Individual Anesthesiologists Research Articles

Using multi-level regression to determine associations and estimate causes and effects in clinical anesthesia due to patient, practitioner and hospital or health system practice variability.

In this research methods tutorial of clinical anesthesia, we will explore techniques to estimate the influence of a myriad of factors on patient outcomes. Big data that contain information on patients, treated by individual anesthesiologists and surgical teams, at different hospitals, have an inherent multi-level data structure (Fig.1). While researchers often attempt to determine the association between patient factors and outcomes, that does not provide clinicians with the whole story. Patient care is clustered together according to clinicians and hospitals where they receive treatment. Therefore, multi-level regression models are needed to validly estimate the influence of each factor at each level. In addition, we will explore how to estimate the influence that variability-for example, one anesthesiologist deciding to do one thing, while another takes a different approach-has on outcomes for patients, using the intra-class correlation coefficient for continuous outcomes and the median odds ratio for binary outcomes. From this tutorial, you should acquire a clearer understanding of how to perform and interpret multi-level regression modeling and estimate the influence of variable clinical practices on patient outcomes in order to answer common but complex clinical questions. Fig.1 Infographics.

Propofol Sedation in Pediatric Upper Endoscopy: A Study of Pharmacodynamics and the Effects of Gastroenterologists, Anesthesiologists, and Supervised Participants on the Procedure Time and Sedation Time.

Background and aims Propofol combined with fentanyl is a commonly used sedative for pediatric upper endoscopies (UEs). The primary aim was to study the association betweenpropofol dose and procedure and sedation time. The secondary aims were to assess the pharmacodynamics of propofol use with fentanyland evaluate if gastroenterologists' and anesthesiologists' years of experience or the presence of supervised participants (such as students, residents, and fellows) have any influence on the procedure and sedation time. Methods A retrospective study was performed at the Children's Hospital of Michigan on patients under 18 years who underwent UEs with propofol sedation with fentanyl over a two-year period. Results A correlation was found between the propofol amount used expressed per body mass index(BMI)/body surface area (BSA), procedure time, and sedation time (p < 0.0001). Throat pain was the most common post-procedural adverse event (4.48%). The impact of psychoactive drugs on these events was not statistically significant, but attention-deficit/hyperactivity disorder (ADHD) medication use was related to increased post-procedural pain complaints. The use of prescribed psychoactive medications was associated with larger propofol dose usage (p = 0.007) without a significant increase in sedation time. Individual gastroenterologists, their years of experience, and the presence of supervised participants were associated with different procedure times (p <0.0001, <0.0001, 0.01). Fellow participation was associated with a 1.11-minute procedure time increase (p = 0.04). Individual anesthesiologists, their years of experience, and the presence of supervised participants were associated with different sedation times (p <0.0001, <0.0001, 0.01). Conclusion We found a novel correlation between propofol dosing expressed by the BMI/BSA and sedation time. The UE procedure time and sedation time are associated with individual gastroenterologists and anesthesiologists, their years of experience, and the presence of supervised participants.

Measuring and Comparing Clinical Productivity of Individual Anesthesiologists.

Measuring and comparing clinical productivity of individual anesthesiologists is confounded by anesthesiologist-independent factors, including facility-specific factors (case duration, anesthetizing site utilization, type of surgical procedure, and non-operating room locations), staffing ratio, number of calls, and percentage of clinical time providing anesthesia. Further, because anesthesia care is billed with different units than relative value units, comparing work with other types of clinical care is difficult. Finally, anesthesia staffing needs are not based on productivity measurements but primarily the number and hours of operation of anesthetizing sites. The intent of this review is to help anesthesiologists, anesthesiology leaders, and facility leaders understand the limitations of anesthesia unit productivity as a comparative metric of work, how this metric often devalues actual work, and the impact of organizational differences, staffing models and coverage requirements, and effectiveness of surgical case load management on both individual and group productivity.

