A Framework for Different Levels of Integration of Computational Models Into Web-Based Virtual Patients

Abstract

BackgroundVirtual patients are increasingly common tools used in health care education to foster learning of clinical reasoning skills. One potential way to expand their functionality is to augment virtual patients’ interactivity by enriching them with computational models of physiological and pathological processes.ObjectiveThe primary goal of this paper was to propose a conceptual framework for the integration of computational models within virtual patients, with particular focus on (1) characteristics to be addressed while preparing the integration, (2) the extent of the integration, (3) strategies to achieve integration, and (4) methods for evaluating the feasibility of integration. An additional goal was to pilot the first investigation of changing framework variables on altering perceptions of integration.MethodsThe framework was constructed using an iterative process informed by Soft System Methodology. The Virtual Physiological Human (VPH) initiative has been used as a source of new computational models. The technical challenges associated with development of virtual patients enhanced by computational models are discussed from the perspectives of a number of different stakeholders. Concrete design and evaluation steps are discussed in the context of an exemplar virtual patient employing the results of the VPH ARCH project, as well as improvements for future iterations.ResultsThe proposed framework consists of four main elements. The first element is a list of feasibility features characterizing the integration process from three perspectives: the computational modelling researcher, the health care educationalist, and the virtual patient system developer. The second element included three integration levels: basic, where a single set of simulation outcomes is generated for specific nodes in the activity graph; intermediate, involving pre-generation of simulation datasets over a range of input parameters; advanced, including dynamic solution of the model. The third element is the description of four integration strategies, and the last element consisted of evaluation profiles specifying the relevant feasibility features and acceptance thresholds for specific purposes. The group of experts who evaluated the virtual patient exemplar found higher integration more interesting, but at the same time they were more concerned with the validity of the result. The observed differences were not statistically significant.ConclusionsThis paper outlines a framework for the integration of computational models into virtual patients. The opportunities and challenges of model exploitation are discussed from a number of user perspectives, considering different levels of model integration. The long-term aim for future research is to isolate the most crucial factors in the framework and to determine their influence on the integration outcome.

Evaluation of three educational use cases for using Virtual Patients in Massive Open Online Courses (MOOCs): a Delphi study

“…Regarding use case C′, the concept of integrating computational models within VP cases has received positive feedback in previous studies [25] and according to the experts has the greatest potential in raising the learners' interest. Even though case C′ was considered by the experts to take the least advantage of the MOOC potential, we see the possibility that computational models integrated into short cases enable adaptive learning and provide insights of the participants' learning experience.…”

Perpetual and Virtual Patients for Cardiorespiratory Physiological Studies

“…2,26 Several types of educational technologies, described in the medical and education literature, are considered to comprise virtual simulation, even if they differ from each other in terms of realism, complexity, financial and human cost, or interface. 4,5,20,21,24,26 The focus of this work is on VP, defined as 4,19,20,27,28 "interactive computer simulation of real-life clinical scenarios for the purpose of health care and medical training, education or assessment." According to the VP definition of Ellaway et al, 4,19,20,27,28 a VP attempts to recreate patients and their environment through a computer interface, 5 with which students can interact to resolve clinical situations, physiological interrogations, or technical issues.…”

“…4,5,20,21,24,26 The focus of this work is on VP, defined as 4,19,20,27,28 "interactive computer simulation of real-life clinical scenarios for the purpose of health care and medical training, education or assessment." According to the VP definition of Ellaway et al, 4,19,20,27,28 a VP attempts to recreate patients and their environment through a computer interface, 5 with which students can interact to resolve clinical situations, physiological interrogations, or technical issues. 5 There are many advantages 4,19,20,[25][26][27][28][29][30][31][32][33] to using VPs in medical training.…”

“…According to the VP definition of Ellaway et al, 4,19,20,27,28 a VP attempts to recreate patients and their environment through a computer interface, 5 with which students can interact to resolve clinical situations, physiological interrogations, or technical issues. 5 There are many advantages 4,19,20,[25][26][27][28][29][30][31][32][33] to using VPs in medical training. Even though VPs do not replace the need for direct interactions with real patients, VPs have been proven to enhance clinical skills and to improve knowledge acquisition, 3,4,27 as reported in several systematic reviews and meta-analysis.…”

“…[10][11][12][13][14][15][16][17][18] The purpose of this article is to define a VP for use in cardiorespiratory simulation and describe interactions with physiological modeling leading to the conception of computational models. 19 We aim to review the literature on the development of such VPs, proposing a step-by-step methodology for their validation and to study their actual contribution to studies of cardiorespiratory physiology. [20][21][22] We also emphasize the role of high-quality clinical databases for validation of computational models and the new concept of the perpetual patient (PP).…”