title: Data mining and clinical data repositories: Insights from a 667,000 patient data set.
abstract: Clinical repositories containing large amounts of biological, clinical, and administrative data are increasingly becoming available as health care systems integrate patient information for research and utilization objectives. To investigate the potential value of searching these databases for novel insights, we applied a new data mining approach, HealthMiner, to a large cohort of 667,000 inpatient and outpatient digital records from an academic medical system. HealthMiner approaches knowledge discovery using three unsupervised methods: CliniMiner, Predictive Analysis, and Pattern Discovery. The initial results from this study suggest that these approaches have the potential to expand research capabilities through identification of potentially novel clinical disease associations.
authors.affiliation: Department of Public Health Sciences, University of Virginia Health System, Charlottesville, VA, USA.
authors.forename: Irene M
authors.initials: IM
authors.lastname: Mullins
authors.forename: Mir S
authors.initials: MS
authors.lastname: Siadaty
authors.forename: Jason
authors.initials: J
authors.lastname: Lyman
authors.forename: Ken
authors.initials: K
authors.lastname: Scully
authors.forename: Carleton T
authors.initials: CT
authors.lastname: Garrett
authors.forename: W Greg
authors.initials: WG
authors.lastname: Miller
authors.forename: Rudy
authors.initials: R
authors.lastname: Muller
authors.forename: Barry
authors.initials: B
authors.lastname: Robson
authors.forename: Chid
authors.initials: C
authors.lastname: Apte
authors.forename: Sholom
authors.initials: S
authors.lastname: Weiss
authors.forename: Isidore
authors.initials: I
authors.lastname: Rigoutsos
authors.forename: Daniel
authors.initials: D
authors.lastname: Platt
authors.forename: Simona
authors.initials: S
authors.lastname: Cohen
authors.forename: William A
authors.initials: WA
authors.lastname: Knaus
mesh_terms: D019963:Clinical Chemistry Tests; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D006801:Humans; D008492:Medical Informatics Computing; D016347:Medical Records Systems, Computerized; D011237:Predictive Value of Tests