Overall anesthesia department quality of clinical supervision of trainees over a year evaluated using mixed effects models

BackgroundEarlier studies of supervision in anesthesiology focused on how to evaluate the quality of individual anesthesiologist's clinical supervision of trainees. What is unknown is how to evaluate clinical supervision collectively, as provided by the department's faculty anesthesiologists. This information can be a metric that departments report annually or use to evaluate the effect of programs on the quality of clinical supervision over time. MethodsThis retrospective cohort study used all 48,788 evaluations of the 115 faculty anesthesiologists using the De Oliveira Filho supervision scale completed by 202 residents and fellows over nine academic years at one department. ResultsThe distributions of mean scores among raters had marked negative skewness and were inconsistent with normal distributions. Consequently, accurate confidence intervals were impracticably wide, and their interpretation suggested lack of validity. In contrast, the logits of the proportions of scores equaling the maximum possible value, calculated for each rater, followed distributions sufficiently close to normal for statistically reliable use in random effects modeling. Parameters and confidence intervals were estimated using the intercept only random effects models, and then inverses computed to convert results from the logit scale to proportions. That approach is analogous to random effect meta-analysis of proportional incidence (or prevalence). Departments that chose to use semi-annual or annual surveys of trainees regarding supervision quality, and report those raw counts, will have far lower estimates of supervision quality versus when calculated accurately using daily evaluations of individual anesthesiologists. ConclusionsRandom effects meta-analysis of percentage incidences of maximum scores is a suitable statistical approach to analyze the daily supervision scores of individual anesthesiologists to evaluate the overall quality of clinical supervision provided to the trainees by the department over a year.

Implementing pathways to anesthesiology: Promoting diversity, equity, inclusion, and success.

Implementing pathways to anesthesiology: Promoting diversity, equity, inclusion, and success.

Preoperative prediction of the need for arterial and central venous catheterization using machine learning techniques

Some surgical patients require an arterial or central venous catheterization intraoperatively. This decision relied solely on the experience of individual anesthesiologists; however, these decisions are not easy for clinicians who are in an emergency or inexperienced. Therefore, applying recent artificial intelligence techniques to automatically extractable data from electronic medical record (EMR) could create a very clinically useful model in this situation. This study aimed to develop a model that is easy to apply in real clinical settings by implementing a prediction model for the preoperative decision to insert an arterial and central venous catheter and that can be automatically linked to the EMR. We collected and retrospectively analyzed data from 66,522 patients, > 18 years of age, who underwent non-cardiac surgeries from March 2019 to April 2021 at the single tertiary medical center. Data included demographics, pre-operative laboratory tests, surgical information, and catheterization information. When compared with other machine learning methods, the DNN model showed the best predictive performance in terms of the area under receiver operating characteristic curve and area under the precision-recall curve. Operation code information accounted for the largest portion of the prediction. This can be applied to clinical fields using operation code and minimal preoperative clinical information.

Seven years on from the Canadian Airway Focus Group Difficult Airway Guidelines: an observational survey.

PurposeNumerous clinical guidelines are available for management of the unanticipated difficult airway. It is unclear if practice recommendations are endorsed on regional, local, or individual levels. The objective of this observational study was to examine local and regional use of airway guidelines by anesthesiologists within a hospital partnership in Southwestern Ontario.MethodsUsing a paper survey, distributed locally to consultant and trainee anesthesiologists in a tertiary hospital, we examined individual clinical and educational practices regarding guideline use in airway management. Respondents were asked to report which published guideline they used for unanticipated airway difficulty. The effectiveness of dissemination of the national Canadian airway guidelines—the Canadian Airway Focus Group (CAFG) Difficult Airway Guidelines—was examined. We invited anesthesia department heads within the regional hospital partnership to complete an electronic survey investigating departmental adoption of guidelines.ResultsThe response rate was 70% locally (79/112 anesthesiologists) and 52% regionally (11/21 department heads). Approximately 80% (64/79) of respondents reported using a formal clinical guideline if unanticipated difficulty with airway management was encountered. Seventy-two per cent of respondents (57/79) were aware of the published CAFG guidelines. Approximately 30% (16/51) of consultant anesthesiologists reported using the CAFG guidelines in clinical practice. Within the hospital partnership, 36% (4/11) of departments formally endorsed use of a specific airway management guideline.ConclusionsDespite widespread awareness of the national CAFG Difficult Airway Guidelines, they are not widely adopted in clinical practice. Further research is warranted to explore barriers to adoption of airway management guidelines for both individual anesthesiologists and anesthesia departments.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12630-021-02056-5.

