Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/435
Title: Incorporating intelligent risk detection to enable superior decision support: the example of orthopaedic surgeries.
Epworth Authors: Wickramasinghe, Nilmini
Other Authors: Moghimi, Hoda
Zadeh, Hossein
Schaffer, Jonathan
Keywords: Orthopaedic Surgeries
Intelligent Risk Detection
Surgery
Surgery Risk Levels
Knowledge Discovery
Surgical Decisions
Hip Surgeries
Knee Surgeries
Orthopaedics
Knowledge Discovery
Data Mining
Decision Support Systems
Chair of Healthcare Information, Epworth HealthCare, Melbourne, Victoria, Australia
Issue Date: Jan-2012
Publisher: Springer
Citation: Health and Technology, vol. 2, no. 1, pp. 33-41.
Abstract: Decision making in healthcare is unstructured, complex and critical. Today, healthcare professionals are continually under immense time pressure to make appropriate treatment decisions which in turn have far reaching implications on the quality of outcomes. Moreover, in order to make such decisions it is necessary for them to process large amounts of disparate data and information. We contend that such a context is appropriate for the application of real time intelligent risk detection decision support. In this application data mining tools in combination with Knowledge Discovery (KD) techniques are used to score the surgery risk levels, assess surgery risks and help medical professionals to make appropriate and superior complex surgical decisions for each patient. To illustrate the benefits of such intelligent risk detection to improve decision efficacy in healthcare contexts we focus within the context of Orthopaedic Surgeries, specifically on hip and knee surgeries. This paper concludes with a conceptual model to move successfully from idea to design and then implementation.
URI: http://hdl.handle.net/11434/435
DOI: doi.org/10.1007/s12553-011-0014-z
ISSN: 2190-7188
2190-7196
Journal Title: Health and Technology
Type: Journal Article
Type of Clinical Study or Trial: Review
Appears in Collections:Musculoskeletal
Health Informatics

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