A Mobile Post Anesthesia Care Unit Order Reminder System Improves Timely Order Entry.

Transition to the postanesthesia care unit (PACU) requires timely order placement by anesthesia providers. Computerized ordering enables automated order reminder systems, but their value is not fully understood. We performed a single-center, retrospective cohort study to estimate the association between automated PACU order reminders and primary outcomes (1) on-time order placement and (2) the degree of delay in placement. As a secondary post-hoc analysis, we studied the association between late order placement and PACU outcomes. We included patients with a qualifying postprocedure order from January 1, 2019, to May 31, 2023. We excluded cases transferred directly to the ICU, whose anesthesia provider was involved in the pilot testing of the reminder system, or those with missing covariate data. Order reminder system usage was defined by the primary attending anesthesiologist's receipt of a push notification reminder on the day of surgery. We estimated the association between reminder system usage and timely order placement using a logistic regression. For patients with late orders, we performed a survival analysis of order placement. The significance level was 0.05. Patient (e.g., age, race), procedural (e.g., anesthesia duration), and provider-based (e.g., ordering privileges) variables were used as covariates within the analyses. Reminders were associated with 51% increased odds of order placement prior to PACU admission (Odds Ratio: 1.51; 95% Confidence Interval: 1.43, 1.58; p ≤ 0.001), reducing the incidence of late PACU orders from 17.5% to 12.6% (p ≤ 0.001). In patients with late orders, the reminders were associated with 10% quicker placement (Hazard Ratio: 1.10; 95% CI 1.05, 1.15; p < 0.001). On-time order placement was associated with decreased PACU duration (p < 0.001), decreased odds of peak PACU pain score (p < 0.001), and decreased odds of multiple administration of antiemetics (p = 0.02). An order reminder system was associated with an increase in order placement prior to PACU arrival and a reduction in delay in order placement after arrival.

Understanding the Accuracy of Clinician Provided Estimated Discharge Dates.

Discharge planning is a vital tool in managing hospital capacity, which is essential for maintaining hospital throughput for surgical postoperative admissions. Early discharge planning has been effective in reducing length of stay and hospital readmissions. Between 2014 and 2017, Vanderbilt University Medical Center (VUMC) implemented a tool in the electronic health record (EHR) requiring providers to input the patient's estimated discharge date on each hospital day. We hypothesized discharge estimates would be more accurate, on average, for surgical patients compared to non-surgical patients because treatment plans are known in advance of surgical admissions. We also analyzed the data to identify factors associated with more accurate discharge estimates. In this retrospective observational study, via an analysis of covariance (ANCOVA) approach, we identified factors associated with more accurate discharge estimates for admitted adult patients at VUMC. The primary outcome was the difference between estimated and actual discharge date, and the primary exposure of interest was whether the patient underwent surgery while admitted to the hospital. A total of 304,802 date of discharge estimate entries from 68,587 inpatient encounters met inclusion criteria. After controlling for measured confounding, we found the discharge estimates were more precise as the difference between estimated and actual discharge date narrowed; for each additional day closer to discharge, prediction accuracy improved by .67 days (95% confidence interval [CI], 0.66 to 0.67; p < 0.001), on average. No difference was observed on the primary outcome in patients undergoing surgery compared with non-surgical treatment (0.02 days; 95% CI, 0.00 to 0.03; p = 0.111). Faculty members were found to perform best among all clinicians in predicting estimated discharge date with a 0.24-day better accuracy (95% CI, 0.20 to 0.27; p < 0.001), on average, than other staff. Weekend and holiday, specific clinical teams, staff types, and discharge dispositions were associated with the variability in estimated versus actual discharge date (p < 0.001). Given the widespread variation in current efforts to improve discharge planning and the recommended approach of assigning a discharge date early in the hospital stay, understanding provider estimated discharge dates is an important tool in hospital capacity management. While we did not determine a difference in discharge estimates among surgical and non-surgical patients, we found estimates were more accurate as discharge came nearer and identified notable trends in provider inputs and patient factors. Assessing factors that impact variability in discharge accuracy can allow hospitals to design targeted interventions to improve discharge planning and reduce unnecessary hospital days.

Pediatric Perioperative Mortality in Kenya: A Prospective Cohort Study from 24 Hospitals.

