Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/52483
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Type: Journal article
Title: Mining unexpected temporal associations: Applications in detecting adverse drug reactions
Author: Jin, H.
Chen, J.
He, H.
Williams, G.
Kelman, C.
O'Keefe, C.
Citation: IEEE Transactions on Information Technology in Biomedicine, 2008; 12(4):488-500
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Issue Date: 2008
ISSN: 1089-7771
1558-0032
Statement of
Responsibility: 
Huidong (Warren) Jin, Jie Chen, Member, Hongxing He, Graham J. Williams, Chris Kelman and Christine M. O’Keefe
Abstract: In various real-world applications, it is very useful mining unanticipated episodes where certain event patterns unexpectedly lead to outcomes, e.g., taking two medicines together sometimes causing an adverse reaction. These unanticipated episodes are usually unexpected and infrequent, which makes existing data mining techniques, mainly designed to find frequent patterns, ineffective. In this paper, we propose unexpected temporal association rules (UTARs) to describe them. To handle the unexpectedness, we introduce a new interestingness measure, residual-leverage, and develop a novel case-based exclusion technique for its calculation. Combining it with an event-oriented data preparation technique to handle the infrequency, we develop a new algorithm MUTARC to find pairwise UTARs. The MUTARC is applied to generate adverse drug reaction (ADR) signals from real-world healthcare administrative databases. It reliably shortlists not only six known ADRs, but also another ADR, flucloxacillin possibly causing hepatitis, which our algorithm designers and experiment runners have not known before the experiments. TheMUTARC performs much more effectively than existing techniques. This paper clearly illustrates the great potential along the new direction of ADR signal generation from healthcare administrative databases.
Keywords: Adverse drug reaction (ADR); data mining; healthcare administrative databases; pharmacovigilance; unanticipated episode; unexpected temporal association
Description: Copyright © 2008 IEEE
RMID: 0020081640
DOI: 10.1109/TITB.2007.900808
Appears in Collections:Mathematical Sciences publications

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