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The term virtual patient is used to describe interactive computer simulations used in health care education.[1] The special focus is targeted on the simulation of clinical processes with virtual patients. Virtual patients combine scientific excellence, modern technologies and the innovative concept of game-based learning. Virtual patients allow the learner to take the role of a health care professional and develop clinical skills such as making diagnoses and therapeutic decisions[2] The use of virtual patient programmes is increasing in healthcare education, partly in response to increasing demands on health care professionals and education of students but also because they allow opportunity for students to practice in a safe environment[2] There are many different formats a virtual patient may take. However the overarching principle is that of interactivity - a virtual patient will have mechanisms for the learner to interact with the case and material or information is made available to the learner as they complete a range of learning activities[3] The interactivity is non-sequential.

Forms of Virtual Patients[edit | edit source]

Virtual patients may take a number of different forms:

  • Artificial patients: computer simulations of biochemical processes such as the effect of drugs in organisms, the physiologic processes of a given organ or entire systems (systems biology) in a given organism. These can be used in different phases of a compound or drug in development in a given pharmacological research as a preliminary to testing on animals and humans for the drug development processes.
  • Real patients: reflected in data e.g. electronic health records (EHRs). In this case the virtual patient is the reflection of the real patient in terms of data held about them. These are sometimes called e-patients.
  • Physical simulators: mannequins (sometimes spelled 'manikins'), models or related artefacts.

Types of Interaction with Simulated or Electronic Patients[edit | edit source]

A number of different modes of virtual patient delivery have been defined:

  • Predetermined scenario [directed mode]
  • The learner may build up the patient or case data from observations and interactions [blank mode]
  • The learner may view and appraise or review an existing patient or scenario [critique mode or rehearsal mode]
  • The VP may be used as a mechanism to address particular topics [context mode]
  • The learner may use a scenario or patient to explore personal/professional dimensions [reflective mode]
  • Banks of patients or scenarios may collectively address broad issues of healthcare [pattern mode]

Types of Interaction with Artificial Patients[edit | edit source]

  • To create and run a mathematical quantitative simulation of a healthy person (physiology) and diseased person to test multiple hypothesis against known and unknown processes in a given set or sets of processes to help fill gaps in knowledge of the physiology or system under investigation.

Possible Benefits of Physical Simulators and Simulated Patients[edit | edit source]

Simulated patients increase the availability of training opportunities for medical students, making them less dependent on actual cases to learn how to handle different situations. Unlike real patients, simulated patients can be accessed on demand and they can be endlessly replayable to allow the user to explore different options and strategies. They can be structured with narratives that represent real situations while challenging the user with a wide range of tasks.

Despite their efficacy simulated patients are still a tangent and a prosthesis to reality. They should be viewed as augmenting existing modes and methods of clinical teaching.

Possible Benefits of Artificial Patients[edit | edit source]

Artificial patients increase the possibility of exploring millions of hypothesis driven experiments on known areas of biological systems to extrapolate the unknown, which enables efficient exploration, informed research and development predictive simulation, which must also be proven by real patient studies clinical trial. If more tests can be done on Artificial patients to filter out possibly unnecessary tests or experiments, fewer subjects pharmacovigilance maybe needed. The Artificial patients insilico modeling are still in the early to middle developmental stages. It will require continual updates and development with the endless availability of new data.

Virtual Patient Data Standards[edit | edit source]

The MedBiquitous consortium established a working group in 2005 to create a free and open data standard for expressing and exchanging virtual patients between different authoring and delivery systems. This was in part to address the problem of exchanging and reusing virtual patients and in part to encourage and support easier and wider use of virtual patients in general.

This standard has been very successful and is now widely adopted, eg in major projects like eViP.

In 2010, this standard attained status as an ANSI standard. American_National_Standards_Institute

Examples[edit | edit source]

Electronic Cases


Virtual physiology

See also[edit | edit source]

External links[edit | edit source]

Notes and references[edit | edit source]

  1. JiSC (2009) Repurposing existing virtual patients. Available accessed 08.06.09
  2. 2.0 2.1 Imison M, Hughes C(2008) The virtual patient project: using low fidelity, student generated online case studies in medical education. in Hello? Where are you in the landscape of educational technology? Proceedings ascilite Melbourne 2008.
  3. Ellaway R (2009) Modelliing virtual patients and virtual cases. Available

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