BACKGROUND: The global surgery access imbalance will have a dramatic impact on the growing population of the world's children. In regions of the world with pediatric surgery and anesthesia manpower deficits and pediatric surgery-specific infrastructure and supply chain gaps, this expanding population will present new challenges. Perioperative mortality rate is an established indicator of the quality and safety of surgical care. To establish a baseline pediatric perioperative mortality rate and factors associated with mortality in Kenya, the authors designed a prospective cohort study and measured 24-h, 48-h, and 7-day perioperative mortality. METHODS: The authors trained anesthesia providers to electronically collect 132 data elements for pediatric surgical cases in 24 government and nongovernment facilities at primary, secondary, and tertiary hospitals from January 2014 to December 2016. Data assistants tracked all patients to 7 days postoperative, even if they had been discharged. Adjusted analyses were performed to compare mortality among different hospital levels after adjusting for prespecified risk factors. RESULTS: Of 6,005 cases analyzed, there were 46 (0.8%) 24-h, 62 (1.1%) 48-h, and 77 (1.7%) 7-day cumulative mortalities reported. In the adjusted analysis, factors associated with a statistically significant increase in 7-day mortality were American Society of Anesthesiologists Physical Status of III or more, night or weekend surgery, and not having the Safe Surgery Checklist performed. The 7-day perioperative mortality rate is less in the secondary (1.4%) and tertiary (2.4%) hospitals when compared with the primary (3.7%) hospitals. CONCLUSIONS: The authors have established a baseline pediatric perioperative mortality rate that is greater than 100 times higher than in high-income countries. The authors have identified factors associated with an increased mortality, such as not using the Safe Surgery Checklist. This analysis may be helpful in establishing pediatric surgical care systems in low-middle income countries and develop research pathways addressing interventions that will assist in decreasing mortality rate.

Prospective Investigation of the Operating Room Time-Out Process.

BACKGROUND: Although the surgical pause or time-out is a required part of most hospitals' standard operating procedures, little is known about the quality of execution of the time-out in routine clinical practice. An interactive electronic time-out was implemented to increase surgical team compliance with the time-out procedure and to improve communication among team members in the operating room. We sought to identify nonroutine events that occur during the time-out procedure in the operating room, including distractions and interruptions, deviations from protocol, and the problem-solving strategies used by operating room team members to mitigate them. METHODS: Direct observations of surgical time-outs were performed on 166 nonemergent surgeries in 2016. For each time-out, the observers recorded compliance with each step, any nonroutine events that may have occurred, and whether any operating room team members were distracted. RESULTS: The time-out procedure was performed before the first incision in 100% of cases. An announcement was made to indicate the start of the time-out procedure in 163 of 166 observed surgeries. Most observed time-outs were completed in <1 minute. Most time-outs were completed without interruption (92.8%). The most common reason for an interruption was to verify patient information. Ten time-out procedures were stopped due to a safety concern. At least 1 member of the operating room team was actively distracted in 10.2% of the time-out procedures observed. CONCLUSIONS: Compliance with preincision time-outs is high at our institution, and nonroutine events are a rare occurrence. It is common for ≥1 member of the operating room team to be actively distracted during time-out procedures, even though most time-outs are completed in under 1 minute. Despite distractions, there were no wrong-site or wrong-person surgeries reported at our hospital during the study period. We conclude that the simple act of performing a preprocedure checklist may be completed quickly, but that distractions are common.

CYP2D6 Genotype-guided Metoprolol Therapy in Cardiac Surgery Patients: Rationale and Design of the Pharmacogenetic-guided Metoprolol Management for Postoperative Atrial Fibrillation in Cardiac Surgery (PREEMPTIVE) Pilot Study.

