Data mining and clinical data repositories: Insights from a 667,000 patient data set.
Publication/Presentation Date
12-1-2006
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.
Volume
36
Issue
12
First Page
1351
Last Page
1377
ISSN
0010-4825
Published In/Presented At
Mullins, I. M., Siadaty, M. S., Lyman, J., Scully, K., Garrett, C. T., Miller, W. G., Muller, R., Robson, B., Apte, C., Weiss, S., Rigoutsos, I., Platt, D., Cohen, S., & Knaus, W. A. (2006). Data mining and clinical data repositories: Insights from a 667,000 patient data set. Computers in biology and medicine, 36(12), 1351–1377. https://doi.org/10.1016/j.compbiomed.2005.08.003
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
16375883
Department(s)
Administration and Leadership
Document Type
Article