Development and Pilot Testing of a Programmatic System for Competency Assessment in US Anesthesiology Residency Training.

BACKGROUND: In 2018, a set of entrustable professional activities (EPAs) and procedural skills assessments were developed for anesthesiology training, but they did not assess all the Accreditation Council for Graduate Medical Education (ACGME) milestones. The aims of this study were to (1) remap the 2018 EPA and procedural skills assessments to the revised ACGME Anesthesiology Milestones 2.0, (2) develop new assessments that combined with the original assessments to create a system of assessment that addresses all level 1 to 4 milestones, and (3) provide evidence for the validity of the assessments. METHODS: Using a modified Delphi process, a panel of anesthesiology education experts remapped the original assessments developed in 2018 to the Anesthesiology Milestones 2.0 and developed new assessments to create a system that assessed all level 1 through 4 milestones. Following a 24-month pilot at 7 institutions, the number of EPA and procedural skill assessments and mean scores were computed at the end of the academic year. Milestone achievement and subcompetency data for assessments from a single institution were compared to scores assigned by the institution's clinical competency committee (CCC). RESULTS: New assessment development, 2 months of testing and feedback, and revisions resulted in 5 new EPAs, 11 nontechnical skills assessments (NTSAs), and 6 objective structured clinical examinations (OSCEs). Combined with the original 20 EPAs and procedural skills assessments, the new system of assessment addresses 99% of level 1 to 4 Anesthesiology Milestones 2.0. During the 24-month pilot, aggregate mean EPA and procedural skill scores significantly increased with year in training. System subcompetency scores correlated significantly with 15 of 23 (65.2%) corresponding CCC scores at a single institution, but 8 correlations (36.4%) were <30.0, illustrating poor correlation. CONCLUSIONS: A panel of experts developed a set of EPAs, procedural skill assessment, NTSAs, and OSCEs to form a programmatic system of assessment for anesthesiology residency training in the United States. The method used to develop and pilot test the assessments, the progression of assessment scores with time in training, and the correlation of assessment scores with CCC scoring of milestone achievement provide evidence for the validity of the assessments.

Development of entrustable professional activities for regional anesthesia and pain medicine fellowship training.

INTRODUCTION: The Accreditation Council for Graduate Medical Education (ACGME) offers descriptions of competencies and milestones but does not provide standardized assessments to track trainee competency. Entrustable professional activities (EPAs) and special assessments (SAs) are emerging methods to assess the level of competency obtained by regional anesthesiology and acute pain medicine (RAAPM) fellows. METHODS: A panel of RAAPM physicians with experience in education and competency assessment and one medical student were recruited to participate in a modified Delphi method with iterative rounds to reach consensus on: a list of EPAs, SAs, and procedural skills; detailed definitions for each EPA and SA; a mapping of the EPAs and SAs to the ACGME milestones; and a target level of entrustment for graduating US RAAPM fellows for each EPA and procedural skill. A gap analysis was performed and a heat map was created to cross-check the EPAs and SAs to the ACGME milestones. RESULTS: Participants in EPA and SA development included 19 physicians and 1 medical student from 18 different programs. The Delphi rounds yielded a final list of 23 EPAs, a defined entrustment scale, mapping of the EPAs to ACGME milestones, and graduation targets. A list of 73 procedural skills and 7 SAs were similarly developed. DISCUSSION: A list of 23 RAAPM EPAs, 73 procedural skills, and 7 SAs were created using a rigorous methodology to reach consensus. This framework can be utilized to help assess RAAPM fellows in the USA for competency and allow for meaningful performance feedback.

Validating GAN-BioBERT: A Methodology for Assessing Reporting Trends in Clinical Trials.