OBJECTIVES: The Preemptive Pharmacogenetic-guided Metoprolol Management for Atrial Fibrillation in Cardiac Surgery (PREEMPTIVE) pilot trial aims to use existing institutional resources to develop a process for integrating CYP2D6 pharmacogenetic test results into the patient electronic health record, to develop an evidence-based clinical decision support tool to facilitate CYP2D6 genotype-guided metoprolol administration in the cardiac surgery setting, and to determine the impact of implementing this CYP2D6 genotype-guided integrated approach on the incidence of postoperative atrial fibrillation (AF), provider, and cost outcomes. DESIGN: One-arm Bayesian adaptive design clinical trial. SETTING: Single center, university hospital. PARTICIPANTS: The authors will screen (including CYP2D6 genotype) up to 600 (264 ± 144 expected under the adaptive design) cardiac surgery patients, and enroll up to 200 (88 ± 48 expected) poor, intermediate, and ultrarapid CYP2D6 metabolizers over a period of 2 years at a tertiary academic center. INTERVENTIONS: All consented and enrolled patients will receive the intervention of CYP2D6 genotype-guided metoprolol management based on CYP2D6 phenotype classified as a poor, intermediate, extensive (normal), or ultrarapid metabolizer. MEASUREMENTS AND MAIN RESULTS: The primary outcome will be the incidence of postoperative AF. Secondary outcomes relating to rates of CYP2D6 genotype-guided prescription changes, costs, lengths of stay, and implementation metrics also will be investigated. CONCLUSIONS: The PREEMPTIVE pilot study is the first perioperative pilot trial to provide essential information for the design of a future, large-scale trial comparing CYP2D6 genotype-guided metoprolol management with a nontailored strategy in terms of managing AF. In addition, secondary outcomes regarding implementation, clinical benefit, safety, and cost-effectiveness in patients undergoing cardiac surgery will be examined.

Transition from Private to Academic Anesthesia Provision Changes Process and Patient Centered Outcomes in an Ambulatory Surgery Center.

A recurring concern in the discussion of performance of anesthesia practices is that academic practitioners are slower, less efficient, or produce poorer operational outcomes than their private practice counterparts. A simple overnight 'swap' of a private anesthesia practice with an academic anesthesia practice took place in an outpatient surgery center where the case volume, case mix, surgeons, and staff remained the same. Operational and quality measures were analyzed for comparison between the practices over the span of two years. All patients who had a procedure at the outpatient surgery center in the year prior to the takeover and the year after were studied. Post-anesthesia care unit times, hospital transfer data, pain scores at discharge, opioids dispensed, and anesthesia control times were compared over two years. Charts were manually abstracted by non-clinical administrative staff who were unaware of the study hypothesis. Procedure data and clinical outcomes were compared between the two years using standard statistical techniques. After exchange to the academic group, the median (mean) pain score at post-anesthesia care unit (PACU) discharge was reduced from 2 (2.0) to 0 (1.7) (Wilcoxon rank sum test p < 0.001), and the odds of having moderate or severe pain was reduced by 32% (95% CI, 25, 39, p < 0.001) after adjusting for surgery type. The year-on-year average recovery room time was reduced by 13.9 min (95% CI, 12.5, 15.4, p < 0.001) after adjusting for surgery type. There was a significant reduction in hospital transfer rate after changing groups (0.45% vs. 0.07%, Pearson chi square test p = 0.005). Hospital transfer rates, dispensed opioids in PACU, pain scores at discharge, and PACU times were all improved after the conversion from a private practice to an academic one, without a compromise in efficiency or throughput.

An enhanced recovery program in colorectal surgery is associated with decreased organ level rates of complications: a difference-in-differences analysis.

BACKGROUND: Perioperative care has lacked coordination and standardization. Enhanced recovery programs (ERPs) have been shown to decrease aggregate complications across surgical specialties. We hypothesize that the sustained implementation of an ERP will be associated with a decrease in a broad range of complications at the organ system level. STUDY DESIGN: Adult patients undergoing elective colorectal procedures between 1/2011 and 10/2016 were included. Patients were stratified based on exposure to a sustained ERP (7/2014-10/2016) after an 18-month wash-in period in a pre-post analysis. The primary outcome was 30-day complication rate by organ category as collected by National Surgical Quality Improvement Program (NSQIP) abstractors. Demographic and other patient level data were collected. Complication rates were compared using multivariable regression employing a differences-in-differences (DiD) approach using the national NSQIP PUF file to account for secular trends. RESULTS: A total of 1182 patients were included in this study, with 47% treated in an ERP. The two groups were similar in age, gender, race, BMI, comorbidity index, and procedure type. In a multivariable DiD analysis, significant reductions were seen in surgical site infection (OR 0.30; 95% CI 0.20-0.43), postoperative pulmonary complications (OR 0.46; 95% CI 0.24-0.90), transfusion (OR 0.27; 95% CI 0.15-0.51), urinary tract infections (OR 0.34; 95% CI 0.18-0.66), sepsis (OR 0.35; 95% CI 0.20-0.61), and cardiac complications (OR 0.10; 95% CI 0.01-0.84). A reduction in return to the operating room and 30-day readmission was also observed. Median length of stay (LOS) decreased from 5.2 to 3.5 days (p < 0.001). No significant changes occurred for acute kidney injury and hematologic complications. CONCLUSION: An ERP was associated with reduced complication rates across a wide range of organ categories and > 1.5-day reduction in LOS in a colorectal surgery population.

