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Published VersionCC BY V3.0, Open Access
Journal article
Meta-design Knowledge for Clinical Decision Support Systems
Australasian Journal of Information Systems, Vol.24, pp.1-21
2020
Abstract
Knowledge gained from a Decision Support Systems (DSS) design should ideally be reusable by DSS designers and researchers. The majority of existing DSS research has mainly focused on empirical problem solving rather than on developing principles that could inform solution approaches for other user contexts. Design Science Research (DSR) has contributed to effective development of various innovative DSS artifacts and associated knowledge development, but there has been limited progress on new knowledge development from a practical problem context, going beyond product and process descriptions. For DSS applications such as Clinical Decision Support Systems (CDSS) design and development, relevant reusable prescriptive knowledge is of significance not only to understand mutability but also to extend application of theory across domains. In this paper, we develop new design knowledge abstracted from the approach taken in a representative case of innovative CDSS development, specified as an architecture and six design principles. The CDSS design artifact was initially designed for a specific clinical need is shown to be flexible for meeting demands of knowledge production both for diagnosis and treatment. It is argued that the proposed general strategy is applicable to designing CDSS artifacts in similar problem domains representing an important contribution of design knowledge both in DSS and DSR fields.
Details
- Title
- Meta-design Knowledge for Clinical Decision Support Systems
- Authors
- Shah J Miah (Author) - Victoria UniversityJacqueline Blake (Author) - University of the Sunshine Coast - USC Business SchoolDon Kerr (Author) - University of the Sunshine Coast - USC Business School
- Publication details
- Australasian Journal of Information Systems, Vol.24, pp.1-21
- Publisher
- University of Canberra
- Date published
- 2020
- DOI
- 10.3127/ajis.v24i0.2049
- ISSN
- 1326-2238; 1449-8618
- Copyright note
- Copyright © 2020. Miah, Blake & Kerr. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial 3.0 Australia License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and AJIS are credited.
- Organisation Unit
- University of the Sunshine Coast, Queensland; USC Business School - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99450949502621
- Output Type
- Journal article
- Research Statement
- false
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Computer Science, Information Systems