AI Article Synopsis

  • Virtual patients are interactive simulations used for clinical decision-making in health care education, but challenges exist in their retrieval and repurposing across platforms due to a lack of standardization.
  • The mEducator Best Practice Network has developed frameworks to improve the sharing and reuse of medical education resources, leading to enhancements in the OpenLabyrinth platform for virtual patient management.
  • An extension for OpenLabyrinth was created to semantically annotate virtual patients, allowing for effective searches and exchanges of educational content among institutions; evaluations showed positive results in creating and sharing repurposed virtual patient cases.

Article Abstract

Background: Virtual patients are interactive computer simulations that are increasingly used as learning activities in modern health care education, especially in teaching clinical decision making. A key challenge is how to retrieve and repurpose virtual patients as unique types of educational resources between different platforms because of the lack of standardized content-retrieving and repurposing mechanisms. Semantic Web technologies provide the capability, through structured information, for easy retrieval, reuse, repurposing, and exchange of virtual patients between different systems.

Objective: An attempt to address this challenge has been made through the mEducator Best Practice Network, which provisioned frameworks for the discovery, retrieval, sharing, and reuse of medical educational resources. We have extended the OpenLabyrinth virtual patient authoring and deployment platform to facilitate the repurposing and retrieval of existing virtual patient material.

Methods: A standalone Web distribution and Web interface, which contains an extension for the OpenLabyrinth virtual patient authoring system, was implemented. This extension was designed to semantically annotate virtual patients to facilitate intelligent searches, complex queries, and easy exchange between institutions. The OpenLabyrinth extension enables OpenLabyrinth authors to integrate and share virtual patient case metadata within the mEducator3.0 network. Evaluation included 3 successive steps: (1) expert reviews; (2) evaluation of the ability of health care professionals and medical students to create, share, and exchange virtual patients through specific scenarios in extended OpenLabyrinth (OLabX); and (3) evaluation of the repurposed learning objects that emerged from the procedure.

Results: We evaluated 30 repurposed virtual patient cases. The evaluation, with a total of 98 participants, demonstrated the system's main strength: the core repurposing capacity. The extensive metadata schema presentation facilitated user exploration and filtering of resources. Usability weaknesses were primarily related to standard computer applications' ease of use provisions. Most evaluators provided positive feedback regarding educational experiences on both content and system usability. Evaluation results replicated across several independent evaluation events.

Conclusions: The OpenLabyrinth extension, as part of the semantic mEducator3.0 approach, is a virtual patient sharing approach that builds on a collection of Semantic Web services and federates existing sources of clinical and educational data. It is an effective sharing tool for virtual patients and has been merged into the next version of the app (OpenLabyrinth 3.3). Such tool extensions may enhance the medical education arsenal with capacities of creating simulation/game-based learning episodes, massive open online courses, curricular transformations, and a future robust infrastructure for enabling mobile learning.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4319094PMC
http://dx.doi.org/10.2196/jmir.3933DOI Listing

Publication Analysis

Top Keywords

virtual patients
28
virtual patient
24
virtual
13
semantic web
12
health care
8
educational resources
8
exchange virtual
8
extended openlabyrinth
8
openlabyrinth virtual
8
patient authoring
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!