Reducing Volatile Anesthetic Waste Using a Commercial Electronic Health Record Clinical Decision Support Tool to Lower Fresh Gas Flows.

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 record-based 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.

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

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.

Keeping an Open Mind About Open Notes: Sharing Anesthesia Records With Patients.

ADDENDUM: Please note that in the interim since this paper was accepted for publication, new governmental regulations, pertinent to the topic, have been approved for implementation. The reader is thus directed to this online addendum for additional relevant information: http://links.lww.com/AA/E44.

Wildfire Smoke Exposure Is Associated with Adverse Respiratory Events under General Anesthesia in At-risk Pediatric Patients.

BACKGROUND: Increasing wildfire activity worldwide has led to exposure to poor air quality and numerous detrimental health impacts. This study hypothesized an association between exposure to poor air quality from wildfire smoke and adverse respiratory events under general anesthesia in pediatric patients. METHODS: This was a single-center retrospective double-cohort study examining two significant wildfire events in Northern California. Pediatric patients presenting for elective surgery during periods of unhealthy air quality were compared with those during periods of healthy air quality. The primary exposure, unhealthy air, was determined using local air quality sensors. The primary outcome was the occurrence of an adverse respiratory event under anesthesia. Secondary analysis included association with other known risk factors for adverse respiratory events. RESULTS: A total of 625 patients were included in the analysis. The overall risk of a respiratory complication was 42.4% (265 of 625). In children without a history of reactive airway disease, the risk of adverse respiratory events did not change during unhealthy air periods (102 of 253, 40.3%) compared with healthy air periods (95 of 226, 42.0%; relative risk 0.96 [0.77 to 1.19], P = 0.703). In children with a history of reactive airway disease, the risk of adverse respiratory events increased from 36.8% (25 of 68) during healthy air periods to 55.1% (43 of 78) during periods with unhealthy air (1.50 [1.04 to 2.17], P = 0.032). The effect of air quality on adverse respiratory events was significantly modified by reactive airways disease status (1.56 [1.02 to 2.40], P = 0.041). CONCLUSIONS: Pediatric patients with underlying risk factors for respiratory complications under general anesthesia had a greater incidence of adverse respiratory events during periods of unhealthy air quality caused by wildfire smoke. In this vulnerable patient population, postponing elective anesthetics should be considered when air quality is poor.

Aerosol Retention Characteristics of Barrier Devices.

BACKGROUND: Disease severity in coronavirus disease 2019 (COVID-19) may be associated with inoculation dose. This has triggered interest in intubation barrier devices to block droplet exposure; however, aerosol protection with these devices is not known. This study hypothesized that barrier devices reduce aerosol outside of the barrier. METHODS: Aerosol containment in closed, semiclosed, semiopen, and open barrier devices was investigated: (1) "glove box" sealed with gloves and caudal drape, (2) "drape tent" with a drape placed over a frame, (3) "slit box" with armholes and caudal end covered by vinyl slit diaphragms, (4) original "aerosol box," (5) collapsible "interlocking box," (6) "simple drape" over the patient, and (7) "no barrier." Containment was investigated by (1) vapor instillation at manikin's right arm with video-assisted visual evaluation and (2) submicrometer ammonium sulfate aerosol particles ejected through the manikin's mouth with ventilation and coughs. Samples were taken from standardized locations inside and around the barriers using a particle counter and a mass spectrometer. Aerosol evacuation from the devices was measured using standard hospital suction, a surgical smoke evacuator, and a Shop-Vac. RESULTS: Vapor experiments demonstrated leakage via arm holes and edges. Only closed and semiclosed devices and the aerosol box reduced aerosol particle counts (median [25th, 75th percentile]) at the operator's mouth compared to no barrier (combined median 29 [-11, 56], n = 5 vs. 157 [151, 166], n = 5). The other barrier devices provided less reduction in particle counts (133 [128, 137], n = 5). Aerosol evacuation to baseline required 15 min with standard suction and the Shop-Vac and 5 min with a smoke evacuator. CONCLUSIONS: Barrier devices may reduce exposure to droplets and aerosol. With meticulous tucking, the glove box and drape tent can retain aerosol during airway management. Devices that are not fully enclosed may direct aerosol toward the laryngoscopist. Aerosol evacuation reduces aerosol content inside fully enclosed devices. Barrier devices must be used in conjunction with body-worn personal protective equipment.

An Implementation-Effectiveness Study of a Perioperative Delirium Prevention Initiative for Older Adults.

