National Delphi Survey on Anesthesiology Resident Training in Perioperative Ultrasound.

OBJECTIVE: To establish agreement among nationwide experts through a Delphi process on the key components of perioperative ultrasound and the recommended minimum number of examinations that should be performed by a resident upon graduation. DESIGN: A prospective cross-sectional study. SETTING: A survey on multiinstitutional academic medical centers. PARTICIPANTS: Anesthesiology residency program directors and/or experts in perioperative ultrasound. INTERVENTIONS: A list of components and examinations recommended for anesthesiology resident training in perioperative ultrasound was developed based on guidelines and 2 survey rounds among a steering committee of 10 experts. A questionnaire asking for a rating of each component on a 5-point Likert scale subsequently was sent to an expert panel of 120 anesthesiology residency program directors across the United States. An agreement of at least 70% of participants, rating a component as 4 or 5, was compulsory to list a component as essential for anesthesiology resident training in perioperative ultrasound. MEASUREMENTS AND MAIN RESULTS: The nationwide survey's response rate was 62.5%, and agreement was reached after 2 Delphi rounds. The final list included 44 essential components for basic ultrasound physics and knobology, cardiac ultrasound, lung ultrasound, and ultrasound-guided vascular access. Agreement was not reached for abdominal ultrasound, gastric ultrasound, and ultrasound-guided airway assessment. Agreement for the recommended minimum number of examinations that should be performed by a resident upon graduation included 50 each for transthoracic and transesophageal echocardiography, and 20 each for lung ultrasound, ultrasound-guided central line, and ultrasound-guided arterial line placements. CONCLUSIONS: The recommendations outlined in this survey can be used to establish standardized training for perioperative ultrasound by anesthesiology residency programs.

Assessing Interrater Reliability of a Faculty-Provided Feedback Rating Instrument.

High quality feedback on resident clinical performance is pivotal to growth and development. Therefore, a reliable means of assessing faculty feedback is necessary. A feedback assessment instrument would also allow for appropriate focus of interventions to improve faculty feedback. We piloted an assessment of the interrater reliability of a seven-item feedback rating instrument on faculty educators trained via a three-workshop frame-of-reference training regimen. The rating instrument's items assessed for the presence or absence of six feedback traits: actionable, behavior focused, detailed, negative feedback, professionalism / communication, and specific; as well as for overall utility of feedback with regard to devising a resident performance improvement plan on an ordinal scale from 1 to 5. Participants completed three cycles consisting of one-hour-long workshops where an instructor led a review of the feedback rating instrument on deidentified feedback comments, followed by participants independently rating a set of 20 deidentified feedback comments, and the study team reviewing the interrater reliability for each feedback rating category to guide future workshops. Comments came from four different anesthesia residency programs in the United States; each set of feedback comments was balanced with respect to utility scores to promote participants' ability to discriminate between high and low utility comments. On the third and final independent rating exercise, participants achieved moderate or greater interrater reliability on all seven rating categories of a feedback rating instrument using Gwet's agreement coefficient 1 for the six feedback traits and using intraclass correlation for utility score. This illustrates that when this instrument is utilized by trained, expert educators, reliable assessments of faculty-provided feedback can be made. This rating instrument, with further validity evidence, has the potential to help programs reliably assess both the quality and utility of their feedback, as well as the impact of any educational interventions designed to improve feedback.

Using Machine Learning to Evaluate Attending Feedback on Resident Performance.

BACKGROUND: High-quality and high-utility feedback allows for the development of improvement plans for trainees. The current manual assessment of the quality of this feedback is time consuming and subjective. We propose the use of machine learning to rapidly distinguish the quality of attending feedback on resident performance. METHODS: Using a preexisting databank of 1925 manually reviewed feedback comments from 4 anesthesiology residency programs, we trained machine learning models to predict whether comments contained 6 predefined feedback traits (actionable, behavior focused, detailed, negative feedback, professionalism/communication, and specific) and predict the utility score of the comment on a scale of 1-5. Comments with ≥4 feedback traits were classified as high-quality and comments with ≥4 utility scores were classified as high-utility; otherwise comments were considered low-quality or low-utility, respectively. We used RapidMiner Studio (RapidMiner, Inc, Boston, MA), a data science platform, to train, validate, and score performance of models. RESULTS: Models for predicting the presence of feedback traits had accuracies of 74.4%-82.2%. Predictions on utility category were 82.1% accurate, with 89.2% sensitivity, and 89.8% class precision for low-utility predictions. Predictions on quality category were 78.5% accurate, with 86.1% sensitivity, and 85.0% class precision for low-quality predictions. Fifteen to 20 hours were spent by a research assistant with no prior experience in machine learning to become familiar with software, create models, and review performance on predictions made. The program read data, applied models, and generated predictions within minutes. In contrast, a recent manual feedback scoring effort by an author took 15 hours to manually collate and score 200 comments during the course of 2 weeks. CONCLUSIONS: Harnessing the potential of machine learning allows for rapid assessment of attending feedback on resident performance. Using predictive models to rapidly screen for low-quality and low-utility feedback can aid programs in improving feedback provision, both globally and by individual faculty.