A retrospective evaluation of the risk of bias in perioperative temperature metrics.

The prevention and treatment of hypothermia is an important part of routine anesthesia care. Avoidance of perioperative hypothermia was introduced as a quality metric in 2010. We sought to assess the integrity of the perioperative hypothermia metric in routine care at a single large center. Perioperative temperatures from all anesthetics of at least 60 min duration between January 2012 and 2017 were eligible for inclusion in analysis. Temperatures were displayed graphically, assessed for normality, and analyzed using paired comparisons. Automatically-recorded temperatures were obtained from several monitoring sites. Provider-entered temperatures were non-normally distributed, exhibiting peaks at temperatures at multiples of 0.5 °C. Automatically-acquired temperatures, on the other hand, were more normally distributed, demonstrating smoother curves without peaks at multiples of 0.5 °C. Automatically-acquired median temperature was highest, 36.8 °C (SD = 0.8 °C), followed by the three manually acquired temperatures (nurse-documented postoperative temperature, 36.5 °C [SD = 0.6 °C]; intraoperative manual temperature, 36.5 °C [SD = 0.6 °C]; provider-documented postoperative temperature, 36.1 °C [SD = 0.6 °C]). Provider-entered temperatures exhibit values that are unlikely to represent a normal probability distribution around a central physiologic value. Manually-entered perioperative temperatures appear to cluster around salient anchoring values, either deliberately, or as an unintended result driven by cognitive bias. Automatically-acquired temperatures may be superior for quality metric purposes.

Implementation and Evaluation of the Z-Score System for Normalizing Residency Evaluations.

BACKGROUND: Assessment of clinical competence is essential for residency programs and should be guided by valid, reliable measurements. We implemented Baker's Z-score system, which produces measures of traditional core competency assessments and clinical performance summative scores. Our goal was to validate use of summative scores and estimate the number of evaluations needed for reliable measures. METHODS: We performed generalizability studies to estimate the variance components of raw and Z-transformed absolute and peer-relative scores and decision studies to estimate the evaluations needed to produce at least 90% reliable measures for classification and for high-stakes decisions. A subset of evaluations was selected representing residents who were evaluated frequently by faculty who provided the majority of evaluations. Variance components were estimated using ANOVA. RESULTS: Principal component extraction from 8,754 complete evaluations demonstrated that a single factor explained 91 and 85% of variance for absolute and peer-relative scores, respectively. In total, 1,200 evaluations were selected for generalizability and decision studies. The major variance component for all scores was resident interaction with measurement occasions. Variance due to the resident component was strongest with raw scores, where 30 evaluation occasions produced 90% reliable measurements with absolute scores and 58 for peer-relative scores. For Z-transformed scores, 57 evaluation occasions produced 90% reliable measurements with absolute scores and 55 for peer-relative scores. The results were similar for high-stakes decisions. CONCLUSIONS: The Baker system produced moderately reliable measures at our institution, suggesting that it may be generalizable to other training programs. Raw absolute scores required few assessment occasions to achieve 90% reliable measurements.

Sources of Variation in Anesthetic Drug Costs.

