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DC Field | Value | Language |
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dc.contributor.author | Wickramasinghe, Nilmini | - |
dc.contributor.editor | Moon, J. | - |
dc.contributor.editor | Galea, Mary | - |
dc.contributor.other | Moghimi, H. | - |
dc.contributor.other | Schaffer, Jonathan | - |
dc.date.accessioned | 2018-10-24T22:52:46Z | - |
dc.date.available | 2018-10-24T22:52:46Z | - |
dc.date.issued | 2016 | - |
dc.identifier.isbn | 9781466694323 | en_US |
dc.identifier.uri | http://hdl.handle.net/11434/1537 | - |
dc.description.abstract | Multi-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.publisher | IGI Global | en_US |
dc.subject | Multi-spectral Data | en_US |
dc.subject | Health Information Technology | en_US |
dc.subject | Data Analysis | en_US |
dc.subject | Hospital Casemix Protocol | en_US |
dc.subject | Data Warehousing | en_US |
dc.subject | Technology Solutions | en_US |
dc.subject | Information Technology | en_US |
dc.subject | IT | en_US |
dc.subject | Predictive Analytics | en_US |
dc.subject | Private Hospitals | en_US |
dc.subject | Chair of Health Informatics Management, Epworth HealthCare, Victoria, Australia | en_US |
dc.title | Leverage health care data assets with predictive analytics: The example of an Australian private hospital. | en_US |
dc.type | Chapter | en_US |
dc.identifier.doi | 10.4018/978-1-4666-9432-3.ch011 | en_US |
dc.description.affiliates | Health Informatics | en_US |
dc.description.affiliates | RMIT University, Melbourne, Victoria, Australia | en_US |
dc.description.affiliates | Cleveland Clinic, Cleveland, Ohio, United States | en_US |
dc.type.contenttype | Text | en_US |
dc.title.book | Improving Health Management through Clinical Decision Support Systems | en_US |
Appears in Collections: | Health Informatics |
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