Application of data mining techniques to healthcare data.
A high-level introduction to data mining as it relates to surveillance of healthcare data is presented. Data mining is compared with traditional statistics, some advantages of automated data systems are identified, and some data mining strategies and algorithms are described. A concrete example illustrates steps involved in the data mining process, and three successful data mining applications in the healthcare arena are described.
Obenshain
Mary K
MK
Data Quality Research Institute, UNC at Chapel Hill, CB#7226, 200 Timberhill Place, Suite 201, Chapel Hill, NC 27599-7226, USA.
D016208:Databases, Factual; D003695:Delivery of Health Care / Q000706:statistics & numerical data*; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D017053:Infection Control / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D011159:Population Surveillance / Q000379:methods; D012984:Software