BACKGROUND: Increasing attention has been focused on health care expenditures, which include anesthetic-related drug costs. Using data from 2 large academic medical centers, we sought to identify significant contributors to anesthetic drug cost variation. METHODS: Using anesthesia information management systems, we calculated volatile and intravenous drug costs for 8 types of inpatient surgical procedures performed from July 1, 2009, to December 31, 2011. For each case, we determined patient age, American Society of Anesthesiologists (ASA) physical status, gender, institution, case duration, in-room provider, and attending anesthesiologist. These variables were then entered into 2 fixed-effects linear regression models, both with logarithmically transformed case cost as the outcome variable. The first model included duration, attending anesthesiologist, patient age, ASA physical status, and patient gender as independent variables. The second model included case type, institution, patient age, ASA physical status, and patient gender as independent variables. When all variables were entered into 1 model, redundancy analyses showed that case type was highly correlated (R = 0.92) with the other variables in the model. More specifically, a model that included case type was no better at predicting cost than a model without the variable, as long as that model contained the combination of attending anesthesiologist and case duration. Therefore, because we were interested in determining the effect both variables had on cost, 2 models were created instead of 1. The average change in cost resulting from each variable compared to the average cost of the reference category was calculated by first exponentiating the ß coefficient and subtracting 1 to get the percent difference in cost. We then multiplied that value by the mean cost of the associated reference group. RESULTS: A total of 5504 records were identified, of which 4856 were analyzed. The median anesthetic drug cost was $38.45 (25th percentile = $23.23, 75th percentile = $63.82). The majority of the variation was not described by our models-35.2% was explained in the model containing case duration, and 32.3% was explained in the model containing case type. However, the largest sources of variation our models identified were attending anesthesiologist, case type, and procedure duration. With all else held constant, the average change in cost between attending anesthesiologists ranged from a cost decrease of $41.25 to a cost increase of $95.67 (10th percentile = -$19.96, 90th percentile = +$20.20) when compared to the provider with the median value for mean cost per case. The average change in cost between institutions was significant but minor ($5.73). CONCLUSIONS: The majority of the variation was not described by the models, possibly indicating high per-case random variation. The largest sources of variation identified by our models included attending anesthesiologist, procedure type, and case duration. The difference in cost between institutions was statistically significant but was minor. While many prior studies have found significant savings resulting from cost-reducing interventions, our findings suggest that because the overall cost of anesthetic drugs was small, the savings resulting from interventions focused on the clinical practice of attending anesthesiologists may be negligible, especially in institutions where access to more expensive drugs is already limited. Thus, cost-saving efforts may be better focused elsewhere.

A Perioperative Systems Design to Improve Intraoperative Glucose Monitoring Is Associated with a Reduction in Surgical Site Infections in a Diabetic Patient Population.

BACKGROUND: Diabetic patients receiving insulin should have periodic intraoperative glucose measurement. The authors conducted a care redesign effort to improve intraoperative glucose monitoring. METHODS: With approval from Vanderbilt University Human Research Protection Program (Nashville, Tennessee), the authors created an automatic system to identify diabetic patients, detect insulin administration, check for recent glucose measurement, and remind clinicians to check intraoperative glucose. Interrupted time series and propensity score matching were used to quantify pre- and postintervention impact on outcomes. Chi-square/likelihood ratio tests were used to compare surgical site infections at patient follow-up. RESULTS: The authors analyzed 15,895 cases (3,994 preintervention and 11,901 postintervention; similar patient characteristics between groups). Intraoperative glucose monitoring rose from 61.6 to 87.3% in cases after intervention (P = 0.0001). Recovery room entry hyperglycemia (fraction of initial postoperative glucose readings greater than 250) fell from 11.0 to 7.2% after intervention (P = 0.0019), while hypoglycemia (fraction of initial postoperative glucose readings less than 75) was unchanged (0.6 vs. 0.9%; P = 0.2155). Eighty-seven percent of patients had follow-up care. After intervention the unadjusted surgical site infection rate fell from 1.5 to 1.0% (P = 0.0061), a 55.4% relative risk reduction. Interrupted time series analysis confirmed a statistically significant surgical site infection rate reduction (P = 0.01). Propensity score matching to adjust for confounders generated a cohort of 7,604 well-matched patients and confirmed a statistically significant surgical site infection rate reduction (P = 0.02). CONCLUSIONS: Anesthesiologists add healthcare value by improving perioperative systems. The authors leveraged the one-time cost of programming to improve reliability of intraoperative glucose management and observed improved glucose monitoring, increased insulin administration, reduced recovery room hyperglycemia, and fewer surgical site infections. Their analysis is limited by its applied quasiexperimental design.

Monitoring Anesthesia Care Delivery and Perioperative Mortality in Kenya Utilizing a Provider-driven Novel Data Collection Tool.

