Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/1837
Title: Leveraging key aspects of collaborative techniques to assist clinical decision making: The case of hip and knee arthroplasty.
Epworth Authors: Wickramasinghe, Nilmini
de Steiger, Richard
Other Authors: Moghimi, Hoda
Haddad, Peter
Schaffer, Jonathan
Keywords: Surgery
Decision Making
Decision Support Systems
Collaborative Systems
Clinical Decision Making
Intelligent Computer Solutions
Intelligent Risk Detection Model
Design Science Research Methodology
Hip and Knee Arthroplasty
Chair of Health Informatics Management, Epworth HealthCare, Victoria, Australia
Musculoskeletal Clinical Institute, Epworth HealthCare, Victoria, Australia
Issue Date: Jan-2015
Conference Name: 48th Hawaii International Conference on System Sciences (HICSS)
Conference Location: Hawaii, USA
Abstract: Employing collaborative systems in healthcare contexts has been explored as an important approach towards designing and developing intelligent computer solutions. This approach is concerned with identify the way in which information and decisions are assembled in the collaboration of care parties. In this regards, this study is conducted to develop a real-time collaborative system using an Intelligent Risk Detection Model (IRD) to improve decision efficiency in the case of Hip and Knee Arthroplasty. The benefits of adopting this solution include increasing awareness, supporting communication, improving decision making process and also improving information sharing between surgeons as key collaborative parties in the research case. This paper presents outcomes of an on-line survey and focus group using Design Science Research Methodology (DSRM) to identify requirements of designing the system. It will be then possible to develop the prototype.
URI: http://hdl.handle.net/11434/1837
DOI: 10.1109/HICSS.2015.101
Type: Conference Paper
Affiliated Organisations: RMIT University, Melbourne, Victoria, Australia
Cleveland Clinic, Cleveland, Ohio, USA
Appears in Collections:Health Informatics
Musculoskeletal

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