Evidence map›Paper›PMID 36480254›Full record

ArticleJMIR perioperative medicine2022

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

Priya Ramaswamy, Aalap Shah, Rishi Kothari, Nina Schloemerkemper, Emily Methangkool, Amalia Aleck, Anne Shapiro, Rakhi Dayal, Charlotte Young, Jon Spinner and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR perioperative medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Environmental impact of anesthetic gases.Medical gas research · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Priya RamaswamyDepartment of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-9862-238X
Aalap ShahDepartment of Anesthesiology and Perioperative Care, University of California, Irvine, Irvine, CA, United States.ORCID https://orcid.org/0000-0001-8761-0458
Rishi KothariDepartment of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-7148-970X
Nina SchloemerkemperDepartment of Anesthesiology and Pain Medicine, University of California, Davis, Sacramento, CA, United States.ORCID https://orcid.org/0000-0002-3091-0713
Emily MethangkoolDepartment of Anesthesiology and Perioperative Medicine, University of California, Los Angeles, Los Angeles, CA, United States.ORCID https://orcid.org/0000-0002-9596-5184
Amalia AleckDepartment of Anesthesiology, University of California, San Diego, San Diego, CA, United States.ORCID https://orcid.org/0000-0003-4125-9070
Anne ShapiroDepartment of Anesthesiology, University of California, San Diego, San Diego, CA, United States.ORCID https://orcid.org/0000-0003-1471-3610
Rakhi DayalDepartment of Anesthesiology and Perioperative Care, University of California, Irvine, Irvine, CA, United States.ORCID https://orcid.org/0000-0002-5989-4366
Charlotte YoungSchool of Medicine, University of California, San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0003-2851-3142
Jon SpinnerDepartment of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-7947-0675
Carly DeiblerSan Francisco Medical Center, University of California, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-7024-6725
Kaiyi WangSan Francisco Medical Center, University of California, San Francisco, CA, United States.ORCID https://orcid.org/0000-0003-3012-7099
David RobinowitzDepartment of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0003-4341-189X
Seema GandhiDepartment of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0003-4658-5318

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInhaled 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.

objectiveIn 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.

methodsWe 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.

resultsThe 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.

conclusionsIt 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.

Indexed as

anesthetic gasclinical decision supportfresh gas flowintraoperativeperioperativesustainabilitywaste reduction

Identifiers

PMID36480254
PMCPMC9782391

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.