Journal article
Streamlining patient consultations for sleep disorders with a knowledge-based CDSS
Information Systems, Vol.56, pp.109-119
2016
Abstract
Objectives: This paper examines the workflow of sleep physicians during a patient consultation and how an innovative clinical decision support system (CDSS) provides efficiency and effectiveness gains. Methods: The CDSS tools consisted of two input applications for patient data, with a knowledge based decision support system developed participatively with physicians and an international panel. An argument tree approach was used to produce diagnostic explanations and an evidence-based report for the physician using medically correct and shared terminology. A usability evaluation using a qualitative approach was carried out to ensure that the CDSS met the physicians' information needs, as well as the wider needs of a Sleep Investigation Unit. Results: The physicians found the CDSS both useful and usable with clear applications in triage and diagnostic decision-making, and in patient education. Conclusion: The CDSS both reduces the time and number of visits needed for consultations, and helps focus consultation on better individual patient care through informed explanation of diagnostic and treatment decisions.
Details
- Title
- Streamlining patient consultations for sleep disorders with a knowledge-based CDSS
- Authors
- Jacqueline Blake (Author) - University of the Sunshine Coast - Faculty of Arts, Business and LawDon Kerr (Author) - University of the Sunshine Coast - Faculty of Arts, Business and LawJohn G Gammack (Author) - Zayed University, United Arab Emirates
- Publication details
- Information Systems, Vol.56, pp.109-119
- Publisher
- Elsevier Ltd.
- Date published
- 2016
- DOI
- 10.1016/j.is.2015.08.003
- ISSN
- 0306-4379
- Copyright note
- Copyright © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
- Organisation Unit
- University of the Sunshine Coast, Queensland; USC Business School - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99449309402621
- Output Type
- Journal article
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