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. 2015 Oct;80(4):844-54.
doi: 10.1111/bcp.12645. Epub 2015 May 28.

Pharmacovigilance in children: detecting adverse drug reactions in routine electronic healthcare records. A systematic review

Corri Black  1 , Nara Tagiyeva-Milne  1 , Peter Helms  1 , Dorothy Moir  1
Affiliations

Pharmacovigilance in children: detecting adverse drug reactions in routine electronic healthcare records. A systematic review

Corri Black et al. Br J Clin Pharmacol. 2015 Oct.

Abstract

Aims: A systematic review of the literature published in English over 10 years was undertaken in order to describe the use of electronic healthcare data in the identification of potential adverse drug reactions (ADRs) in children.

Methods: MEDLINE and EMBASE were searched using MESH headings and text words. Titles, keywords and abstracts were checked for age <18 years, potential ADRs and electronic healthcare data. Information extracted included age, data source, pharmacovigilance method, medicines and ADRs. Studies were quality assessed.

Results: From 14 804 titles, 314 had a full text review and 71 were included in the final review. Fifty were published in North America, 10 in Scandinavia. Study size ranged from less than 1000 children to more than 10 million. Sixty per cent of studies used data from one source. Comparative observational studies were most commonly reported (66.2%) with 15% using passive surveillance. Electronic healthcare data set linkage and the quality of the data source were poorly reported. ADRs were classified using the International Classification of Disease (ICD10). Multi-system reactions were most commonly studied, followed by central nervous system and mental and behavioural disorders. Vaccines were most frequently prescribed followed by corticosteroids, general anaesthetics and antidepressants.

Conclusions: Routine electronic healthcare records were increasingly reported to be used for pharmacovigilance in children. This growing and important health protection activity could be enhanced by consistent reporting of studies to improve the identification, interpretation and generalizability of the evidence base.

Keywords: adverse drug reactions; children; electronic healthcare data; systematic review.

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Figures

Figure 1
Figure 1
PRISMA flow diagram summarizing study selection process
Figure 2
Figure 2
Size of the 68 data sources reported by population covered or the number of events reported per year/within the study period. M, Millions *two data sources did not report size. formula image, Population; formula image, Records/Reports
Figure 3
Figure 3
Summary of the quality assessment. formula image, Not applicable; formula image, Not reported; formula image, Did not meet criteria; formula image, Partially met criteria; formula image, Met criteria
Figure 4
Figure 4
Therapeutic groups of medicines studied for potential ADRs in routine electronic healthcare data
See this image and copyright information in PMC

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