Data Mining in Health Care Applications

Data Mining in Health Care Applications

Fay Cobb Payton (North Carolina State University, USA)
Copyright: © 2003 |Pages: 16
DOI: 10.4018/978-1-59140-051-6.ch015
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Abstract

Recent attention has turned to the healthcare industry and its use of voluntary community health information network (CHIN) models for e-health and care delivery. This chapter suggests that competition, economic dimensions, political issues, and a group of enablers are the primary determinants of implementation success. Most critical to these implementations is the issue of data management and utilization. Thus, health care organizations are finding value as well as strategic applications to mining patient data, in general, and community data, in particular. While significant gains can be obtained and have been noted at the organizational level of analysis, much attention has been given to the individual, where the focal points have centered on privacy and security of patient data. While the privacy debate is a salient issue, data mining (DM) offers broader community-based gains that enable and improve healthcare forecasting, analyses, and visualization.

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