Predictive Analytics and Intelligent Risk Detection in Healthcare Contexts

Predictive Analytics and Intelligent Risk Detection in Healthcare Contexts

Nilmini Wickramasinghe (Epworth HealthCare, Australia & Deakin University, Australia)
DOI: 10.4018/978-1-5225-2255-3.ch589
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Abstract

As the value agenda progresses in healthcare, we are witnessing a growing interest in the potential and possibilities for predictive analytics and intelligent risk detection to facilitate the processing of multi-spectral data to enable and sound decision making to ensue. However, the exponential growth of data coupled with a rapid increase of service demands in healthcare contexts today requires a robust framework enabled by IT (information technology) solutions as well as real-time service handling in order to ensure superior decision making and successful healthcare outcomes. The following serves to unpack critical issues in this regard context of Orthopedics.
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Background

Recent discussions on healthcare disparities (Gibbons, 2011) all note the significant potential benefit technology can make in trying to provide an equal experience to all Americans. Sadly, while there are many good points about the US healthcare system, there also exists a considerable racial and ethnic disparity in the delivery of healthcare across the US (ibid). The underlying root causes for these disparities are all amenable to interventions using IS/IT(information systems/information technology). The thesis of this paper is that technology is well suited to assist is that of limited English proficiency (LEP).

More than 23 million Americans today have limited English proficiency, which in turn has a negative impact on their ability to receive and comprehend appropriate healthcare delivery(Youdelman, 2008; Flores et al. 2008). Integral to the delivery of care is communication between doctor and patient; however, language barriers typically lead to problems such as delay or denial of services, issues with medication management, and underutilization of preventative services (Green et al, 2005; Jacobs et al, 2004; Ghandi et al, 2000; Karliner et al, 2004). The literature suggests that the quality of communication between Although Title VI of the Civil Rights Act 1964 has always required that entities receiving federal funds provide language services to those with LEP, the law has not often been enforced in healthcare settings (Jacobs et al., 2006). However, awareness of the need to provide language services in healthcare has increased in recent years (Gibbons, 2011).

Key Terms in this Chapter

Language Translation: The act of converting the meaning into a different language.

Meaningful Use: Federal government stipulation for technology solutions in healthcare.

Real-Time Translation: Translation that happens instantaneously at the point of action.

Cloud-Based Computing (or Cloud Computing): When computing resources such as software and hardware are delivered as a service over a network.

Healthcare Delivery: The network, structure and stakeholders involved in administering medical care to individuals.

LEP-Limited English Proficiency: Individuals for whom English is not their native language and thus have difficulty communicating and understanding in English.

Human Interpreter: Person who performs language translation.

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