying their average FGF and their deviation or compliance with respect to the target. This approach was effective in achieving a significant reduction in FGF utilization. More recent work has demonstrated the feasibility and utility of utilizing the CDS tools available in commercial integrated electronic health records. Olmos et al described the creation of a CDS tool working within the Epic EHR through the Best Practice Advisory framework. (Olmos, Robinowitz, Feiner, Chen, & Gandhi, 2023) Their real-time interruptive tool targeted a FGF of > 1 L/min for Sevoflurane and >0.7 L/min for Isoflurane and Desflurane. The tools could be snoozed or dismissed by the provider. It was later modified in response to feedback to become non-interruptive. Their BPA effectively decreased FGF for Sevoflurane and Isoflurane. They estimated an annual volatile anesthetic cost savings of $123,120 for 2019. Ramaswamy et al expanded on this work with the creation of a “FGF CDS toolkit” compatible with the Best Practice Alert framework available in the Epic EHR. (Ramaswamy, et al., 2022) The toolkit was rolled out to five systems across the UC Health network. Each health system had the ability to modify the details of the alert with respect to if the alert was interruptive or not and what gas flows were targeted. Overall, this body of work demonstrates the utility, flexibility, and scalability of CDS in addressing sustainability concerns in anesthesiology.

References

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4. Epstein, R. H., Dexter, F., Maguire, D. P., Agarwalla, N. K., & Gratch, D. M. (2016). Economic and Environmental Considerations During Low Fresh Gas Flow Volatile Agent Administration After Change to a Nonreactive Carbon Dioxide Absorbent. Anesth Analg, 122, 996-1006.

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7. Olmos, A. V., Robinowitz, D., Feiner, J. R., Chen, C. L., & Gandhi, S. (2023). Reducing Volatile Anesthetic Waste Using a Commercial Electronic Health Record Clinical Decision Support Tool to Lower Fresh Gas Flows. Anesth Analg, 136, 327–37.

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9. Shah, A. C., Przybysz, A. J., Wang, K., Jones, I. A., Manuel, S. P., Dayal, R., . . . Gandhi, S. (2023). Knowledge Gaps in Anesthetic Gas Utilization in a Large Academic Hospital System: A Multicenter Survey. Cureus, 15(3), e35868.

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13. Smith, C. L., Zurynski, Y., & Braithwaite, J. (2022). We can’t mitigate what we don’t monitor: using informatics to measure and improve healthcare systems’ climate impact and environmental footprint. Journal of the American Medical Informatics Association, 29 (12), 2168–2173.

14. Van Norman, G. A., & Jackson, S. (2020). The anesthesiologist and global climate change: an ethical obligation to act. Curr Opin Anesthesiol, 33, 577-583. World Health Organization. (2021, 10 30). Climate change and health. Retrieved 5 4, 2023, from World Health Organization: https://www.who.int/news-room/fact-sheets/detail/climate-change-and-health

Submitted by (Reem Khatib)