Implementing Remote Collaboration in a Virtual Patient Platform: Usability Study.

BACKGROUND: Learning with virtual patients is highly popular for fostering clinical reasoning in medical education. However, little learning with virtual patients is done collaboratively, despite the potential learning benefits of collaborative versus individual learning. OBJECTIVE: This paper describes the implementation of student collaboration in a virtual patient platform. Our aim was to allow pairs of students to communicate remotely with each other during virtual patient learning sessions. We hypothesized that we could provide a collaborative tool that did not impair the usability of the system compared to individual learning and that this would lead to better diagnostic accuracy for the pairs of students. METHODS: Implementing the collaboration tool had five steps: (1) searching for a suitable software library, (2) implementing the application programming interface, (3) performing technical adaptations to ensure high-quality connections for the users, (4) designing and developing the user interface, and (5) testing the usability of the tool in 270 virtual patient sessions. We compared dyad to individual diagnostic accuracy and usability with the 10-item System Usability Scale. RESULTS: We recruited 137 students who worked on 6 virtual patients. Out of 270 virtual patient sessions per group (45 dyads times 6 virtual patients, and 47 students working individually times 6 virtual patients minus 2 randomly selected deleted sessions) the students made successful diagnoses in 143/270 sessions (53%, SD 26%) when working alone and 192/270 sessions (71%, SD 20%) when collaborating (P=.04, η2=0.12). A usability questionnaire given to the students who used the collaboration tool showed a usability score of 82.16 (SD 1.31), representing a B+ grade. CONCLUSIONS: The collaboration tool provides a generic approach for collaboration that can be used with most virtual patient systems. The collaboration tool helped students diagnose virtual patients and had good overall usability. More broadly, the collaboration tool will provide an array of new possibilities for researchers and medical educators alike to design courses for collaborative learning with virtual patients.

Planning a Collection of Virtual Patients to Train Clinical Reasoning: A Blueprint Representative of the European Population.

BACKGROUND: Virtual patients (VPs) are a suitable method for students to train their clinical reasoning abilities. We describe a process of developing a blueprint for a diverse and realistic VP collection (prior to VP creation) that facilitates deliberate practice of clinical reasoning and meets educational requirements of medical schools. METHODS: An international and interdisciplinary partnership of five European countries developed a blueprint for a collection of 200 VPs in four steps: (1) Defining the criteria (e.g., key symptoms, age, sex) and categorizing them into disease-, patient-, encounter- and learner-related, (2) Identifying data sources for assessing the representativeness of the collection, (3) Populating the blueprint, and (4) Refining and reaching consensus. RESULTS: The blueprint is publicly available and covers 29 key symptoms and 176 final diagnoses including the most prevalent medical conditions in Europe. Moreover, our analyses showed that the blueprint appears to be representative of the European population. CONCLUSIONS: The development of the blueprint required a stepwise approach, which can be replicated for the creation of other VP or case collections. We consider the blueprint an appropriate starting point for the actual creation of the VPs, but constant updating and refining is needed.

Adaptation of an international virtual patient collection to the COVID-19 pandemic.

The COVID-19 pandemic posed new global challenges for teaching. We met these challenges as an international collaboration by adapting a collection of virtual patients for clinical reasoning training to this novel context.