BACKGROUND: Volatile anesthetic consumption can be reduced by minimizing excessive fresh gas flows (FGFs). Currently, it is unknown whether decision support tools embedded within commercial electronic health record systems can be successfully adopted to achieve long-term reductions in FGF rates. The authors describe the implementation of an electronic health recordbased clinical decision support tool aimed at reducing FGF and evaluate the effectiveness of this intervention in achieving sustained reductions in FGF rates and volatile anesthetic consumption. METHODS: On August 29, 2018, we implemented a decision support tool within the Epic Anesthesia Information Management System (AIMS) to alert providers of high FGF (>0.7 L/ min for desflurane and >1 L/min for sevoflurane) during maintenance of anesthesia. July 22, 2015, to July 10, 2018, served as our baseline period before the intervention. The intervention period spanned from August 29, 2018, to December 31, 2019. Our primary outcomes were mean FGF (L/min) and volatile agent consumption (mL/MAC-h). Because a simple comparison of 2 time periods may result in false conclusions due to underlying trends independent of the intervention, we performed segmented regression of the interrupted time series to assess the change in level at the start of the intervention and the differences in slopes before and after the intervention. The analysis was also adjusted for potential confounding variables. Data included 44,899 cases using sevoflurane preintervention with 26,911 cases postintervention, and 17,472 cases using desflurane with 1185 cases postintervention. RESULTS: Segmented regression of the interrupted times series demonstrated a decrease in mean FGF by 0.6 L/min (95% CI, 0.6-0.6 L/min; P < .0001) for sevoflurane and 0.2 L/min (95% CI, 0.2-0.3 L/min; P < .0001) for desflurane immediately after implementation of the intervention. For sevoflurane, mL/MAC-h decreased by 3.8 mL/MAC-h (95% CI, 3.6-4.1 mL/ MAC-h; P < .0001) after implementation of the intervention and decreased by 4.1 mL/MAC-h (95% CI, 2.6-5.6 mL/MAC-h; P < .0001) for desflurane. Slopes for both FGF and mL/MAC-h in the postintervention period were statistically less negative than the preintervention slopes (P < .0001 for sevoflurane and P < .01 for desflurane). CONCLUSIONS: A commercial AIMS-based decision support tool can be adopted to change provider FGF management patterns and reduce volatile anesthetic consumption in a sustainable fashion. (Anesth Analg 2023;136:327-37) KEY POINTS• Question: Can we adopt decision support tools embedded within a commercial electronic health record system to minimize volatile anesthetic waste? • Findings: Implementation of a commercial Anesthesia Information Management System (AIMS)-based clinical decision support tool led to sustained reductions in fresh gas flow (FGF) rates and inhaled anesthetic agent consumption. • Meaning: A commercial AIMS-based clinical decision support tool led to changes in provider FGF management patterns and may be an effective approach t...

ObjectiveMultimodal analgesia pathways have been shown to reduce opioid use and side effects in surgical patients. A quality improvement initiative was implemented to increase the use of multimodal analgesia in adult patients presenting for general anaesthesia at an academic tertiary care centre. The aim of this study was to increase adoption of a perioperative multimodal analgesia protocol across a broad population of surgical patients. The use of multimodal analgesia was tracked as a process metric. Our primary outcome was opioid use normalised to oral morphine equivalents (OME) intraoperatively, in the postanaesthesia care unit (PACU), and 48 hours postoperatively. Pain scores and use of antiemetics were measured as balancing metrics.MethodsWe conducted a quality improvement study of a multimodal analgesia protocol implemented for adult (≥18 and≤70) non-transplant patients undergoing general anaesthesia (≥180 min). Components of multimodal analgesia were defined as (1) preoperative analgesic medication (acetaminophen, celecoxib, diclofenac, gabapentin), (2) regional anaesthesia (peripheral nerve block or catheter, epidural catheter or spinal) or (3) intraoperative analgesic medication (ketamine, ketorolac, lidocaine infusion, magnesium, acetaminophen, dexamethasone ≥8 mg, dexmedetomidine). We compared opioid use, pain scores and antiemetic use for patients 1 year before (baseline group—1 July 2018 to 30 June 2019) and 1 year after (implementation group—1 July 2019 to 30 June 2020) project implementation.ResultsUse of multimodal analgesia improved from 53.9% in the baseline group to 67.5% in the implementation group (p<0.001). There was no significant difference in intraoperative OME use before and after implementation (β0=44.0, β2=0.52, p=0.875). OME decreased after the project implementation in the PACU (β0=34.4, β2=−3.88, p<0.001) and 48 hours postoperatively (β0=184.9, β2=−22.59, p<0.001), while pain scores during those time points were similar.ConclusionA perioperative pragmatic multimodal analgesic intervention was associated with reduced OME use in the PACU and 48 hours postoperatively.

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