Not The Ghost in The Machine: Transforming Patient Data into E-Learning Cases Within A Case-Based Blended Learning Framework For Medical Education

摘要

Emergent challenges in medical education support an implementation of trans-disciplinary case-based learning. We propose a case-based blended learning framework, synergistically combining textbook, e-learning cases and a simulated patient course in medical education. A novel server system architecture allows patient data to be automatically transferred from the Vienna General Hospital to the Medical University of Vienna, and then imported into an e-learning template, in which online MCQ questions can be generated. We present one example of a transferred, imported and completed anxiety disorder e-learning case, currently implemented in the pre-clinical psychiatry course. This framework facilitates the creation of up to date teaching content, while addressing difficulties in transforming declarative knowledge into procedural-knowledge and -skill, (background knowledge into clinical reasoning) especially in domains which profit from a structured learning approach in creating a close link in understanding between functional morphology and clinical presentation.