Utilising neural network applications to enhance efficiency in the healthcare industry: Predicting populations of future chronic illness
Document Type
Article
Publication Date
1-1-2006
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. Copyright © 2006 Inderscience Enterprises Ltd.
Identifier
33750967052 (Scopus)
Publication Title
International Journal of Business Intelligence and Data Mining
External Full Text Location
https://doi.org/10.1504/IJBIDM.2006.010780
e-ISSN
17438195
ISSN
17438187
First Page
371
Last Page
383
Issue
4
Volume
1
Recommended Citation
Kudyba, Stephan; Hamar, G. Brent; and Gandy, William M., "Utilising neural network applications to enhance efficiency in the healthcare industry: Predicting populations of future chronic illness" (2006). Faculty Publications. 19122.
https://digitalcommons.njit.edu/fac_pubs/19122
