Evidence map›Paper›PMID 25683723›Full record

ArticleBritish journal of clinical pharmacology2015

The role of electronic healthcare record databases in paediatric drug safety surveillance: a retrospective cohort study.

Sandra de Bie, Preciosa M Coloma, Carmen Ferrajolo, Katia M C Verhamme, Gianluca Trifirò, Martijn J Schuemie, Sabine M J M Straus, Rosa Gini, Ron Herings, Giampiero Mazzaglia and 7 more

Abstract read
In one paragraph

Article in British journal of clinical pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Sandra de BieDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Preciosa M ColomaDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Carmen FerrajoloDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Katia M C VerhammeDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Gianluca TrifiròDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Martijn J SchuemieDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Sabine M J M StrausDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Rosa GiniAgenzia Regionale di Sanità della Toscana, Florence, Italy.
Ron HeringsDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Giampiero MazzagliaSocietà Italiana di Medicina Generale, Florence, Italy.
Gino PicelliPedianet-Società Servizi Telematici SRL, Padova, Italy.
Arianna GhirardiDepartment of Statistics, Universita di Milano-Bicocca, Milan, Italy.
Lars PedersenDepartment of Clinical Epidemiology, Aarhus University Hospital Aarhus, Denmark.
Bruno H C StrickerDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Johan van der LeiDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Miriam C J M SturkenboomDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
EU-ADR consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimElectronic healthcare record (EHR)-based surveillance systems are increasingly being developed to support early detection of safety signals. It is unknown what the power of such a system is for surveillance among children and adolescents. In this paper we provide estimates of the number and classes of drugs, and incidence rates (IRs) of events, that can be monitored in children and adolescents (0-18 years).

methodsData were obtained from seven population-based EHR databases in Denmark, Italy, and the Netherlands during the period 1996-2010. We estimated the number of drugs for which specific adverse events can be monitored as a function of actual drug use, minimally detectable relative risk (RR) and IRs for 10 events.

resultsThe population comprised 4 838 146 individuals (25 575 132 person years (PYs)), who were prescribed 2170 drugs (1 610 631 PYs drug-exposure). Half of the total drug-exposure in PYs was covered by only 18 drugs (0.8%). For a relatively frequent event like upper gastrointestinal bleeding there were 39 drugs for which an association with a RR ≥4, if present, could be investigated. The corresponding number of drugs was eight for a rare event like anaphylactic shock.

conclusionDrug use in children is rare and shows little variation. The number of drugs with enough exposure to detect rare adverse events in children and adolescents within an EHR-based surveillance system such as EU-ADR is limited. Use of additional sources of paediatric drug exposure information and global collaboration are imperative in order to optimize EHR data for paediatric safety surveillance.

Indexed as

AdolescentAdverse Drug Reaction Reporting SystemsChildChild, PreschoolCohort StudiesDatabases, FactualDrug-Related Side Effects and Adverse ReactionsElectronic Health RecordsEuropean UnionHumansInfantPharmacovigilanceRetrospective Studiesactive drug safety surveillanceelectronic healthcare recordsEU-ADRpaediatric drug safetypharmacovigilancesafety monitoring

Identifiers

PMID25683723
PMCPMC4541978

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.