Educating Anesthesiologists During the Coronavirus Disease 2019 Pandemic and Beyond.

The coronavirus disease 2019 (COVID-19) pandemic has altered approaches to anesthesiology education by shifting educational paradigms. This vision article discusses pre-COVID-19 educational methodologies and best evidence, adaptations required under COVID-19, and evidence for these modifications, and suggests future directions for anesthesiology education. Learning management systems provide structure to online learning. They have been increasingly utilized to improve access to didactic materials asynchronously. Despite some historic reservations, the pandemic has necessitated a rapid uptake across programs. Commercially available systems offer a wide range of peer-reviewed curricular options. The flipped classroom promotes learning foundational knowledge before teaching sessions with a focus on application during structured didactics. There is growing evidence that this approach is preferred by learners and may increase knowledge gain. The flipped classroom works well with learning management systems to disseminate focused preclass work. Care must be taken to keep virtual sessions interactive. Simulation, already used in anesthesiology, has been critical in preparation for the care of COVID-19 patients. Multidisciplinary, in situ simulations allow for rapid dissemination of new team workflows. Physical distancing and reduced availability of providers have required more sessions. Early pandemic decreases in operating volumes have allowed for this; future planning will have to incorporate smaller groups, sanitizing of equipment, and attention to use of personal protective equipment. Effective technical skills training requires instruction to mastery levels, use of deliberate practice, and high-quality feedback. Reduced sizes of skill-training workshops and approaches for feedback that are not in-person will be required. Mock oral and objective structured clinical examination (OSCE) allow for training and assessment of competencies often not addressed otherwise. They provide formative and summative data and objective measurements of Accreditation Council for Graduate Medical Education (ACGME) milestones. They also allow for preparation for the American Board of Anesthesiology (ABA) APPLIED examination. Adaptations to teleconferencing or videoconferencing can allow for continued use. Benefits of teaching in this new era include enhanced availability of asynchronous learning and opportunities to apply universal, expert-driven curricula. Burdens include decreased social interactions and potential need for an increased amount of smaller, live sessions. Acquiring learning management systems and holding more frequent simulation and skills sessions with fewer learners may increase cost. With the increasing dependency on multimedia and technology support for teaching and learning, one important focus of educational research is on the development and evaluation of strategies that reduce extraneous processing and manage essential and generative processing in virtual learning environments. Collaboration to identify and implement best practices has the potential to improve education for all learners.

Formation of an Intraoperative Educational Curriculum for Anesthesiology Residents Using a Systematic Approach.

Anesthesiology residents spend most of their training in operating rooms, but intraoperative teaching is often unstructured. Needs assessment indicated a need to incorporate a more evidence-based approach to education and improvement of our methods of introducing residents to primary anesthesiology literature. Kern's 6-step approach to curriculum development was used to create a robust and innovative curriculum to increase both the evidence-based component of our curriculum and the amount of educational intraoperative discussion among trainees and faculty. Our curriculum uses a structured topic outline, an e-journal club, and other relevant resources to facilitate discussion of the topics.

Case Study: Fatal Exertional Rhabdomyolysis Possibly Related to Drastic Weight Cutting.

Rapid weight loss or "weight cutting" is a dangerous practice that is ubiquitous in modern combat sports yet underrepresented in the medical literature. We present a case of exertional rhabdomyolysis in a mixed martial artist with sickle cell trait to illustrate the hazards of weight cutting and ensuing critical illness. Sickle cell trait is known to predispose patients to exertional rhabdomyolysis, and multiple fatal cases have been reported in the setting of strenuous exercise. Dehydration and consequent electrolyte abnormalities make combat sport athletes with sickle cell trait particularly vulnerable to this entity. This case suggests a potential role for sickle cell trait screening in this population and underscores the need for safer weight-control practices and monitoring among all combat sport athletes.

Anesthesia for Patients with Peripheral Vascular Disease and Cardiac Dysfunction.

Patients with vascular disease and cardiac dysfunction present particular challenges to the anesthesiologist. They are hemodynamically brittle, at high risk of morbidity and mortality during surgery, and often carry additional comorbidities that increase their complexity and risk. Those with peripheral vascular disease should be assumed to have coronary artery disease and tend to have other systemic vascular problems. Poor cardiac function further worsens perfusion in an already compromised peripheral vascular system. Care of these patients requires judicious monitoring, an anesthetic that optimizes hemodynamic function, and avoidance of particularly likely complications such as perioperative myocardial ischemia, stroke, and bleeding.