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Cohort analysis of simulation-based medical training for decision support
conference contributionposted on 2017-11-27, 00:00 authored by James ZhangJames Zhang, Samer HanounSamer Hanoun, Burhan KhanBurhan Khan, Douglas CreightonDouglas Creighton, Saeid Nahavandi, Kellie BrittKellie Britt, Karen D'SouzaKaren D'Souza, Jon Watson, R Yanieri
© 2017 IEEE. Debriefing is the practice of after session review of training performance to enhance self-reflection through feedback. It has been considered as a vital and crucial part of simulation-based medical training. However an accurate, objective and in-depth evaluation of trainee performance has been a significant challenge. To address this we developed a knowledge-based framework in which the criteria of performance for clinical training are distilled into expert rules. These rules are then matched to data streams from a training session to evaluate the strengths and weaknesses of a trainee. We applied the evaluation technology to a dataset collected from two medical cohorts. The cohort characteristics are calculated, visualised, and validated by the medical experts. The cohort analysis results inform decision making at the levels of both the trainers and the enterprise. Trainers can compare and characterise the performance of different student cohorts or the same cohort over a period of time. The course coordinators can use the cohort analysis result to adjust the course design to target the identified common problems in trainee cohorts.