Evidence map›Paper›PMID 28840504›Full record

ArticleDrug safety2018

From Big Data to Smart Data for Pharmacovigilance: The Role of Healthcare Databases and Other Emerging Sources.

Gianluca Trifirò, Janet Sultana, Andrew Bate

Abstract read
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In one paragraph

Article in Drug safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 5 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

41 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Review
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  14. Editorial: Traditional and innovative approaches for signal detection.Frontiers in drug safety and regulation · 2024
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  16. Review
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  18. Article
  19. Use of State Sequence Analysis in Pharmacoepidemiology: A Tutorial.International journal of environmental research and public health · 2021
    Article
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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

3 authors.

Gianluca TrifiròDepartment of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy. trifirog@unime.it.
Janet SultanaDepartment of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy.
Andrew BateEpidemiology Group Lead, Analytics, Worldwide Safety, Pfizer, Tadworth, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last decade 'big data' has become a buzzword used in several industrial sectors, including but not limited to telephony, finance and healthcare. Despite its popularity, it is not always clear what big data refers to exactly. Big data has become a very popular topic in healthcare, where the term primarily refers to the vast and growing volumes of computerized medical information available in the form of electronic health records, administrative or health claims data, disease and drug monitoring registries and so on. This kind of data is generally collected routinely during administrative processes and clinical practice by different healthcare professionals: from doctors recording their patients' medical history, drug prescriptions or medical claims to pharmacists registering dispensed prescriptions. For a long time, this data accumulated without its value being fully recognized and leveraged. Today big data has an important place in healthcare, including in pharmacovigilance. The expanding role of big data in pharmacovigilance includes signal detection, substantiation and validation of drug or vaccine safety signals, and increasingly new sources of information such as social media are also being considered. The aim of the present paper is to discuss the uses of big data for drug safety post-marketing assessment.

Indexed as

PharmacovigilanceAdverse Drug Reaction Reporting SystemsDatabases, FactualData MiningDelivery of Health CareDrug-Related Side Effects and Adverse ReactionsElectronic Health RecordsHumansSocial Media

Identifiers

PMID28840504

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.