A virtual patient (VP) is “an interactive computer simulation of real-life clinical scenarios for the purpose of medical training, education, or assessment”.
There are various degrees of complexity in the types of VP scenarios. In their basic form, a VP allows the user to think about options and decisions they need to make based on some clinical information. The user is then presented with either feedback or more clinical information depending on the type of VP the user is playing. VPs are also known as virtual scenarios (VS), as decision-making scenarios can be used in other disciplines outside medicine and healthcare.
The range of VPs can be varied, starting from simple linear scenarios, which allows the learner to move from one page to another, with added interactivity of assessment questions to test the learners’ knowledge. More complex VPs are referred to as ‘branched’ or ‘decision’ VPs that offer choices to the learner at different stages in the scenario. Branched VPs offer the learners a chance to explore the different options available to them and follow consequences of their choices. Branched VPs can be used for self-directed learning, assessment or problem-based learning scenarios.
VPs in problem-based learning
Here is an example of a branched problem-based learning (PBL) case called Edward Payne. The scenario is split into three tutorials and runs over a week. The topics covered in this case are tuberculosis, fever, weight loss, infection, inflammation, and hypersensitivity.
VPs have been used in a number of international projects to transform the curriculum by imbedding VP in PBL sessions. Some of these projects are TAME, CROESUS , ePBLnet, Generation 4, eViP and PREVIEW.
Through the WAVES project you will find the information you need to author and implement your own VPs for your teaching or training. The project provides both technical and non-technical guidelines, including a MOOC.
 Ellaway, R., Candler, C., Greene, P. and Smothers, V., 2006. An Architectural Model for MedBiquitous Virtual Patients. Baltimore, MD: MedBiquitous.