Utilising neural network applications to enhance efficiency in the healthcare industry: predicting populations of future chronic illness

Authors:
Stephan Kudyba;G. Brent Hamar;William M. Gandy
Affiliations:
Department of Management, New Jersey Institute of Technology, University Heights, Newark, NJ, USA.;Informatics, Healthways Inc., USA.;Informatics, Healthways Inc., USA
Venue:
International Journal of Business Intelligence and Data Mining
Year:
2006

Citing 6
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Abstract

Advanced analytic and forecasting methodologies can enable organisations to more fully leverage the data resources available to them. In the healthcare industry, service providers can use data mining methods to enhance the decision-making process in optimising resource allocation by identifying the sources of future high-cost treatment in a given health plan population. The following paper includes a case study by Healthways Inc. that illustrates how predictive modelling techniques (e.g., neural networks) can help healthcare providers identify the sources of future high resource demand, enabling them to more effectively apply preemptive treatment to mitigate future high-cost treatment of fully developed cases of chronic illness.