BACKGROUND: Perioperative mortality rate is regarded as a credible quality and safety indicator of perioperative care, but its documentation in low- and middle-income countries is poor. We developed and tested an electronic, provider report-driven method in an East African country. METHODS: We deployed a data collection tool in a Kenyan tertiary referral hospital that collects case-specific perioperative data, with asynchronous automatic transmission to central servers. Cases not captured by the tool (nonobserved) were collected manually for the last two quarters of the data collection period. We created logistic regression models to analyze the impact of procedure type on mortality. RESULTS: Between January 2014 and September 2015, 8,419 cases out of 11,875 were captured. Quarterly data capture rates ranged from 423 (26%) to 1,663 (93%) in the last quarter. There were 93 deaths (1.53%) reported at 7 days. Compared with four deaths (0.53%) in cesarean delivery, general surgery (n = 42 [3.65%]; odds ratio = 15.80 [95% CI, 5.20 to 48.10]; P < 0.001), neurosurgery (n = 19 [2.41%]; odds ratio = 14.08 [95% CI, 4.12 to 48.10]; P < 0.001), and emergency surgery (n = 25 [3.63%]; odds ratio = 4.40 [95% CI, 2.46 to 7.86]; P < 0.001) carried higher risks of mortality. The nonobserved group did not differ from electronically captured cases in 7-day mortality (n = 1 [0.23%] vs. n = 16 [0.58%]; odds ratio =3.95 [95% CI, 0.41 to 38.20]; P = 0.24). CONCLUSIONS: We created a simple solution for high-volume, prospective electronic collection of perioperative data in a lower- to middle-income setting. We successfully used the tool to collect a large repository of cases from a single center in Kenya and observed mortality rate differences between surgery types.

Electronically Mediated Time-out Initiative to Reduce the Incidence of Wrong Surgery: An Interventional Observational Study.

BACKGROUND: "Wrong surgery" is defined as wrong site, wrong operation, or wrong patient, with estimated incidence up to 1 per 5,000 cases. Responding to national attention on wrong surgery, our objective was to create a care redesign intervention to minimize the rate of wrong surgery. METHODS: The authors created an electronic system using existing intraoperative electronic documentation to present a time-out checklist on large in-room displays. Time-out was dynamically interposed as a forced-function documentation step between "patient-in-operating room" and "incision." Time to complete documentation was obtained from audit logs. The authors measured the postimplementation wrong surgery rate and used Bayesian methods to compare the pre- and postimplementation rates at our institution. Previous probabilities were selected using wrong surgery rate estimates from the observed performance reported in the literature to generate previous probabilities (4.24 wrong surgeries per 100,000 cases). RESULTS: No documentation times exceeded 5 min; 97% of documentation tasks were completed within 2 min. The authors performed 243,939 operations over 5 yr using the system, with zero wrong surgeries, compared with 253,838 operations over 6 yr with two wrong surgeries before implementation. Bayesian analysis suggests an 84% probability that the postimplementation wrong rate is lower than baseline. However, given the rarity of wrong surgery in our sample, there is substantial uncertainty. The total system-development cost was $34,000, roughly half the published cost of one weighted median settlement for wrong surgery. CONCLUSION: Implementation of a forced-completion electronically mediated time-out process before incision is feasible, but it is unclear whether true performance improvements occur.

An Evaluation of Induced Failure Modes in the Belmont® Rapid Infuser.

BACKGROUND: Rapid infusers are vital tools during massive hemorrhage and resuscitation. Sporadic reports of overheating and shutdown of the Belmont® Rapid Infuser, a commonly used system, have been attributed to 1-sided clot blockage of the fluid path. We investigated multiple causes of failure of this device. METHODS: Packed red blood cells and thawed fresh frozen plasma with normal saline solution were used as base fluids for serial 10-minute trials using standard disposable sets in 2 Belmont devices. Possible contributors to device failure, including calcium-containing solutions and external leakage currents, were evaluated. Thermographic images of the heater and disposable cartridges were recorded. The effects of complete unilateral clotting were modeled by sealing half of the disposable cartridge with epoxy. RESULTS: Clotting on the surface of the heat exchanger coil increased with calcium concentration and was only observed at calcium concentrations >12.0 mmol/L (P < 0.0001) in a 1:1 plasma:red blood cell mixture, resulting in high-pressure downstream occlusion alarms and interruption of flow. CONCLUSIONS: Clot-based occlusion can be induced in the Belmont Rapid Infuser under unrealistic conditions. In the absence of complete unilateral flow blockage, we did not observe any significant overheating of the infuser under extreme operating conditions.

Prolonged patient emergence time among clinical anesthesia resident trainees.

