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Choosing Technologies for Handheld and Ubiquitous Decision Support

Choosing Technologies for Handheld and Ubiquitous Decision Support

Darren Woollatt, Paul Koop, Sara Jones, Jim Warren
Copyright: © 2007 |Volume: 2 |Issue: 3 |Pages: 11
ISSN: 1555-3396|EISSN: 1555-340X|ISSN: 1555-3396|EISBN13: 9781615202966|EISSN: 1555-340X|DOI: 10.4018/jhisi.2007070101
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MLA

Woollatt, Darren, et al. "Choosing Technologies for Handheld and Ubiquitous Decision Support." IJHISI vol.2, no.3 2007: pp.1-11. http://doi.org/10.4018/jhisi.2007070101

APA

Woollatt, D., Koop, P., Jones, S., & Warren, J. (2007). Choosing Technologies for Handheld and Ubiquitous Decision Support. International Journal of Healthcare Information Systems and Informatics (IJHISI), 2(3), 1-11. http://doi.org/10.4018/jhisi.2007070101

Chicago

Woollatt, Darren, et al. "Choosing Technologies for Handheld and Ubiquitous Decision Support," International Journal of Healthcare Information Systems and Informatics (IJHISI) 2, no.3: 1-11. http://doi.org/10.4018/jhisi.2007070101

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Abstract

Wireless, handheld devices are becoming increasingly popular in health care settings, but the full potential of their role in patient-specific decision support remains to be achieved. This article presents a multicriteria framework for choosing technologies apropos to handheld and ubiquitous decision support architecture. This framework is illustrated through architectural middleware choices made in the context of a podiatry and diabetes care network. Performance issues are found to be very important in the handheld space, and minor aspects of connectivity and other constraints drive significant changes in choices of architectural approach. The resulting architecture employs layers, including serialized objects, XML payloads, event notification, Web services, and dynamic class loading, with the mix varying among the system interfaces. The overall recommendation is that organizations wishing to fully exploit mobile technology must use a flexible policy and pursue a process of technology choice that is scenario-based and iterative to take into account discoveries from prototyping and field-test experience.

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