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A High Performance Agent-Based System for Reporting Suspected Adverse Drug Reactions

Authors: Yanqing Ji; Fangyang Shen; John Tran;

A High Performance Agent-Based System for Reporting Suspected Adverse Drug Reactions

Abstract

Adverse drug reactions (ADRs) represent a serious worldwide problem. Current post-marketing ADR detection approaches largely rely on spontaneous reports filed by various healthcare professionals such as physicians, pharmacists et.al.. Underreporting is a serious deficiency of these methods - the actually reported adverse events represent less than 10% of all cases. Studies show that two important reasons that cause the underreporting are: 1) healthcare professionals are unaware of encountered ADRs, especially for those unusual ADRs, 2) they are too busy to voluntarily report ADRs since it takes a lot of time to fill out the reporting forms. This paper addresses these two issues by developing a high performance agent-based ADR reporting system. The system can 1) help healthcare professionals detect the causal relationship between a drug and an ADR by analyzing patients' electronic records, 2) make the reporting much easier by automatically linking the patients' electronic data with the reporting form.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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