Akron Children's Uses Epic and Real-Time Analytics to Reduce Waste Anesthesia Gases
•February 13, 2026
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Why It Matters
The program shows how health‑IT can transform clinical workflows into measurable climate benefits, offering a scalable template for hospitals to reduce emissions and operational costs.
Key Takeaways
- •Waste gases 5‑10% of hospital emissions.
- •Low‑flow reminders cut nitrous oxide 5% instantly.
- •Project WAGER cut nitrous use 85% overall.
- •Total fresh‑gas flow down 50% with 20% more minutes.
- •AdaptX provides near‑real‑time analytics for anesthesia.
Pulse Analysis
Hospitals are increasingly scrutinized for their carbon footprints, and anesthesia gases have emerged as a hidden but significant source of emissions. Nitrous oxide and sevoflurane possess global warming potentials hundreds of times greater than carbon dioxide, and at Akron Children’s they accounted for up to ten percent of total greenhouse‑gas output. By embedding low‑flow prompts directly into the Epic electronic health record and on anesthesia workstations, clinicians received real‑time cues to reduce gas flow without compromising patient safety, turning a technical adjustment into a sustainability lever.
The data‑driven approach deepened when the institution partnered with AdaptX, a platform that extracts minute‑by‑minute anesthesia metrics from Epic each night. This near‑real‑time visibility allowed anesthesiologists and CRNAs to benchmark their gas usage against peers, spot outliers, and iterate quickly. Simple visual reminders yielded a 5% nitrous oxide reduction, while monthly analytics dashboards supported a broader cultural shift that ultimately slashed nitrous use by more than 85% and cut total fresh‑gas flow in half, even as anesthesia minutes rose 20%.
These results illustrate a replicable pathway for health systems seeking both environmental stewardship and cost efficiency. Real‑time analytics transform raw EHR data into actionable insights, enabling rapid feedback loops and continuous improvement. As more hospitals join collaborative networks like Project Spruce, the collective impact could translate into hundreds of metric tons of CO₂‑equivalent emissions avoided annually, reinforcing the role of health‑IT as a catalyst for sustainable clinical practice.
Akron Children's uses Epic and real-time analytics to reduce waste anesthesia gases
Dr. Peggy Allen is a pediatric anesthesiologist and the anesthesiology sustainability program director at Akron Children’s Hospital. The hospital has reached Stage 7 on the HIMSS Electronic Medical Record Adoption Model, or EMRAM.
Part of that achievement was a successful effort to reduce gases harmful to the environment that stem from anesthesia. And the hospital’s anesthesiology team used technology to do so.
Akron Children’s Hospital posed an innovation challenge to all departments in 2021: How can the organization reduce its carbon footprint?
Allen and Tabby Cline, CRNA, one of the nurse anesthetists, had some conversations, did some research, and learned the hospital’s waste anesthesia gases were a significant contributor to the organization’s greenhouse‑gas emissions. Indeed, 5‑10 % of the hospital’s greenhouse‑gas emissions came exclusively from the waste anesthesia gases.
Healthcare IT News sat down with Allen to get the whole scoop on her and her colleagues’ work to help the environment using technology.
Q. What was the nitrous oxide challenge you faced before turning to the technology you used?
A. The two most prominent anesthesia gases we use at Akron Children’s Hospital – and probably the most commonly used across the country and maybe even globally – are sevoflurane and nitrous oxide.
Nitrous oxide is about 300 times worse than carbon dioxide for the atmosphere and lingers for more than 100 years. Sevoflurane lingers for more than a year and is about 100 times worse than carbon dioxide. They certainly have an environmental impact. Our goal was not to eliminate them, but to minimize how much we’re using.
An interesting thing about anesthesia is the brain doesn’t care how many liters of these gases it sees. It cares about what percent it sees. So, if you have 50 % of something flowing at 2 L versus 50 % flowing at 10 L, the brain doesn’t care. It sees the 50 % and that’s the effect.
We did a lot of research and educated ourselves and all of our colleagues in the department about using low‑flow anesthesia, where you simply reduce the flows, maintain the percent of anesthesia, and still keep the patient adequately anesthetized, but you just reduce the flows.
We really wanted to reduce our nitrous oxide use because of its profound effect on the environment. As an institution we historically were very heavy users of nitrous oxide, and we saw this as an opportunity to really make an impact on the environment.
Once you learn about it, it’s impressive. It’s not historically a part of anesthesia education. It is becoming part of anesthesia education as we are learning more about it as a profession. But when I trained 20‑plus years ago, there was essentially no conversation about this. The waste anesthesia gases come out of the back of the anesthesia machine, are vented out the roof of the hospital, and off they go.
Q. What technology did you use to address this challenge? What was the proposal this technology offered to resolve the challenge? How is it supposed to alleviate it?
A. I look at technology on multiple different levels. We had some low‑basic technology things. For example, anesthetics are part of the electronic health record—an electronic anesthesia record within Epic.
