Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/1537
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dc.contributor.authorWickramasinghe, Nilmini-
dc.contributor.editorMoon, J.-
dc.contributor.editorGalea, Mary-
dc.contributor.otherMoghimi, H.-
dc.contributor.otherSchaffer, Jonathan-
dc.date.accessioned2018-10-24T22:52:46Z-
dc.date.available2018-10-24T22:52:46Z-
dc.date.issued2016-
dc.identifier.isbn9781466694323en_US
dc.identifier.urihttp://hdl.handle.net/11434/1537-
dc.description.abstractMulti-spectral data residing in disparate data bases represents a critical raw asset for today's healthcare organizations (). However, in order to gain maximum value from such data, it is essential to apply prudent technology solutions and tailored analytic techniques. The following chapter proposes how the application of bespoke predictive analytic tools and techniques can be designed and then applied to a hospital data warehouse, called the Hospital Casemix Protocol (HCP) Extended data set, in order to improve decision efficiency in the private healthcare sector in Australia. The main objective of this chapter is to present the developed conceptual model to demonstrate inputs, outputs, components, principles and services of predictive analytics for private hospitals.en_US
dc.publisherIGI Globalen_US
dc.subjectMulti-spectral Dataen_US
dc.subjectHealth Information Technologyen_US
dc.subjectData Analysisen_US
dc.subjectHospital Casemix Protocolen_US
dc.subjectData Warehousingen_US
dc.subjectTechnology Solutionsen_US
dc.subjectInformation Technologyen_US
dc.subjectITen_US
dc.subjectPredictive Analyticsen_US
dc.subjectPrivate Hospitalsen_US
dc.subjectChair of Health Informatics Management, Epworth HealthCare, Victoria, Australiaen_US
dc.titleLeverage health care data assets with predictive analytics: The example of an Australian private hospital.en_US
dc.typeChapteren_US
dc.identifier.doi10.4018/978-1-4666-9432-3.ch011en_US
dc.description.affiliatesHealth Informaticsen_US
dc.description.affiliatesRMIT University, Melbourne, Victoria, Australiaen_US
dc.description.affiliatesCleveland Clinic, Cleveland, Ohio, United Statesen_US
dc.type.contenttypeTexten_US
dc.title.bookImproving Health Management through Clinical Decision Support Systemsen_US
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