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The Conceptual MADE Framework for Pervasive and Knowledge-Based Decision Support in Telemedicine

The Conceptual MADE Framework for Pervasive and Knowledge-Based Decision Support in Telemedicine

Nick L. S. Fung, Valerie M. Jones, Ing Widya, Tom H. F. Broens, Nekane Larburu, Richard G. A. Bults, Erez Shalom, Hermie J. Hermens
Copyright: © 2016 |Volume: 7 |Issue: 1 |Pages: 15
ISSN: 1947-8208|EISSN: 1947-8216|EISBN13: 9781466692268|DOI: 10.4018/IJKSS.2016010102
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MLA

Fung, Nick L. S., et al. "The Conceptual MADE Framework for Pervasive and Knowledge-Based Decision Support in Telemedicine." IJKSS vol.7, no.1 2016: pp.25-39. https://doi.org/10.4018/IJKSS.2016010102

APA

Fung, N. L., Jones, V. M., Widya, I., Broens, T. H., Larburu, N., Bults, R. G., Shalom, E., & Hermens, H. J. (2016). The Conceptual MADE Framework for Pervasive and Knowledge-Based Decision Support in Telemedicine. International Journal of Knowledge and Systems Science (IJKSS), 7(1), 25-39. https://doi.org/10.4018/IJKSS.2016010102

Chicago

Fung, Nick L. S., et al. "The Conceptual MADE Framework for Pervasive and Knowledge-Based Decision Support in Telemedicine," International Journal of Knowledge and Systems Science (IJKSS) 7, no.1: 25-39. https://doi.org/10.4018/IJKSS.2016010102

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Abstract

Telemedicine systems are inherently distributed, but, especially in the context of the Internet-of-Things, their complete physical configuration may only be determined after design time by considering, for example, the individual patient's needs. Therefore, to enable pervasive and knowledge-based decision support to be provided in telemedicine, a conceptual framework was developed for modelling and executing clinical knowledge as networks of four types of concurrent processes: Monitoring (M), Analysis (A), Decision (D) and Effectuation (E). In this way, the required decision support functionality can, as presented in this article, be distributed at run-time by mapping different portions of the knowledge across the devices constituting the system. This MADE framework was applied to model a clinical guideline for gestational diabetes mellitus and to derive a prototype knowledge-based system that executes the resulting MADE network. Thus it is shown to support the full development trajectory of a telemedicine system, including analysis, design and implementation.

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