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KMID : 1011320090020020078
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Journal of Pharmacoepidemiology and Risk Management
2009 Volume.2 No. 2 p.78 ~ p.88
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Data Quality Management in Pharmacovigilance
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Lee Jin-Ho
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Abstract
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Pharmacovigilance depends on informations gathered from the collection of individual case safety reports and other pharmacoepidemiological data. Spontaneous reports have many inherent limitations as data itself. The usefulness of this data source can be improved with good data quality management. Data quality management can also reduce the negative impact of incomplete reports, which is a serious problem in pharmacovigilance. Quality management consists of quality planning, quality control, quality assurance and quality improvements. The pharmacovigilance data processing cycle starts with data collection and data entry, usually in computerized systems; the next step is data storage and maintenance; followed by data selection, retrieval and manipulation. The resulting data output is analysed and assessed. Finally, conclusions are drawn and decisions made. The increased knowledge feeds back into the data processing cycle. Focussing on the first three steps of the data processing cycle, the different quality dimensions associated with these steps are described in this review, together with examples relevant to pharmacovigilance data. Functioning, well documented, and transparent quality management systems will benefit not only those involved in data collection, management and output production, but, ultimately, also the pharmacovigilance end users, the patients.
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KEYWORD
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Data quality, Quality management, Pharmacovigilance
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FullTexts / Linksout information
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Listed journal information
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