Your Next-Generation Virtual Human Patients Will See You Now

Couger Team
Couger
Published in
4 min readSep 6, 2020

Virtual patients already help doctors, nurses, and other healthcare professionals train their skills in a safe environment with proven positive results. The next step is adding more realism to the training scenarios through the introduction of new technology, such as Ludens’ Virtual Human Agents (VHA).

Photo by National Cancer Institute on Unsplash

Study after study from across the globe is reaching the same conclusion: using virtual humans to train healthcare professionals has a long list of proven benefits.

However, the approach also has its challenges, for example, regarding limited scenarios, repeatability, and realistic interactions.

All three are areas where Luden’s Virtual Human Agent (VHA) technology can provide important updates.

The Virtual Human Patient History

The use of virtual patients in healthcare is not a new phenomenon. It initially involved role-playing scenarios where healthcare professionals could train a variety of skills, including soft skills and diagnosis, in hypothetical situations. Virtual patients were usually a set of personality traits written down on paper pieces used by a teacher or a fellow student to act out a patient-healthcare professional scenario. Alternatively, the virtual patient would function like a choose-your-own-adventure book, where a choice between several options leads to a new set of options, followed by a new set of possibilities, and so on.

Since then, virtual human patients have steadily progressed in sophistication. Today, many training programs involve the use of low-fidelity virtual patients through interactive computer-based clinical scenarios. However, they remain somewhat limited in their ability to provide realistic training scenarios. Something we will return to later in this article.

Photo by Olga Guryanova on Unsplash

Proven Efficiency and Safety

Many international studies have examined whether virtual human patients work and can help healthcare professionals train and improve their skillsets.

Almost all find that this is the case.

For example, a study by researchers from North and South America looked at 51 trials using virtual human patients to train skills such as conducting interviews, perform physical exams, clinical judgment, gauge the relevance of medical exams, and present cases. The findings showed that healthcare students viewed the approach as an easy-to-use, motivating, and stress-free learning tool.

Another review, performed by a group of researchers based across Europe and Asia, found that virtual human patients allowed for better follow-up of the students’ learning process. The review also concluded that virtual patients could effectively improve both skills and knowledge among healthcare professionals.

Taking the Next Step With VHAs

While the research results show how virtual patients can help increase learning and retaining knowledge, the positive effects reported were between low and moderate. In other words, virtual patients help make learning more efficient, but their impact may be increased.

Part of the reason is likely that most current virtual patients are low-fidelity versions of their human counterparts. Said differently, they are quite different from human patients, and therefore there is a limit to how realistic training scenarios involving them can be.

Virtual Human Agents (VHAs) created by Ludens can help to improve the efficiency of training. Thanks to the use of advanced game AI, virtual humanoid form, and emotional and gesture recognition systems, VHAs can increase the realism of teaching and training in a variety of ways.

For example, improving on the following aspects of learning:

  • Engagement: Through providing more human-like interactions, VHAs can increase student engagement. This is particularly the case for patient-professional scenarios where the student is training decision-making during conversations.
  • Retention: Thanks to the ability to revisit realistic scenarios and interact with a dynamic, AI-powered VHA, students can increase their retention of knowledge. Furthermore, VHAs present an opportunity for splitting learning experiences into segments that can be flexibly planned and integrated into the students’ existing schedules.
  • Active Learning: Most of us will subscribe to the fact that active learning through exercises and realistic case studies is more effective than through static learning scenarios, such as teacher presentations or simple textbook studies. Again, VHAs can help make learning experiences more active and interactive.
  • Flexibility: This extends to both modification of content and the time/shape or delivery. Thanks to Luden’s VHA marketplace, developers of all types of VHA-related content and technology have a place to offer modified and optimized content and systems. The timing of delivery of training can be adjusted to fit the individual student.
Photo by Aron Visuals on Unsplash

Tips for Integrating VHA Technology

For both healthcare scenarios and many other areas where VHA technology can be used to increase the efficiency and flexibility of learning, the following tips may help optimize training experiences:

  • Consider your learners’ level: Educational background and experience levels of your target group may impact the optimization of learning experiences.
  • Integrate teamwork and collaboration: Most job tasks in modern organizations involve some form of cooperation. Realistic training scenarios should aim to mirror this reality.
  • Incorporate feedback and repetition: The use of VHAs for training should be accompanied by some kind of feedback from instructors. Reflective practice should be encouraged.
  • Encourage experimentation: One of the core strengths of VHA technology is that it provides users with a safe space in which to try out different approaches. Learners should be encouraged to try out varying approaches during role-playing sessions.

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Couger Team
Couger
Editor for

We develop next generation interface “Virtual Human Agent” and XAI(Explainable AI).