Background: The aim of this study was to validate a three-class sentiment classification model for clinical trial abstracts combining adversarial learning and the BioBERT language processing model as a tool to assess trends in biomedical literature in a clearly reproducible manner. We then assessed the model's performance for this application and compared it to previous models used for this task. Methods: Using 108 expert-annotated clinical trial abstracts and 2,000 unlabeled abstracts this study develops a three-class sentiment classification algorithm for clinical trial abstracts. The model uses a semi-supervised model based on the Bidirectional Encoder Representation from Transformers (BERT) model, a much more advanced and accurate method compared to previously used models based upon traditional machine learning methods. The prediction performance was compared to those previous studies. Results: The algorithm was found to have a classification accuracy of 91.3%, with a macro F1-Score of 0.92, significantly outperforming previous studies used to classify sentiment in clinical trial literature, while also making the sentiment classification finer grained with greater reproducibility. Conclusion: We demonstrate an easily applied sentiment classification model for clinical trial abstracts that significantly outperforms previous models with greater reproducibility and applicability to large-scale study of reporting trends.

Development and Pilot Testing of Entrustable Professional Activities for US Anesthesiology Residency Training.

BACKGROUND: Modern medical education requires frequent competency assessment. The Accreditation Council for Graduate Medical Education (ACGME) provides a descriptive framework of competencies and milestones but does not provide standardized instruments to assess and track trainee competency over time. Entrustable professional activities (EPAs) represent a workplace-based method to assess the achievement of competency milestones at the point-of-care that can be applied to anesthesiology training in the United States. METHODS: Experts in education and competency assessment were recruited to participate in a 6-step process using a modified Delphi method with iterative rounds to reach consensus on an entrustment scale, a list of EPAs and procedural skills, detailed definitions for each EPA, a mapping of the EPAs to the ACGME milestones, and a target level of entrustment for graduating US anesthesiology residents for each EPA and procedural skill. The defined EPAs and procedural skills were implemented using a website and mobile app. The assessment system was piloted at 7 anesthesiology residency programs. After 2 months, faculty were surveyed on their attitudes on usability and utility of the assessment system. The number of evaluations submitted per month was collected for 1 year. RESULTS: Participants in EPA development included 18 education experts from 11 different programs. The Delphi rounds produced a final list of 20 EPAs, each differentiated as simple or complex, a defined entrustment scale, mapping of the EPAs to milestones, and graduation entrustment targets. A list of 159 procedural skills was similarly developed. Results of the faculty survey demonstrated favorable ratings on all questions regarding app usability as well as the utility of the app and EPA assessments. Over the 2-month pilot period, 1636 EPA and 1427 procedure assessments were submitted. All programs continued to use the app for the remainder of the academic year resulting in 12,641 submitted assessments. CONCLUSIONS: A list of 20 anesthesiology EPAs and 159 procedural skills assessments were developed using a rigorous methodology to reach consensus among education experts. The assessments were pilot tested at 7 US anesthesiology residency programs demonstrating the feasibility of implementation using a mobile app and the ability to collect assessment data. Adoption at the pilot sites was variable; however, the use of the system was not mandatory for faculty or trainees at any site.

Educating Perioperative Nurses About Local Anesthetic Systemic Toxicity Using High-Fidelity Simulation.

BACKGROUND: The rarity of perianesthetic catastrophic events creates a challenge in training support staff in the treatment of emergencies such as local anesthetic systemic toxicity (LAST). Simulation learning offers a unique venue in which to safely encounter rare events. AIMS: This study aimed to evaluate knowledge retention regarding LAST in perianesthetic nursing staff using high-fidelity simulation and a short didactic session. DESIGN: Nurses were recruited from perioperative locations to participate in a simulated scenario of LAST and engage in a short didactic session. SETTINGS: Simulation and education occurred in the high-fidelity simulation center at the University of Wisconsin Hospital. PARTICIPANTS/SUBJECTS: Thirteen nurses from the preoperative, post-anesthesia, and block nursing teams participated in the study. METHODS: Participants completed a pre-test before participating in the simulation, followed by a formal debrief and short lecture. They then completed post-tests and a short survey focused on self-efficacy and review of the simulation experience. RESULTS: Test scores, compared to the pre-test, improved significantly on the immediately-post, 1-month, and 3-month assessments. Participants felt more equipped to handle crisis scenarios. CONCLUSIONS: Experiential learning often results in significant knowledge acquisition and retention. Participants in this study improved their test scores regarding LAST and increased their sense of self-efficacy and ability to handle crisis scenarios after taking part in a high-fidelity simulation.