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Extraction of Medical Pathways from Electronic Patient Records
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Author(s): Dario Antonelli (Politecnico di Torino, Italy), Elena Baralis (Politecnico di Torino, Italy), Giulia Bruno (Politecnico di Torino, Italy), Silvia Chiusano (Politecnico di Torino, Italy), Naeem A. Mahoto (Politecnico di Torino, Italy)and Caterina Petrigni (Politecnico di Torino, Italy)
Copyright: 2013
Pages: 15
Source title:
Data Mining: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-2455-9.ch051
PurchaseView on the publisher's website for pricing and purchasing information.
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Abstract
With the introduction of electronic medical records, a large amount of patients’ medical data has been available. An actual problem in this domain is to perform reverse engineering of the medical treatment process to highlight medical pathways typically adopted for specific health conditions. This chapter addresses the ability of sequential data mining techniques to reconstruct the actual medical pathways followed by patients. Detected medical pathways are in the form of sets of exams frequently done together, sequences of exam sets frequently followed by patients and frequent correlations between exam sets. The analysis shows that the majority of the extracted pathways are consistent with the medical guidelines, but also reveals some unexpected results, which can be useful both to enrich existing guidelines and to improve the public sanitary service.
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