BACKGROUND: Postoperative delirium is a common and serious problem for older adults. To better align local practices with delirium prevention consensus guidelines, we implemented a 5-component intervention followed by a quality improvement (QI) project at our institution. METHODS: This hybrid implementation-effectiveness study took place at 2 adult hospitals within a tertiary care academic health care system. We implemented a 5-component intervention: preoperative delirium risk stratification, multidisciplinary education, written memory aids, delirium prevention postanesthesia care unit (PACU) orderset, and electronic health record enhancements between December 1, 2017 and June 30, 2018. This was followed by a department-wide QI project to increase uptake of the intervention from July 1, 2018 to June 30, 2019. We tracked process outcomes during the QI period, including frequency of preoperative delirium risk screening, percentage of "high-risk" screens, and frequency of appropriate PACU orderset use. We measured practice change after the interventions using interrupted time series analysis of perioperative medication prescribing practices during baseline (December 1, 2016 to November 30, 2017), intervention (December 1, 2017 to June 30, 2018), and QI (July 1, 2018 to June 30, 2019) periods. Participants were consecutive older patients (≥65 years of age) who underwent surgery during the above timeframes and received care in the PACU, compared to a concurrent control group <65 years of age. The a priori primary outcome was a composite of perioperative American Geriatrics Society Beers Criteria for Potentially Inappropriate Medication Use (Beers PIM) medications. The secondary outcome, delirium incidence, was measured in the subset of older patients who were admitted to the hospital for at least 1 night. RESULTS: During the 12-month QI period, preoperative delirium risk stratification improved from 67% (714 of 1068 patients) in month 1 to 83% in month 12 (776 of 931 patients). Forty percent of patients were stratified as "high risk" during the 12-month period (4246 of 10,494 patients). Appropriate PACU orderset use in high-risk patients increased from 19% in month 1 to 85% in month 12. We analyzed medication use in 7212, 4416, and 8311 PACU care episodes during the baseline, intervention, and QI periods, respectively. Beers PIM administration decreased from 33% to 27% to 23% during the 3 time periods, with adjusted odds ratio (aOR) 0.97 (95% confidence interval [CI], 0.95-0.998; P = .03) per month during the QI period in comparison to baseline. Delirium incidence was 7.5%, 9.2%, and 8.5% during the 3 time periods with aOR of delirium of 0.98 (95% CI, 0.91-1.05, P = .52) per month during the QI period in comparison to baseline. CONCLUSIONS: A perioperative delirium prevention intervention was associated with reduced administration of Beers PIMs to older adults.

An analysis of near misses identified by anesthesia providers in the intensive care unit.

BACKGROUND: Learning from adverse events and near misses may reduce the incidence of preventable errors. Current literature on adverse events and near misses in the ICU focuses on errors reported by nurses and intensivists. ICU near misses identified by anesthesia providers may reveal critical events, causal mechanisms and system weaknesses not identified by other providers, and may differ in character and causality from near misses in other anesthesia locations. METHODS: We analyzed events reported to our anesthesia near miss reporting system from 2009 to 2011. We compared causative mechanisms of ICU near misses with near misses in other anesthesia locations. RESULTS: A total of 1,811 near misses were reported, of which 22 (1.2 %) originated in the ICU. Five causal mechanisms explained over half of ICU near misses. Compared to near misses from other locations, near misses from the ICU were more likely to occur while on call (45 % vs. 19 %, p = 0.001), and were more likely to be associated with airway management (50 % vs. 12 %, p < 0.001). ICU near misses were less likely to be associated with equipment issues (23 % vs. 48 %, p = 0.02). CONCLUSIONS: A limited number of causal mechanisms explained the majority of ICU near misses, providing targets for quality improvement. Errors associated with airway management in the ICU may be underappreciated. Specialist consultants can identify systems weaknesses not identified by critical care providers, and should be engaged in the ICU patient safety movement.

Public reporting of provider performance: can its impact be made greater?

Public reporting of provider performance is becoming increasingly commonplace. In this chapter, we first review studies of prior public reports (or report cards) that show real but small impact on provider attempts to improve quality, on consumers' impressions of providers, and even on consumer selection of providers. Among other factors, two potential explanations for the low level of impact are that, in most early reports, the large majority of providers have been labeled "average" and consumers may have had difficulty understanding the statistical assessments. In response, some current report card producers are using or considering a variety of methods to increase the number of distinctions among providers and the ease of comprehension of the labels used. Therefore, we also consider the advantages and disadvantages of several novel approaches to analyzing and reporting provider performance.