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Kononowicz AA, Narracott AJ, Manini S, et al. A framework for different levels of integration of computational models into web-based virtual patients. J Med Internet Res. 2014;16(1):e23doi: 10.2196/jmir.2593.
Kononowicz, A. A., Narracott, A. J., Manini, S., Bayley, M. J., Lawford, P. V., McCormack, K., & Zary, N. (2014). A framework for different levels of integration of computational models into web-based virtual patients. Journal of medical Internet research, 16(1), e23. https://doi.org/10.2196/jmir.2593
Kononowicz, Andrzej A, et al. "A framework for different levels of integration of computational models into web-based virtual patients." Journal of medical Internet research vol. 16,1 (2014): e23. doi: https://doi.org/10.2196/jmir.2593
Kononowicz AA, Narracott AJ, Manini S, Bayley MJ, Lawford PV, McCormack K, Zary N. A framework for different levels of integration of computational models into web-based virtual patients. J Med Internet Res. 2014 Jan 23;16(1):e23. doi: 10.2196/jmir.2593. PMID: 24463466; PMCID: PMC3906686.
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J Med Internet Res. 2014 Jan 23;16(1):e23. doi: 10.2196/jmir.2593.

A framework for different levels of integration of computational models into web-based virtual patients.

Journal of medical Internet research

Andrzej A Kononowicz, Andrew J Narracott, Simone Manini, Martin J Bayley, Patricia V Lawford, Keith McCormack, Nabil Zary

Affiliations

  1. Digital Patient Lab, Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden. [email protected].

PMID: 24463466 PMCID: PMC3906686 DOI: 10.2196/jmir.2593

Abstract

BACKGROUND: Virtual 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.

OBJECTIVE: The 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.

METHODS: The 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.

RESULTS: The 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.

CONCLUSIONS: This 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.

Keywords: computer simulation; computer-assisted instruction; education, medical; medical informatics applications

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