title: Using data mining tools to discover novel clinical laboratory test batteries.
abstract: Using statistical analysis and data mining tools, we examined possible associations among clinical laboratory orders placed at the Ohio State University Medical Center between January and October of 2006. Upon applying the Frequent Itemset data mining technique to this data set, the results indicated that, while the most frequently ordered battery of tests was not associated with others, some highly associated orders may be good candidates to comprise new test batteries.
authors.affiliation: Information Warehouse, The Ohio State University Medical Center, Columbus, OH, USA.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Santangelo
authors.forename: Patrick
authors.initials: P
authors.lastname: Rogers
authors.forename: Jason
authors.initials: J
authors.lastname: Buskirk
authors.forename: Hagop S
authors.initials: HS
authors.lastname: Mekhjian
authors.forename: Jianhua
authors.initials: J
authors.lastname: Liu
authors.forename: Jyoti
authors.initials: J
authors.lastname: Kamal
mesh_terms: D000046:Academic Medical Centers; D002984:Clinical Laboratory Information Systems; D019411:Clinical Laboratory Techniques / Q000706:statistics & numerical data*; D005240:Feasibility Studies; D016247:Information Storage and Retrieval; D050316:Medical Order Entry Systems; D009820:Ohio; D013223:Statistics as Topic