There is an ongoing shift in the medical education community from a time-based model of medical education to a competency-based model. In the competency-based model, trainees’ performance must be continually monitored. But due to constraints on expert scheduling, this is infeasible for expert preceptors. Moreover, despite the advent of structured assessment rubrics, expert assessment remains subjective. This motivates the development of automated assessment methods. This can be complemented by methods for automatic feedback and instruction, which can be used to improve the training process and acceleration learning curves without the presence of an expert preceptor. Ultrasound-guided interventions are particularly challenging for trainees to learn. They require simultaneous manipulation of the ultrasound in coordination with another tool. All while the operator must interpret a noisy 2D ultrasound image and mentally reconstruct it back into 3D. This means that ultrasound-guided interventions are of interest for competency-based medical education, and thus, automated assessment and feedback methods. In consultation with clinical experts, it is imperative that assessment and feedback methods must be clinically driven, not empirically driven. That is, the methods should incorporate domain knowledge based on clinical expertise and use that as a basis for the assessment and feedback. The assessment and feedback methods should be both transparent and configurable. This allows trainees to understand their assessment, interpret the assessment into actionable feedback, and it allows the expert preceptors to adjust the assessment to their particular setup or to emphasize particular skills.
Holden, Matthew, "Competence Assessment and Automated Feedback for Ultrasound-Guided Intervention Training" (2018). Link Foundation Modeling, Simulation and Training Fellowship Reports. 26.