Newe A (2016)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2016
Publisher: PeerJ, Inc.
Pages Range: e1851
Journal Issue: 4
DOI: 10.7717/peerj.1851
Open Access Link: http://dx.doi.org/10.7717/peerj.1851
According to the World Health Organization, one of the criteria for the standardized assessment of case causality in adverse drug reactions is the temporal relationship between the intake of a drug and the occurrence of a reaction or a laboratory test abnormality. This article presents and describes an algorithm for the detection of a reasonable temporal correlation between the administration of a drug and the alteration of a laboratory value course. The algorithm is designed to process normalized lab values and is therefore universally applicable. It has a sensitivity of 0.932 for the detection of lab value courses that show changes in temporal correlation with the administration of a drug and it has a specificity of 0.967 for the detection of lab value courses that show no changes. Therefore, the algorithm is appropriate to screen the data of electronic health records and to support human experts in revealing adverse drug reactions. A reference implementation in Python programming language is available.
APA:
Newe, A. (2016). Dramatyping: A generic algorithm for detecting reasonable temporal correlations between drug administration and lab value alterations. PeerJ, 4, e1851. https://dx.doi.org/10.7717/peerj.1851
MLA:
Newe, Axel. "Dramatyping: A generic algorithm for detecting reasonable temporal correlations between drug administration and lab value alterations." PeerJ 4 (2016): e1851.
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