Sustained management of the variability in work hours among anesthesiologists providing patient care in operating rooms and not on call to work late if necessary

Study objectiveWe evaluated a department's long-term (6.5-year) success of achieving an overall and individual incidence of anesthesiologists working late of approximately 20% of days when not on call to work late, if necessary, and providing care in operating rooms. DesignHistorical cohort study, January 2014 through September 2020. SettingInpatient surgical suite of large teaching hospital. Main resultsThe percentage of days worked past 5:00 PM was mean (standard deviation) 17.7% (5.0%) of days, 99% confidence interval (CI) 15.0% to 20.4%. There was considerable variability among quarters, the coefficient of variation being 28% (99% CI 20% to 45%). This was caused, in part, by anesthesiologists less often working late during January–March versus July–September (14.0% [4.5%] versus 21.6% [3.2%]; P = 0.0031; N = 7 years each). The N = 67 anesthesiologists not on call differed in their percentages of workdays finishing after 5:00 PM (P < 0.0001). While the mean was 18% (6%), the coefficient of variation was 37% (29% to 49%). There were no significant outliers. In contrast, not only were there differences among anesthesiologists in the relative risks of working late when receiving relief versus when not handing off a case (P < 0.0001), there were outliers. ConclusionsAn anesthesia department aiming for a 20% incidence of anesthesiologists having to work late when not on call can achieve this objective, long-term, within a few percent (e.g., 2%). Seasonal variation can contribute to variability among quarters in the overall departmental incidence. Individual anesthesiologists can have variability among themselves, though, and that is caused by large heterogeneity in their relative risks of working late when receiving relief versus when not handing off a case. For departments choosing to provide information to anesthesiologists to increase predictability, factors to consider should include season of the year and the individual anesthesiologist.

How Anesthesiologists Experience and Negotiate Ethical Challenges from Drug Shortages

Background In the face of ongoing drug shortages, anesthesiologists have been described as having to become “Iron Chefs, challenged to create safe patient outcomes with missing ingredients. Unfortunately, developing responsive ethical guidance for how anesthesiologists should best handle ethical concerns with ongoing and mutable drug shortages is limited by the dearth of studies examining how bedside clinicians actually experience drug shortages and what ethical challenges they encounter. In order to better understand what ethical concerns individual anesthesiologists experience around drug shortages and how they negotiate them, we undertook this qualitative interview study. Methods: We conducted semi-structured interviews with anesthesiologists at three field sites: an academic tertiary care adult hospital that performs approximately 46,000 anesthetics annually comprising cases ranging across all surgical disciplines; the affiliated veteran’s affairs hospital that performs 12,000 anesthetics annually; and, the affiliated children’s hospital that performs 20,500 anesthetics annually. Results: 29 anesthesiologists were interviewed (17 adult and 12 pediatric anesthesiologists), representing a spectrum of practice areas in clinical anesthesia: general, pediatric, regional, pain, critical care, obstetrics, liver transplant, and palliative medicine. Three themes emerged: (1) uncertainty about responsibility for clinical decisions made in consequence to a shortage; (2) creativity, and its limits, in choosing anesthetic plans; and, (3) disclosure of concerns about shortages (to patients and colleagues). Conclusions: Our data suggests anesthesiologists have unmet needs for ethical guidance on how to approach drug shortages. First is managing responsibility for decisions stemming from a drug shortage. Second, interviewees struggled with disclosure of their concerns, both to patients and to surgical colleagues. A formal shared decision making approach may present the best solution, since the act of structuring a shared decision making conversation or creating a decision making tool will have to incorporate the views of all stakeholders around shortages and their potential clinical consequences.

Real-Time Locating Systems and the Effects on Efficiency of Anesthesiologists

To investigate the impact of Real Time Locating System (RTLS) technology on the perioperative efficiency of anesthesiologists. A retrospective chart review was performed for all outpatient and short-stay patients who received General Anesthesia care at our institution between January 2016 and October 2017. Patients included were over 18 years and had ASA classification scores of 1, 2, and 3. Only first cases of the day for individual anesthesiologists were included. Duration between two perioperative time points was collected and used as a measure of efficiency. Two groups of anesthesiologists were compared Group 1: Anesthesiologists at Main Campus who do not use RTLSGroup 2: Anesthesiologists at Josie Robertson Surgery Center who use RTLSThe outcome measure collected from patient electronic medical records was defined as DUR: Duration from when patient is admitted to the operating room and initiation of induction only for first case of the day by attending anesthesiologist. The outcome was compared between the two groups using Wilcoxon rank sum test. The duration between admission to the OR and initiation of induction was significantly shorter in JRSC (with RTLS) than main campus (without RTLS); specifically, median (25th, 75th percentile) of the duration was 7.0 (5.0, 10.0) at JRSC vs. 8.0 (6.0, 11.0) at main campus (p < 0.0001, Table 1). In our initial study, we found that anesthesiologists who had access to RTLS at JRSC performed more efficiently in their preoperative evaluation of patients as well as time to induction for general anesthesia cases. Because of various confounding factors that potentially influenced the increase in efficiency of anesthesiologists with access to RTLS, this follow-up study aims to eliminate several confounding factors by assessing only time to induction of general anesthesia for all first cases of the day by anesthesiologists. We continue to find a small yet statistically significant difference in time to induction of anesthesiologists with access to RTLS. This translates directly into increased efficiency in perioperative workflow. Additional investigation and application can help elucidate the true value of RTLS on workflow efficiency in the healthcare setting.

