Computer model for the cardiovascular system: development of an e-learning tool for teaching of medical students.
David Roy Warriner, Martin Bayley, Yubing Shi, Patricia Victoria Lawford, Andrew Narracott, John Fenner
Author Information
David Roy Warriner: Mathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK. d.r.warriner@sheffield.ac.uk.
Martin Bayley: Department of Scientific Computing, Royal Hallamshire Hospital, Sheffield Teaching Hospitals, Glossop Road, Sheffield, S10 2JF, UK.
Yubing Shi: Mathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.
Patricia Victoria Lawford: Mathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.
Andrew Narracott: Mathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.
John Fenner: Mathematical Modelling in Medicine Group, Department of Infection Immunity and Cardiovascular Disease, University of Sheffield, The Medical School, Room OU140, O Floor, Beech Hill Road, Sheffield, S10 2RX, UK.
BACKGROUND: This study combined themes in cardiovascular modelling, clinical cardiology and e-learning to create an on-line environment that would assist undergraduate medical students in understanding key physiological and pathophysiological processes in the cardiovascular system. METHODS: An interactive on-line environment was developed incorporating a lumped-parameter mathematical model of the human cardiovascular system. The model outputs were used to characterise the progression of key disease processes and allowed students to classify disease severity with the aim of improving their understanding of abnormal physiology in a clinical context. Access to the on-line environment was offered to students at all stages of undergraduate training as an adjunct to routine lectures and tutorials in cardiac pathophysiology. Student feedback was collected on this novel on-line material in the course of routine audits of teaching delivery. RESULTS: Medical students, irrespective of their stage of undergraduate training, reported that they found the models and the environment interesting and a positive experience. After exposure to the environment, there was a statistically significant improvement in student performance on a series of 6 questions based on cardiovascular medicine, with a 33% and 22% increase in the number of questions answered correctly, p < 0.0001 and p < 0.001 respectively. CONCLUSIONS: Considerable improvement was found in students' knowledge and understanding during assessment after exposure to the e-learning environment. Opportunities exist for development of similar environments in other fields of medicine, refinement of the existing environment and further engagement with student cohorts. This work combines some exciting and developing fields in medical education, but routine adoption of these types of tool will be possible only with the engagement of all stake-holders, from educationalists, clinicians, modellers to, most importantly, medical students.
