The tools used, in this case, for knowledge discovery and data mining where based on artificial neural networks (ANN) and consisted of four different models. All models represented supervised learning models with a known output. The four models of the ANN were dynamic network, prune network, the multilayer perceptron, and the radial basis function network.
The main challenge for its implementation was that data needed to be cleaned so the data mining process can easily retrieve these data and process them according to the required use. All abnormalities needed to be eliminated since the outcome would have been impacted by invalid or erroneous information.
The result of the business intelligence implementation was successful and the VHA could reach their goal of reducing the length of stay for each patient where necessary. Also a better productivity and a more efficient care program for their patients was a result of this implementation.
As this case has shown the use of new technologies in conjunction with new ways of analyzing, modifying, and implementing problems solutions, can significantly improve a more productive organization and reduces the costs associated with its operation to a more manageable level. Data mining in healthcare information systems is in its infant stages, yet we should be able to expect a more drastic change and more improvements in this field.
Kraft, M.R., Desouza, K.C., & Androwich, I. (2003). Case Study of a Veterans Administration Spinal Cord Injury Population. Retrieved April 24th, 2010, from Data Mining in Healthcare Information Systems: http://csdl2.computer.org/comp/proceedings/hicss/2003/1874/06/187460159a.pdf
Smalltree, H. (2006, July 20th). Business Analytics/Business Intelligence News. Retrieved April 23rd, 2010, from Business intelligence case study: Hospital BI helps healthcare: http://searchbusinessanalytics.techtarget.com/news/1507291/Business-intelligence-case-study-Hospital-BI-helps-healthcare.