The Strategic Value of Big Data Analytics in Health Care Policy-Making

The Strategic Value of Big Data Analytics in Health Care Policy-Making

Hamed M. Zolbanin (Ball State University, Muncie, USA), Dursun Delen (Oklahoma State University, Tulsa, USA) and Sushil K. Sharma (Ball State University, Muncie, USA)
Copyright: © 2018 |Pages: 14
DOI: 10.4018/IJEBR.2018070102
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This article describes how the metrics that are used to gauge acceptable versus inadequate care have spurred debates among health care administrators and scholars. Specifically, they argue that the use of readmissions as a quality-of-care metric may reduce patients' safety. Consequently, the new well-intended policies may prove ineffective, or even worse, yield disappointing results. While the discussions over the advantages and disadvantages of the new policies are based more on conjectures rather than on evidence, analytics provides a vehicle to measure the effectiveness of such overarching strategies. In this effort, the authors analyze large volumes of hospital encounters data before and after the implementation of the Patient Protection and Affordable Care Act (PPACA) to show how overlooking some aspects of a problem may lead to unexpected outcomes. The authors conclude that the feedback provided by big data analytics can be used by the government and organization policymakers to obtain a better understanding of loopholes and to propose more effective policies in prospective endeavors.
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An Overview Of Ppaca

PPACA is a watershed in the U.S. public health policy (Rosenbaum, 2011). Signed into law on March 23, 2010, the act is a combination of ten separate legislative titles that seeks several key objectives, including reduction of costs to enable the system to serve a larger number of patients. A significant portion of the projected cost savings has been planned to be realized from the elimination of wasteful spending within the health care system, such as preventable hospital readmissions.

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