Title: Exploring the possibilities for intelligent risk detection in healthcare contexts

Authors: Hoda Moghimi; Jonathan L. Schaffer; Nilmini Wickramasinghe

Addresses: 15 Pentlowe Ave, Templestowe Lower, VIC 3107, Australia ' Center for Joint Replacement, Department of Orthopaedic Surgery, Distance Health, Clinical Transformation, Information Technology Division, 9500 Euclid Avenue, Desk A41, Cleveland, Ohio 44195, USA ' Epworth HealthCare & Deakin University, Office of the PVC, Bldg BC Level 4, 221 Burwood Highway, Burwood VIC 3125, Australia

Abstract: The exponential growth of data coupled with a rapid increase of service demands in healthcare contexts today requires a robust framework enabled by information technology (IT) solutions as well as real-time service handling in order to ensure superior decision making and successful healthcare outcomes. Contemporaneous with the challenges facing healthcare, we are witnessing the development of very sophisticated intelligent tools and technologies. Therefore, it would appear to be prudent to investigate the possibility of applying such tools and technologies into various healthcare contexts to facilitate better risk detection and support superior decision making. This study is exploratory in nature and endeavours to explore the main components, barriers, issues and requirements to design and develop an intelligent risk detection framework to be applied to healthcare contexts. The following serves to do this in the context of orthopaedics, total hip and knee arthroplasty and congenital heart disease.

Keywords: clinical decision making; risk detection; orthopaedics; knowledge management; business intelligence; business analytics; congenital heart disease; CHD; total hip and knee arthroplasty; risk assessment; healthcare technology; e-healthcare; electronic healthcare; intelligent systems; decision support systems; DSS.

DOI: 10.1504/IJNVO.2016.076490

International Journal of Networking and Virtual Organisations, 2016 Vol.16 No.2, pp.171 - 190

Received: 13 Jun 2015
Accepted: 13 Jul 2015
Published online: 10 May 2016 *

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