Antiemetic Prophylaxis as a Marker of Health Care Disparities in the National Anesthesia Clinical Outcomes Registry.

US health care disparities persist despite repeated countermeasures. Research identified race, ethnicity, gender, and socioeconomic status as factors, mediated through individual provider and/or systemic biases; little research exists in anesthesiology. We investigated antiemetic prophylaxis as a surrogate marker for anesthesia quality by individual providers because antiemetics are universally available, indicated contingent on patient characteristics (gender, age, etc), but independent of comorbidities and not yet impacted by regulatory or financial constraints. We hypothesized that socioeconomic indicators (measured as insurance status or median income in the patients' home zip code area) are associated with the utilization of antiemetic prophylaxis (as a marker of anesthesia quality). We tested our hypothesis in several subsets of electronic anesthesia records from the National Anesthesia Clinical Outcomes Registry (NACOR), fitting frequentist and novel Bayesian multilevel logistic regression models. NACOR contained 12 million cases in 2013. Six institutions reported on antiemetic prophylaxis for 441,645 anesthesia cases. Only 173,133 cases included details on insurance information. Even fewer (n = 92,683) contained complete data on procedure codes and provider identifiers. Bivariate analysis, multivariable logistic regression, and our Bayesian hierarchical model all showed a large and statistically significant association between socioeconomic markers and antiemetic prophylaxis (ondansetron and dexamethasone). For Medicaid versus commercially insured patients, the odds ratio of receiving the antiemetic ondansetron is 0.85 in our Bayesian hierarchical mixed regression model, with a 95% Bayesian credible interval of 0.81-0.89 with similar inferences in classical (frequentist) regression models. Our analyses of NACOR anesthesia records raise concerns that patients with lower socioeconomic status may receive inferior anesthesia care provided by individual anesthesiologists, as indicated by less antiemetics administered. Effects persisted after we controlled for important patient characteristics and for procedure and provider influences. Findings were robust to sensitivity analyses. Our results challenge the notion that anesthesia providers do not contribute to health care disparities.

Amnesia of the Operating Room in the B-Unaware and BAG-RECALL Clinical Trials.

Patient memories of the operating room (OR) may serve as the informational basis for assessing satisfaction with individual anesthesiologists. Furthermore, the provision of clinically important information may assume that perioperative memories are retained. Studies assessing the extent of perioperative amnesia and factors associated with perioperative amnesia are sparse. Therefore, we assessed patient amnesia of the OR and of the preoperative holding area in hospitals where midazolam is typically administered in the preoperative holding area and evaluated whether midazolam dose administered in the preoperative holding area and patient age were associated with amnesia of the OR before induction of anesthesia. This was a retrospective study among 7750 adult patients who had general anesthesia and participated in the B-Unaware and Bispectral Index or Anesthetic Gas to Reduce Explicit Recall (BAG-RECALL) clinical trials. The last location the patient remembered before induction of anesthesia and the first location they remembered after induction of anesthesia were determined through a modified Brice questionnaire administered over the phone 30 days postoperatively. Regarding the preoperative period, patients were excluded if their last memory was unclear with respect to location before induction of anesthesia or if they were recruited at Winnipeg, where midazolam was typically first administered in the OR. Midazolam dose (mg/kg) administered in the preoperative holding area was divided into quartiles. Poisson regression models were used to calculate age- and multivariable-adjusted odds ratios (95% confidence intervals [CIs]) for the association between midazolam dose and amnesia of the OR before induction of anesthesia. Of the 5339 patients included, 59.5% (95% CI, 58.2–60.9) of patients had amnesia of the OR before induction of anesthesia. In addition, 44.1% (95% CI, 42.8–45.7) last remembered the preoperative holding area, and 15.4% (95% CI, 14.4–16.4) only had preoperative memories before the holding area. The percentages of patients with amnesia of the OR before induction of anesthesia differed according to age groups: 50.7% (95% CI, 47.7%–53.7%) in patients aged 18 to 47 years versus 70.0% (95% CI, 67.0%–72.9%) in patients aged 73 to 99 years. Patients in the highest midazolam quartile had an adjusted prevalence ratio of 1.31 (95% CI, 1.22–1.42) for amnesia of the OR compared with those who did not receive midazolam. In hospitals where patients typically receive midazolam in the preoperative holding area, the majority of patients do not remember the OR, and a clinically relevant number of patients does not remember the preoperative holding area. If additional studies produce results indicating that a substantial proportion of patients has amnesia of the anesthesiologist, these findings would argue against the validity of assessing patient satisfaction with individual anesthesiologists providing exclusively OR care in such hospitals. Furthermore, if additional studies yield findings suggesting patient amnesia of the preoperative holding area, these results would suggest reconsideration of providing clinically important information only in the preoperative holding area. Older age and midazolam-induced anterograde amnesia are probably associated with impaired perioperative memories.

