Competency-Based Time-Variable Anesthesiology Residency Training: Identification of Problems and Solutions.

BACKGROUND: Global medical education is gradually moving toward more comprehensive implementations of a competency-based education (CBE) model. Elimination of standard time-based training and adoption of time-variable training (competency-based time-variable training [CB-TVT]) is one of the final stages of implementation of CBE. While CB-TVT has been implemented in some programs outside the United States, residency programs in the United States are still exploring this approach to training. The Accreditation Council for Graduate Medical Education (ACGME) and the American Board of Medical Specialties (ABMS) are encouraging member boards and residency review committees to consider innovative ways programs could implement CB-TVT. The goals of this study were to (1) identify potential problems with the implementation of CB-TVT in anesthesiology residency training, (2) rank the importance of the problems and the perceived difficulty of solving them, and (3) develop proposed solutions to the identified problems. METHODS: Study participants were recruited from key stakeholder groups in anesthesiology education, including current or former program directors, department chairs, residents, fellows, American Board of Anesthesiology (ABA) board members, ACGME residency review committee members or ACGME leaders, designated institutional officials, residency program coordinators, clinical operations directors, and leaders of large anesthesiology community practice groups. This study was conducted in 2 phases. In phase 1, survey questionnaires were iteratively distributed to participants to identify problems with the implementation of CB-TVT. Participants were also asked to rank the perceived importance and difficulty of each problem and to identify relevant stakeholder groups that would be responsible for solving each problem. In phase 2, surveys focused on identifying potential solutions for problems identified in phase 1. RESULTS: A total of 36 stakeholders identified 39 potential problems, grouped into 7 major categories, with the implementation of CB-TVT in anesthesiology residency training. Of the 39 problems, 19 (48.7%) were marked as important or very important on a 5-point scale and 12 of 19 (63.2%) of the important problems were marked as difficult or very difficult to solve on a 5-point scale. Stakeholders proposed 165 total solutions to the identified problems. CONCLUSIONS: CB-TVT is a promising educational model for anesthesiology residency, which potentially results in learner flexibility, individualization of curricula, and utilization of competencies to determine learner advancement. Because of the potential problems with the implementation of CB-TVT, it is important for future pilot implementations of CB-TVT to document realized problems, efficacy of solutions, and effects on educational outcomes to justify the burden of implementing CB-TVT.

Transitioning to Virtual Meetings: Experiences From the Society for Education in Anesthesia Virtual Fall 2020 Meeting.

The COVID-19 pandemic has forced organizers of traditional in-person continuing medical education conferences to transition to a virtual format. There are both advantages and disadvantages to this change in format. When planning a virtual meeting, several factors require consideration, including costs, virtual platforms, sponsorship, networking, and meeting logistics. This manuscript describes the authors' experiences of transforming the Society of Education in Anesthesia 2020 Fall Meeting into a virtual conference and explores the lessons learned and future impacts of this new medium.

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.

Enhancing Feedback on Professionalism and Communication Skills in Anesthesia Residency Programs.

BACKGROUND: Despite its importance, training faculty to provide feedback to residents remains challenging. We hypothesized that, overall, at 4 institutions, a faculty development program on providing feedback on professionalism and communication skills would lead to (1) an improvement in the quantity, quality, and utility of feedback and (2) an increase in feedback containing negative/constructive feedback and pertaining to professionalism/communication. As secondary analyses, we explored these outcomes at the individual institutions. METHODS: In this prospective cohort study (October 2013 to July 2014), we implemented a video-based educational program on feedback at 4 institutions. Feedback records from 3 months before to 3 months after the intervention were rated for quality (0-5), utility (0-5), and whether they had negative/constructive feedback and/or were related to professionalism/communication. Feedback records during the preintervention, intervention, and postintervention periods were compared using the Kruskal-Wallis and χ tests. Data are reported as median (interquartile range) or proportion/percentage. RESULTS: A total of 1926 feedback records were rated. The institutions overall did not have a significant difference in feedback quantity (preintervention: 855/3046 [28.1%]; postintervention: 896/3327 [26.9%]; odds ratio: 1.06; 95% confidence interval, 0.95-1.18; P = .31), feedback quality (preintervention: 2 [1-4]; intervention: 2 [1-4]; postintervention: 2 [1-4]; P = .90), feedback utility (preintervention: 1 [1-3]; intervention: 2 [1-3]; postintervention: 1 [1-2]; P = .61), or percentage of feedback records containing negative/constructive feedback (preintervention: 27%; intervention: 32%; postintervention: 25%; P = .12) or related to professionalism/communication (preintervention: 23%; intervention: 33%; postintervention: 24%; P = .03). Institution 1 had a significant difference in feedback quality (preintervention: 2 [1-3]; intervention: 3 [2-4]; postintervention: 3 [2-4]; P = .001) and utility (preintervention: 1 [1-3]; intervention: 2 [1-3]; postintervention: 2 [1-4]; P = .008). Institution 3 had a significant difference in the percentage of feedback records containing negative/constructive feedback (preintervention: 16%; intervention: 28%; postintervention: 17%; P = .02). Institution 2 had a significant difference in the percentage of feedback records related to professionalism/communication (preintervention: 26%; intervention: 57%; postintervention: 31%; P < .001). CONCLUSIONS: We detected no overall changes but did detect different changes at each institution despite the identical intervention. The intervention may be more effective with new faculty and/or smaller discussion sessions. Future steps include refining the rating system, exploring ways to sustain changes, and investigating other factors contributing to feedback quality and utility.

Perioperative outcomes among patients with the modified metabolic syndrome who are undergoing noncardiac surgery.

BACKGROUND: Previous studies have demonstrated that obesity is paradoxically associated with a lower risk of mortality after noncardiac surgery. This study will determine the impact of the modified metabolic syndrome (defined as the presence of obesity, hypertension, and diabetes) on perioperative outcomes. METHODS: This study is based on data from 310,208 patients in the American College of Surgeons National Surgical Quality Improvement Program database. We estimated separate multivariate logistic regression models for 30-day mortality and for 30-day complications. RESULTS: Patients with the modified metabolic syndrome who are super obese had a 2-fold increased risk of death (adjusted odds ratio [AOR] 1.99; 95% CI 1.41-2.80). As stratified by body mass index, patients with the modified metabolic syndrome had a 2- to 2.5-fold higher risk of cardiac adverse events (CAE) compared with normal-weight patients: obese (AOR 1.70; 95% CI 1.40-2.07), morbidly obese (AOR 2.01; 95% CI 1.48-2.73), and super obese (AOR 2.66; 95% CI 1.68-4.19). In addition, the risk of acute kidney injury (AKI) was 3- to 7-fold higher in these patients: obese (AOR 3.30; 95% CI 2.75-3.94), morbidly obese (AOR 5.01; 95% CI 3.87-6.49), and super obese (AOR 7.29; 95% CI 5.27-10.1). CONCLUSION: Patients with the modified metabolic syndrome undergoing noncardiac surgery are at substantially higher risk of complications compared with patients of normal weight.