Enhancing efficiency in the health care industry

Authors:
Stephan Kudyba;G. Brent Hamar;William M. Gandy
Affiliations:
New Jersey Institute of Technology, University Heights, CAB Building, Newark, NJ;American Healthways, Inc., Nashville, TN;American Healthways, Inc., Nashville, TN
Venue:
Communications of the ACM - The semantic e-business vision
Year:
2005

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Abstract

This paper illustrates the use of advanced analytics to increase efficiency in the healthcare sector through cost reduction. The application of multivariate techniques on health population data depicted better accuracy in identifying patients at risk of developing a chronic illness (diabetes) than more conventional techniques. The model results enable healthcare providers to more effectively apply preventive treatment methods to the at-risk population to reduce the likelihood of individuals from experiencing a fully developed illness. An estimate of the cost savings in the form of preventing cases of fully developed diabetes through predictive modeling is included.