Quality of Supervision as an Independent Contributor to an Anesthesiologist's Individual Clinical Value.

Although the clinical (operating room) production of individual anesthesiologists has been measured in multiple related ways (e.g., hours of direct clinical care), the same is not true for the quality of that effort. In our study, we consider the quality of clinical supervision provided by anesthesiologists who are supervising anesthesia residents and nurse anesthetists. The quality of the daily supervision can be measured reliably and validly using the scale developed by de Oliveira Filho et al. If clinical production and supervisory quality were not positively correlated, then it would be important for departments to measure the quality of clinical supervision because, essentially, the clinical value provided by an anesthesiologist would be correlated with, but not necessarily proportional to, their clinical hours. Our department sends daily e-mail requests to anesthesia residents and nurse anesthetists to evaluate the supervision provided by each anesthesiologist with whom they worked the previous day in an operating room setting. We compared anesthesiologists' clinical activity (total operating room hours) and supervision scores obtained during the first (July 1, 2013 to December 31, 2013) and last (July 1, 2014 to December 31, 2014) of 3 consecutive 6-month periods. During the first 6 months, anesthesiologists received no feedback regarding the supervision scores. During the last 6 months, there was feedback to all anesthesiologists regarding their individual supervision scores and comments provided by residents (during the preceding 6 months) and nurse anesthetists (during the preceding 12 months). Anesthesiologists' mean supervision scores were not positively correlated with their total (weekly) hours of clinical activity. For the first 6 months, the correlations were r = -0.18 among scores provided by residents (P = 0.92 for positive correlation, N = 57 anesthesiologists) and r = -0.04 among scores provided by nurse anesthetists (P = 0.70, N = 61). For the last 6 months, the correlations were r = -0.28 (P = 0.98) and r = -0.10 (P = 0.79), respectively. Pairwise by anesthesiologist, the mean supervision scores provided by residents increased by 0.08 ± 0.01 points (P < 0.0001, N = 44). The mean supervision scores provided by nurse anesthetists increased by 0.28 ± 0.02 points (P < 0.0001, N = 49). When anesthesiologists supervise anesthesia residents and nurse anesthetists, the amount of clinical work performed and the quality of the supervision provided do not necessarily follow one another. Thus, faculty supervision scores serve as an independent measure of the contribution of an individual anesthesiologist to the care of the patient. Furthermore, when supervision quality is monitored and feedback is provided to anesthesiologists, quality can increase. The results suggest that anesthesiology department managers should not only be monitoring (and perhaps reporting) the quality of their departments' level of supervision, but also establishing processes so that individual anesthesiologists can learn about the quality of supervision they provide.

Reliability and Validity of Assessing Subspecialty Level of Faculty Anesthesiologists’ Supervision of Anesthesiology Residents

