Framework for characterizing data and identifying anomalies in health care databases.
As health care databases are becoming important sources of health care data, the anomalies these data may contain are of increasing concern. This paper proposes a framework that can be used to characterize data in health care databases through meta data, and which can be used to understand the element structures and processes that influence and generate these data and for identifying and discovering anomalies. Continued research in the refinement of the framework could serve as a predictive tool for identifying anomalies and potential anomalies in a variety of health care databases.
Savage
A M
AM
Division of Medical Informatics and Outcomes Research, Oregon Health Sciences University, Portland, USA.
D003627:Data Interpretation, Statistical; D016208:Databases, Factual; D003695:Delivery of Health Care / Q000706:statistics & numerical data*; D006302:Health Services Research; D006751:Hospital Information Systems; D006801:Humans; D016247:Information Storage and Retrieval