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Leverage Healthcare Data Assets with Predictive Analytics: The Example of an Australian Private Hospital

Leverage Healthcare Data Assets with Predictive Analytics: The Example of an Australian Private Hospital

Nilmini Wickramasinghe, Hoda Moghimi, Jonathan L. Schaffer
Copyright: © 2017 |Pages: 15
ISBN13: 9781522518372|ISBN10: 1522518371|EISBN13: 9781522518389
DOI: 10.4018/978-1-5225-1837-2.ch035
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MLA

Wickramasinghe, Nilmini, et al. "Leverage Healthcare Data Assets with Predictive Analytics: The Example of an Australian Private Hospital." Decision Management: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2017, pp. 823-837. https://doi.org/10.4018/978-1-5225-1837-2.ch035

APA

Wickramasinghe, N., Moghimi, H., & Schaffer, J. L. (2017). Leverage Healthcare Data Assets with Predictive Analytics: The Example of an Australian Private Hospital. In I. Management Association (Ed.), Decision Management: Concepts, Methodologies, Tools, and Applications (pp. 823-837). IGI Global. https://doi.org/10.4018/978-1-5225-1837-2.ch035

Chicago

Wickramasinghe, Nilmini, Hoda Moghimi, and Jonathan L. Schaffer. "Leverage Healthcare Data Assets with Predictive Analytics: The Example of an Australian Private Hospital." In Decision Management: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 823-837. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1837-2.ch035

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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.

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