Supervision of anesthesiology residents is a major responsibility of faculty (academic) anesthesiologists. Supervision can be evaluated daily for individual anesthesiologists using a 9-question instrument. Faculty anesthesiologists with lesser individual scores contribute to lesser departmental (global) scores. Low (<3, "frequent") department-wide evaluations of supervision are associated with more mistakes with negative consequences to patients. With the long-term aim for residency programs to be evaluated partly based on the quality of their resident supervision, we assessed the 9-item instrument's reliability and validity when used to compare anesthesia programs' rotations nationwide. One thousand five hundred residents in the American Society of Anesthesiologists' directory of anesthesia trainees were randomly selected to be participants. Residents were contacted via e-mail and requested to complete a Web-based survey. Nonrespondents were mailed a paper version of the survey. Internal consistency of the supervision scale was excellent, with Cronbach's α = 0.909 (95% CI, 0.896-0.922, n = 641 respondents). Discriminant validity was found based on absence of rank correlation of supervision score with characteristics of the respondents and programs (all P > 0.10): age, hours worked per week, female, year of anesthesia training, weeks in the current rotation, sequence of survey response, size of residency class, and number of survey respondents from the current rotation and program. Convergent validity was found based on significant positive correlation between supervision score and variables related to safety culture (all P < 0.0001): "Overall perceptions of patient safety," "Teamwork within units," "Nonpunitive response to errors," "Handoffs and transitions," "Feedback and communication about error," "Communication openness," and rotation's "overall grade on patient safety." Convergent validity was found also based on significant negative correlation with variables related to the individual resident's burnout (all P < 0.0001): "I feel burnout from my work," "I have become more callous toward people since I took this job," and numbers of "errors with potential negative consequences to patients [that you have] made and/or witnessed." Usefulness was shown by supervision being predicted by the same 1 variable for each of 3 regression tree criteria: "Teamwork within [the rotation]" (e.g., "When one area in this rotation gets busy, others help out"). Evaluation of the overall quality of supervision of residents by faculty anesthesiologists depends on the reliability and validity of the instrument. Our results show that the 9-item de Oliveira Filho et al. supervision scale can be applied for overall (department, rotation) assessment of anesthesia training programs.

Anesthesia residents' global (departmental) evaluation of faculty anesthesiologists' supervision can be less than their average evaluations of individual anesthesiologists.

Faculty anesthesiologists' supervision of anesthesiology residents is required for both postgraduate medical education and billing compliance. Previously, using the de Oliveira Filho et al. supervision question set, De Oliveira et al. found that residents who reported mean department-wide supervision scores <3.0 ("frequent") reported a significantly more frequent occurrence of mistakes with negative consequences to patients, as well as medication errors. In our department, residents provide daily evaluations of the supervision received by individual faculty. Using a survey study, we compared relationships between residents' daily supervision scores for individual faculty anesthesiologists and residents' supervision scores for the entire department (comprised these faculty). We studied all anesthesiology residents in clinical years 1, 2, and 3 (i.e., neither in the "base year" nor in fellowship). There were daily evaluations of individual faculty supervision of operative anesthesia for 36 weeks. Residents clicked a hyperlink on the invitation e-mail taking them to a secure Web page to provide their global (departmental) assessment of faculty supervision. We calculated the ratio of each resident's global (departmental) faculty supervision score (i.e., mean among 9 questions × 1 evaluation) to the same resident's daily evaluations of individual faculty (i.e., mean among 9 questions × many evaluations). All 39 of 39 residents chose to participate. The mean departmental supervision score was significantly less (P < 0.0001) than the mean of individual faculty scores. The median ratio of scores was 86% (95% confidence interval, 83%-89%). Kendall's rank correlation between global and (mean) individual faculty scores was τb = 0.34 ± 0.11 (P = 0.0032). The ratios were uniformly distributed (P = 0.64) between the observed minimums and maximums; were not correlated with the mean value of individual faculty scores previously provided by each resident (P = 0.64); were not correlated with the number of individual faculty evaluations previously provided by each resident (P = 0.49); and did not differ among the first, second, or third year residents (P = 0.37). Residents' perceptions of overall (departmental) faculty supervision were less than overall averages of their perceptions of individual faculty supervision. This should be considered when interpreting national survey results (e.g., of patient safety), residency program evaluations, and individual faculty anesthesiologist performance.

Operating room metrics score card-creating a prototype for individualized feedback.

The balance between reducing costs and inefficiencies with that of patient safety is a challenging problem faced in the operating room suite. An ongoing challenge is the creation of effective strategies that reduce these inefficiencies and provide real-time personalized metrics and electronic feedback to anesthesia practitioners. We created a sample report card structure, utilizing existing informatics systems. This system allows to gather and analyze operating room metrics for each anesthesia provider and offer personalized feedback. To accomplish this task, we identified key metrics that represented time and quality parameters. We collected these data for individual anesthesiologists and compared performance to the overall group average. Data were presented as an electronic score card and made available to individual clinicians on a real-time basis in an effort to provide effective feedback. These metrics included number of cancelled cases, average turnover time, average time to operating room ready and patient in room, number of delayed first case starts, average induction time, average extubation time, average time to recovery room arrival to discharge, performance feedback from other providers, compliance to various protocols, and total anesthetic costs. The concept we propose can easily be generalized to a variety of operating room settings, types of facilities and OR health care professionals. Such a scorecard can be created using content that is important for operating room efficiency, research, and practice improvement for anesthesia providers.

