Decision support systems for adoption in dental clinics: a survey
Article
Article Title | Decision support systems for adoption in dental clinics: a survey |
---|---|
ERA Journal ID | 18062 |
Article Category | Article |
Authors | Goh, Wee Pheng (Author), Tao, Xiaohui (Author), Zhang, Ji (Author) and Yong, Jianming (Author) |
Journal Title | Knowledge-Based Systems |
Journal Citation | 104, pp. 195-206 |
Number of Pages | 12 |
Year | 2016 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0950-7051 |
1872-7409 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.knosys.2016.04.022 |
Web Address (URL) | http://www.sciencedirect.com/science/article/pii/S0950705116300740 |
Abstract | While most dental clinicians use some sort of information system, they are involved with administrative functions, despite the advisory potential of some of these systems. This paper outlines some current decision support systems (DSS) and the common barriers facing dentists in adopting them within their workflow. These barriers include lack of perceived usefulness, complicated social and economic factors, and the difficulty for users to interpret the advice given by the system. A survey of current systems found that although there are systems that suggest treatment options, there is no real-time integration with other knowledge bases. Additionally, advice on drug prescription at point-of-care is absent from such systems, which is a significant omission, in consideration of the fact that disease management and drug prescription are common in the workflow of a dentist. This paper also addresses future trends in the research and development of dental clinical DSS, with specific emphasis on big data, standards and privacy issues to fulfil the vision of a robust, user-friendly and scalable personalised DSS for dentists. The findings of this study will offer strategies in design, research and development of a DSS with sufficient perceived usefulness to attract adoption and integration by dentists within their routine clinical workflow, thus resulting in better health outcomes for patients and increased productivity for the clinic. |
Keywords | dental clinical decision support system; dental informatics; dental HCI; big data |
ANZSRC Field of Research 2020 | 460902. Decision support and group support systems |
Public Notes | First place winner for the USQ School-Specific 2016 Publication Excellence Awards for Journal Articles - School of Management and Enterprise. |
Byline Affiliations | School of Agricultural, Computational and Environmental Sciences |
School of Management and Enterprise | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q36wx/decision-support-systems-for-adoption-in-dental-clinics-a-survey
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