Background: The Web-based Simulation of Patients (Web-SP) project was initiated in order to facilitate the use of realistic and interactive virtual patients (VP) in medicine and healthcare education. Web-SP focuses on moving beyond the technology savvy teachers, when integrating simulation-based education into health sciences curricula, by making the creation and use of virtual patients easier. The project strives to provide a common generic platform for design/creation, management, evaluation and sharing of webbased virtual patients. The aim of this study was to evaluate if it was possible to develop a web-based virtual patient case simulation environment where the entire case authoring process might be handled by teachers and which would be flexible enough to be used in different healthcare disciplines.

The analysis of students' online activities in a blended medical education course by means of LA techniques can help early predict underachieving students, and can be used as an early warning sign for timely intervention.

BackgroundCollaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students’ performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance.MethodsInteraction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students’ performance was calculated, and automatic linear regression was used to predict students’ performance.ResultsBy using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user’s position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student’s position and role in information relay in online case discussions, combined with the strength of that student’s network (social capital), can be used as predictors of performance in relevant settings.ConclusionBy using social network analysis, researchers can analyze the social structure of an online course and reveal important information about students’ and teachers’ interactions that can be valuable in guiding teachers, improve students’ engagement, and contribute to learning analytics insights.Electronic supplementary materialThe online version of this article (10.1186/s12909-018-1126-1) contains supplementary material, which is available to authorized users.

Medication dosing errors are frequent in neonatal wards. In an Iranian neonatal ward, a 7.5 months study was designed in three periods to compare the effect of Computerized Physician Order Entry (CPOE) without and with decision support functionalities in reducing non-intercepted medication dosing errors in antibiotics and anticonvulsants. Before intervention (Period 1), error rate was 53%, which did not significantly change after the implementation of CPOE without decision support (Period 2). However, errors were significantly reduced to 34% after that the decision support was added to the CPOE (Period 3; P < 0.001). Dose errors were more often intercepted than frequency errors. Over-dose was the most frequent type of medication errors and curtailed-interval was the least. Transcription errors did not reduce after the CPOE implementation. Physicians ignored alerts when they could not understand why they appeared. A suggestion is to add explanations about these reasons to increase physicians' compliance with the system's recommendations.

Virtual patients as a form of educational intervention can take many forms and can provide highly effective ways of addressing reduced student access to real patients, the need for standardised and well-structured educational patient encounters, and opportunities for students to practice in safe and responsive environments. However, virtual patients can also be complicated and costly to develop. As a result collaborative and distributed development is best suited to their widespread take up. This paper considers the development and use of virtual patients and the steps that have been taken to support authors in making this approach more sustainable and adaptable. In particular, this has involved the development of a common data interoperability standard, which in turn has engaged a number of communities that have developed, or are developing, virtual patient commons, consisting of shared resources, tools and knowledge for mutual benefit. The paper illustrates how innovative and otherwise difficult to sustain models for supporting and extending healthcare education, such as virtual patients, can be supported using a commons approach with commonly agreed data standards and specifications at their core.