Public awareness about the specialty of anesthesiology and the role of anesthesiologists: a national survey

BackgroundThe aims of this national survey were to determine the views of Korean people regarding the specialty of anesthesiology and the role of anesthesiologists and to consider the ways in which individual anesthesiologists and the Korean Society of Anesthesiologists inform the public.MethodsThis off-line national survey was conducted by a professional research organization to obtain exact and reliable data. The questionnaire included structured questions to identify perceptions of the specialty of anesthesiology and the role of anesthesiologists inside and outside the operating room, people's desire for explanation of anesthesia by anesthesiologists, and their opinion about the best way to raise awareness about anesthesia and anesthesiologists.ResultsOf the respondents, 25.2% did not know that anesthesiologists are in charge of anesthesia during surgery. Furthermore, even respondents who knew that had very little knowledge of anesthesiologists' actual roles inside and outside the operating room. Respondents wanted their anesthesiologist to inform them about their anesthesia.ConclusionsThe public's awareness regarding the role of anesthesiologists seems to be inadequate. To improve this awareness, in hospitals, each anesthesiologist should provide patients with more exact and detailed information. Simultaneously, the National Society of Anesthesiology should provide systematic information reflecting the public's thoughts.

Anaesthetic and Perioperative Complications

Anesthesia, like most fields of medicine, has now become evidence based. Protocols are established for management of scenarios ranging from conscious sedation to cardiac arrest. The chapters of the Clinical Aspects of Complications section of Anaesthetic and Perioperative Complications begin with the ABCs of anesthesia: airway, breathing (respiration), and circulation. They are organized in the format of prevention, recognition, and management of anesthetic-related complications. Checklists are included in several chapters, but are sorely missed in others.The chapter devoted to airway complications lists the Difficult Airway Society algorithm for managing unanticipated difficult intubation. It wisely includes the point of not making more than three attempts at rigid laryngoscopy and the need to use an alternative laryngoscope (either video or fiberoptic through a laryngeal mask airway). The chapter includes the caveat from the American Society of Anesthesiologists closed claims studies showing that fatal complications can occur after oversedation during attempts at awake intubation. In the presence of a compromised airway, less sedation and more cooperation are better than obtundation and airway obstruction.The sections on cardiovascular complications include a table on the differential diagnosis of intraoperative hypotension and an excellent table covering perioperative pharmacological cardiac protection. It would have been useful to have included a forest plot of the efficacy of the various therapies of antiplatelet, antithrombin, β blockers, and statins in preventing perioperative myocardial ischemia.The obstetric anesthetic chapter makes the recommendation that the conversion rate of regional to general anesthesia should be less than 3%. This is a laudable goal, considering that the National Audit Project (NAP4) found that two out of four failed intubations for cesarean section occurred in association with failed regional anesthesia. The paragraph on providing adequate doses of local anesthetic states that fentanyl 10 mg given intrathecally needs to be corrected to 10 mcg. This chapter lacks a section on the prevention and management of postpartum hemorrhage, now a major cause of maternal mortality.The chapter devoted to perioperative neurological complications presents several current controversies in the realm of whether more monitoring can prevent complications. Logically, one would suspect that operative spinal cord injury should be reduced by monitoring somatosensory evoked potentials, motor-evoked potentials, and electromyography, but this information is not referenced.The B-Aware and B-Unaware trials failed to show that awareness occurs more often with solely monitoring end-tidal concentrations of volatile anesthetics compared with the bispectral index monitor. However, many anesthetics are delivered as total intravenous agents, with propofol providing amnesia and remifentanil supplying the analgesia, so there is no vapor level to measure, thus making the bispectral index an essential monitor of anesthetic depth.A good part of the regional anesthesia complications chapter is devoted to vertebral canal hematomas after epidural placement. A table listing drugs acting on the coagulation cascade and their half-lives should have been provided. Instead, a figure, labeled management of leg weakness following epidural anesthesia, lists pager numbers of the acute pain team at Derriford Hospital, Plymouth, England. However, the table devoted to management of local anesthetic toxicity is well annotated.The drug reaction chapter clearly states that two thirds of allergic anaphylactic reactions in anesthesia are due to succinylcholine and rocuronium. Serum tryptase levels should be measured to confirm an immunoglobulin E–mediated reaction.The last portion of the book discusses the legal ramifications of anesthetic mishaps. The case of Mrs. Elaine Bromiley, the 37-yr-old wife of an airline pilot, is presented. As the result of a “can’t intubate, can’t ventilate” situation, multiple attempts at intubation were made, rather than an emergency cricothyroidotomy. Despite all the algorithms and training, perhaps our basic equipment needs updating to the 21st century. Would this complication have been avoided if the initial attempt at intubation was with a video laryngoscope or an inexpensive disposable video bronchoscope?With the advent of electronic medical records, it will be possible to monitor performance of individual anesthesiologists, especially when complications occur. This book outlines potential pitfalls. We would be wise to read it carefully and incorporate its lessons into our daily practice.