So, you can adjust the EHR to your institution’s practices. One thing we implemented was simply an electronic low‑flow reminder that popped up at the beginning of every anesthetic case, probably about the first 10 minutes of each case. Just a simple visual reminder to consider low‑flow anesthesia.
That was a simple one. After we implemented that, we saw about a 5 % reduction in our nitrous oxide use right there alone, just by one simple little technological reminder. Our anesthesia machines also have a visual reminder on them to reduce our flows of anesthesia. It’s color‑coded, has a little bar graph, and text that tells you whether you are using optimal flows of gas.
They call it efficient flow of gas – too little or too much. The machine interprets what you’ve dialed in, the patient’s characteristics, and then how much gas you flow, and if you’re giving too much gas to the patient.
We also put laminated cards on every anesthetic machine to encourage people to use low‑flow for induction of anesthesia, which means the beginning of anesthesia when you’re getting a patient off to sleep.
Those are some low‑fidelity technologies we used. The biggest, most involved one was getting our data from Epic. Since we have an electronic health record, we said, “Let’s use it.” The challenge was to determine: How much gas are we really using?
We know anecdotally a provider uses a lot, and this provider already does low‑flow, but how much are we all using? Epic allowed us to capture that answer. We got four months of baseline data before we even announced the project to try to reduce our flows.
We had baseline data for four months, starting in December 2021 through the spring of 2022, to know how much gas we were using overall. Then we have data, and we continue to collect every minute of anesthesia at every single location since that time.
That data is now in Epic. Epic is a great electronic health record for most things, but it can be a little cumbersome to use. So, we had a third member of our team—one of our Epic analysts—gather all that data and crank it out into a report for us once a month. About the end of the first week of the month, I would get last month’s data.
I got a great report—basically an Excel spreadsheet—with our data for how much each individual uses in terms of the different gases, how much they use compared to their colleagues. For example, if you did 5 % of the anesthesia minutes but used 10 % of the gas flows, you’re an outlier. The report also had a couple of nice graphs. It was great data to have. I could not have done this study without the work of our Epic analyst.
The challenge was that the data wasn’t terribly timely. I’m getting the data on the seventh or eighth of the month for the previous month. It’s great, but it’s not real‑time data. It allows you to look at the bigger picture and see trends over time, but it also required the skills of our Epic analyst. There were other opportunities that came afterward.
Q. So how did your waste gas journey continue?
A. The effort we called Project WAGER (Waste Anesthesia Gas Emission Reduction) was all in‑house. We did education with our colleagues, sent out emails, and shared the data—lots of carrots, no sticks.
After about a year, we were invited to join an international pediatric anesthesia consortium, initially nine hospitals headed up by Seattle Children’s and Denver Children’s, plus other children’s hospitals in the U.S., Canada, and Australia. This was called Project Spruce.
In our first effort, our in‑house project, we had reduced our nitrous use by 40 %—fantastic. When we joined Project Spruce, the goal for the first year was to reduce waste anesthesia gas or greenhouse‑gas emissions by 50 % from that point. It seemed a tall ask, but we did it. We joined Spruce in September 2023 and hit the 50 % target in the first year, as did every other member of the consortium.
A key for Project Spruce was a platform called AdaptX. It’s a software platform that takes all the Epic data and downloads it every night, so the anesthetics I do today get downloaded tomorrow. I can look in AdaptX and see if I did something different yesterday and whether it made a difference in my gas emissions or other variables.
AdaptX looks at many peri‑operative variables—anesthesia time for induction, emergence, total operative time, length of stay in recovery, need for nausea or pain medicines, etc. It gathers all that data and lets me answer any clinical question. For Project Spruce, it gave us our CO₂‑equivalence (the unit of measure in this field) and let us view it by anesthesiologist, CRNA, surgical service, case type, etc., to identify improvement opportunities.
The software is super user‑friendly. Everyone in the department has access; anyone can log in, pose questions, and get results in a few clicks. The tables are beautiful and ready for PowerPoint presentations. Every month I give our department report and show a couple of slides from AdaptX.
AdaptX is light‑years ahead of the Epic data we had. Epic feeds AdaptX, but AdaptX lets us get the data on our own schedule without waiting for the analyst each month.
Q. What are some of the hard results you’ve achieved from your efforts?
A. In terms of hard results, there are three key achievements from this nearly four‑year process:
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Total fresh‑gas flow reduction: We have reduced the flow of all three carrier gases (oxygen, air, nitrous oxide) by 50 % while increasing our minutes of anesthesia by 20 %. This means our relative flow per case is actually greater than a 50 % reduction.
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Nitrous oxide use: We reduced nitrous oxide use by more than 85 % over the same period. Per minute of anesthesia, we now use only 12 % of what we used before.
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Carbon‑dioxide‑equivalent emissions: If we had continued our previous practice through 2025, we would have emitted an extra 498 metric tons of CO₂ last year. Instead, we saved that amount in 2025 through the practice changes.
These results demonstrate a truly remarkable change in practice and a significant environmental impact.
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