title: Mining administrative and clinical diabetes data with temporal association rules.
abstract: The Regional Healthcare Agency (ASL) of Pavia has been collecting and maintaining a central data repository which stores both administrative and clinical healthcare data about the population of Pavia area. The analysis of such integrated databases could greatly help to extract useful information for the assessment of health care delivery process. In this paper we focus our attention on the care delivery flow of Diabetes Mellitus, and we show the application of an algorithm for the extraction of Temporal Association Rules on sequences of hybrid events. This method allows to properly exploit the integration of different healthcare information sources, and can be used to evaluate the pertinence of the care delivery flow for specific pathologies, in order to reassess or refine the inappropriate practices which lead to unsatisfactory outcomes.
authors.affiliation: Dipartimento di Informatica e Sistemistica, Università di Pavia, 27100 Pavia, Italy. stefano.concaro@unipv.it
authors.forename: Stefano
authors.initials: S
authors.lastname: Concaro
authors.forename: Lucia
authors.initials: L
authors.lastname: Sacchi
authors.forename: Carlo
authors.initials: C
authors.lastname: Cerra
authors.forename: Riccardo
authors.initials: R
authors.lastname: Bellazzi
mesh_terms: D000465:Algorithms; D003695:Delivery of Health Care / Q000592:standards; D003920:Diabetes Mellitus / Q000503:physiopathology; D006801:Humans; D016247:Information Storage and Retrieval / Q000706:statistics & numerical data