An Accessible Clinical Decision Support System to Curtail Anesthetic Greenhouse Gases in a Large Health Network: Implementation Study

Abstract

Background Inhaled anesthetics in the operating room are potent greenhouse gases and are a key contributor to carbon emissions from health care facilities. Real-time clinical decision support (CDS) systems lower anesthetic gas waste by prompting anesthesia professionals to reduce fresh gas flow (FGF) when a set threshold is exceeded. However, previous CDS systems have relied on proprietary or highly customized anesthesia information management systems, significantly reducing other institutions’ accessibility to the technology and thus limiting overall environmental benefit. Objective In 2018, a CDS system that lowers anesthetic gas waste using methods that can be easily adopted by other institutions was developed at the University of California San Francisco (UCSF). This study aims to facilitate wider uptake of our CDS system and further reduce gas waste by describing the implementation of the FGF CDS toolkit at UCSF and the subsequent implementation at other medical campuses within the University of California Health network. Methods We developed a noninterruptive active CDS system to alert anesthesia professionals when FGF rates exceeded 0.7 L per minute for common volatile anesthetics. The implementation process at UCSF was documented and assembled into an informational toolkit to aid in the integration of the CDS system at other health care institutions. Before implementation, presentation-based education initiatives were used to disseminate information regarding the safety of low FGF use and its relationship to environmental sustainability. Our FGF CDS toolkit consisted of 4 main components for implementation: sustainability-focused education of anesthesia professionals, hardware integration of the CDS technology, software build of the CDS system, and data reporting of measured outcomes. Results The FGF CDS system was successfully deployed at 5 University of California Health network campuses. Four of the institutions are independent from the institution that created the CDS system. The CDS system was deployed at each facility using the FGF CDS toolkit, which describes the main components of the technology and implementation. Each campus made modifications to the CDS tool to best suit their institution, emphasizing the versatility and adoptability of the technology and implementation framework. Conclusions It has previously been shown that the FGF CDS system reduces anesthetic gas waste, leading to environmental and fiscal benefits. Here, we demonstrate that the CDS system can be transferred to other medical facilities using our toolkit for implementation, making the technology and associated benefits globally accessible to advance mitigation of health care–related emissions.

Advances in Clinical Decision Support Systems: Contributions from the 2022 Literature

“…Wu et al conducted an implementation effectiveness trial for examining the clinical impact of patient-oriented and provider-facing CDS report for health risk assessment [7]. Notably, one study demonstrated the scalability and transferability of a CDS system to reduce anesthetic gas waste [8], innovatively linking informatics solutions to environmental impact.…”

“…Structural aspects include the type of CDS and clinical setting where the CDS was deployed or studied. Six studies included domain-specific systems such as an electronic alert to notify prescribers about inappropriate red blood cell and platelet transfusion [6]; a patient-specific CDS report for disease prevention and surveillance in the primary care setting [7]; a non-interruptive alert in anesthesia to reduce fresh gas flow when a predefined threshold was exceeded [8]; a real-time text message alert when antimicrobial therapy was inappropriate (i.e., an antimicrobial agent-pathogen mismatch with a positive blood culture result) [9]; a guideline-based CDS for maternal health [10]; and a microRNA-based thyroid molecular…”

A race to net zero—early lessons from healthcare's decarbonization marathon

“…For example, individual hospital systems, such as University of California–San Francisco (UCSF) hospitals and Yale University Hospital, are utilizing electronic health records to change the type of and reduce the flow rate of anesthetic gases. 33 , 34 On the national level, Practice GreenHealth (a nonprofit collaborative focused on developing environmentally conscious solutions for healthcare) facilitates multiorganizational collaborations in running pilots and scaling efforts. 38 Additionally, many case examples also document clear financial incentives and outcomes (such as the cost savings cited by CommonSpirit and Kaiser).…”

JMIR Perioperative Medicine: A Global Journal for Publishing Interdisciplinary Innovations, Research, and Perspectives

“…Artificial intelligence and machine learning, which seemed quixotic years ago, have made an unexpectedly large leap with several potential applications, such as reducing medication errors, perioperative risk assessment, early detection of clinical deterioration, predicting postoperative morbidity and mortality, streamlining workflows, creating personalized care pathways, real-time image analysis, providing clinical decision support, analysis of structured and unstructured data in electronic health records, or understanding health disparities [10][11][12]. Experts in perioperative medicine are investigating a broad range of topics-from sustainability and the carbon footprint of surgeries to taking a deeper dive into precision medicine using omics and biomarkers [13]. Some of these discoveries and research will reduce inequities and improve surgical safety on a global scale while others may improve outcomes and care delivery locally, both of which are important.…”