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A statistical signalling model for use in surveillance of adverse drug reaction data

 

作者: EricM. Hillson,   JaxkH. Reeves,   CharlotteA. Mcmillan,  

 

期刊: Journal of Applied Statistics  (Taylor Available online 1998)
卷期: Volume 25, issue 1  

页码: 23-40

 

ISSN:0266-4763

 

年代: 1998

 

DOI:10.1080/02664769823287

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

This paper presents a statistically superior lag-adjusted model for detecting increased frequency of reports of adverse drug event (ADE) rates. The effect of a significant lag time between ADE occurrence and report dates is studied. The approach in this paper to analyzing ADE data of this nature involves proposing a statistical model that utilizes a lag density function. The statistical method proposed was the development of an 'exact' procedure to monitor drugs that have a low incidence of ADEs. The approach determines statistically whether a change in the frequency of a specific ADE exists between two predetermined time intervals. There exist immense public health implications associated with the early detection of serious ADEs. The reduced risk of unfavorable outcomes associated with medication therapy is the goal of all involved. Simulated illustrations and discussion are provided, along with a detailed FORTRAN program used to implement the newly suggested lag-adjusted procedure.

 

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