Mining big data to support decision making in healthcare. Issue 3 (7th September 2016) - Swain, Ajaya K.
Abstract: This study demonstrates an application of data mining in the analysis of big healthcare data. Considering the significant impact of obesity on the ever-rising healthcare costs in the United States, this study identifies key demographic and lifestyle characteristics associated with adult obesity. The sample for this study was drawn from the Behavioral Risk Factor Surveillance System data base of the Centers for Disease Control and Prevention. Using SAS Enterprise Miner, two predictive models are built to create a profile of an adult population group who are at risk of being obese. The models provide support for early intervention strategies and policymaking decisions for healthcare administrators and professionals.