BACKGROUND AND AIMS: Emergence time, or the duration between incision closure and extubation, is costly nonoperative time. Efforts to improve operating room efficiency and identify trainee progress make such time intervals of interest. We sought to calculate the incidence of prolonged emergence (i.e., >15 min) for patients under the care of clinical anesthesia (CA) residents. We also sought to identify factors from resident training, medical history, anesthetic use, and anesthesia staffing, which affect emergence. MATERIAL AND METHODS: In this single-center, historical cohort study, perioperative information management systems provided data for surgical cases under resident care at a tertiary care center in the United States from 2006 to 2008. Using multiple logistic regression, the effects of variables on emergence was analyzed. RESULTS: Of 7687 cases under the care of 27 residents, the incidence of prolonged emergence was 13.9%. Emergence prolongation decreased by month in training for 1st-year (CA-1) residents (r2 = 0.7, P < 0.001), but not for CA-2 and CA-3 residents. Mean patient emergence time differed among 27 residents (P < 0.01 for 58.4% or 205/351 paired comparisons). In a model restricted to 1st-year residents, patient male gender, American Society of Anesthesiologists (ASA) physical status >II, emergency surgical case, operative duration ≥2 h, and paralytic agent use were associated with higher frequency of prolonged emergence, while sevoflurane or desflurane use was associated with lower frequency. Attending anesthesiologist handoff was not associated with longer emergence. CONCLUSION: Incidence of prolonged emergence from general anesthesia differed significantly among trainees, by resident training duration, and for patients with ASA >II.

Reducing intraoperative red blood cell unit wastage in a large academic medical center.

BACKGROUND: The wastage of red blood cell (RBC) units within the operative setting results in significant direct costs to health care organizations. Previous education-based efforts to reduce wastage were unsuccessful at our institution. We hypothesized that a quality and process improvement approach would result in sustained reductions in intraoperative RBC wastage in a large academic medical center. STUDY DESIGN AND METHODS: Utilizing a failure mode and effects analysis supplemented with time and temperature data, key drivers of perioperative RBC wastage were identified and targeted for process improvement. RESULTS: Multiple contributing factors, including improper storage and transport and lack of accurate, locally relevant RBC wastage event data were identified as significant contributors to ongoing intraoperative RBC unit wastage. Testing and implementation of improvements to the process of transport and storage of RBC units occurred in liver transplant and adult cardiac surgical areas due to their history of disproportionately high RBC wastage rates. Process interventions targeting local drivers of RBC wastage resulted in a significant reduction in RBC wastage (p < 0.0001; adjusted odds ratio, 0.24; 95% confidence interval, 0.15-0.39), despite an increase in operative case volume over the period of the study. Studied process interventions were then introduced incrementally in the remainder of the perioperative areas. CONCLUSIONS: These results show that a multidisciplinary team focused on the process of blood product ordering, transport, and storage was able to significantly reduce operative RBC wastage and its associated costs using quality and process improvement methods.

Automated Case Cancellation Review System Improves Systems-Based Practice.

BACKGROUND: Accreditation Council for Graduate Medical Education (ACGME) core competencies of systems-based practice and practice-based learning and improvement are difficult to assess, as they are often not directly measurable or observable. Reviewing day-of-surgery cancellations could provide resident learning opportunities in these areas. OBJECTIVE: An automated system to facilitate anesthesiology resident review of cancelled cases was implemented on the Preoperative Evaluation Clinic (PEC) rotation at the authors' institution. This study aims to evaluate its impact on resident education. METHODS: Residents on the PEC rotation during the 6 months preceding (n = 22) and following (n = 13) implementation in 2014 were surveyed about their experience performing cancelled case reviews in order to ascertain the effect of the intervention on their training. RESULTS: Significant changes were reported in the number of cases reviewed by each resident (p < 0.0001), perceived importance of review (p = 0.03), and ease of review (p = 0.03) after system implementation. There was also an increase in the proportion of cancelled cases reviewed from 17.3% (34 of 196) to 95.6% (194 of 203) (p < 0.0001). Non-significant trends were seen in perceived rotation effect on ACGME competencies, including systems-based practice. Several specific improvements to our clinical practice, including the creation of standardized guidelines, arose from these case reviews. CONCLUSION: Implementation of automated systems can improve compliance with educational goals by clarifying priorities and simplifying workflow. This system increased the number of cases reviewed by residents and the perceived importance of this review as a part of their educational experience.