Blood loss, predictors of bleeding, transfusion practice and strategies of blood cell salvaging during liver transplantation

Blood loss during liver transplantation (OLTx) is a common consequence of pre-existing abnormalities of the hemostatic system, portal hypertension with multiple collateral vessels, portal vein thrombosis, previous abdominal surgery, splenomegaly, and poor "functional" recovery of the new liver. The intrinsic coagulopathic features of end stage cirrhosis along with surgical technical difficulties make transfusion-free liver transplantation a major challenge, and, despite the improvements in understanding of intraoperative coagulation profiles and strategies to control blood loss, the requirements for blood or blood products remains high. The impact of blood transfusion has been shown to be significant and independent of other well-known predictors of posttransplant-outcome. Negative effects on immunomodulation and an increased risk of postoperative complications and mortality have been repeatedly demonstrated. Isovolemic hemodilution, the extensive utilization of thromboelastogram and the use of autotransfusion devices are among the commonly adopted procedures to limit the amount of blood transfusion. The use of intraoperative blood salvage and autologous blood transfusion should still be considered an important method to reduce the need for allogenic blood and the associated complications. In this article we report on the common preoperative and intraoperative factors contributing to blood loss, intraoperative transfusion practices, anesthesiologic and surgical strategies to prevent blood loss, and on intraoperative blood salvaging techniques and autologous blood transfusion. Even though the advances in surgical technique and anesthetic management, as well as a better understanding of the risk factors, have resulted in a steady decrease in intraoperative bleeding, most patients still bleed extensively. Blood transfusion therapy is still a critical feature during OLTx and various studies have shown a large variability in the use of blood products among different centers and even among individual anesthesiologists within the same center. Unfortunately, despite the large number of OLTx performed each year, there is still paucity of large randomized, multicentre, and controlled studies which indicate how to prevent bleeding, the transfusion needs and thresholds, and the "evidence based" perioperative strategies to reduce the amount of transfusion.

Variability in Blood and Blood Component Utilization as Assessed by an Anesthesia Information Management System

Data can be collected for various purposes with anesthesia information management systems. The authors describe methods for using data acquired from an anesthesia information management system to assess intraoperative utilization of blood and blood components. Over an 18-month period, data were collected on 48,086 surgical patients at a tertiary care academic medical center. All data were acquired with an automated anesthesia recordkeeping system. Detailed reports were generated for blood and blood component utilization according to surgical service and surgical procedure, and for individual surgeons and anesthesiologists. Transfusion hemoglobin trigger and target concentrations were compared among surgical services and procedures, and between individual medical providers. For all patients given erythrocytes, the mean transfusion hemoglobin trigger was 8.4 ± 1.5, and the target was 10.2 ± 1.5 g/dl. Variation was significant among surgical services (trigger range: 7.5 ± 1.2-9.5 ± 1.1, P = 0.0001; target range: 9.1 ± 1.2-11.3 ± 1.4 g/dl, P = 0.002), surgeons (trigger range: 7.2 ± 0.7-9.8 ± 1.0, P = 0.001; target range: 8.8 ± 0.9-11.8 ± 1.3 g/dl, P = 0.001), and anesthesiologists (trigger range: 7.2 ± 0.8-9.6 ± 1.2, P = 0.001; target range: 9.0 ± 0.9-11.7 ± 1.3 g/dl, P = 0.0004). The use of erythrocyte salvage, fresh frozen plasma, and platelets varied threefold to fourfold among individual surgeons compared with their peers performing the same surgical procedure. The use of data acquired from an anesthesia information management system allowed a detailed analysis of blood component utilization, which revealed significant variation among surgical services and surgical procedures, and among individual anesthesiologists and surgeons compared with their peers. Incorporating these methods of data acquisition and analysis into a blood management program could reduce unnecessary transfusions, an outcome that may increase patient safety and reduce costs.