From Data Silos to Standardized, Linked, and FAIR Data for Pharmacovigilance: Current Advances and Challenges with Observational Healthcare Data

Pharmacovigilance (PV) encompasses all data gathering and processing activities related to the detection, assessment, understanding, and prevention of adverse effects throughout the entire life cycle of drugs. The current era of data explosion or big data affects the entire spectrum of health scienc...

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Bibliographic Details
Published in:Drug safety 2019-05, Vol.42 (5), p.583-586
Main Author: Koutkias, Vassilis
Format: Article
Language:English
Subjects:
Applications programs
Clinical outcomes
Clinical trials
Commentary
Data models
Dictionaries
Digital media
Drug Safety and Pharmacovigilance
Electronic health records
Electronic medical records
Gene mapping
Genotype & phenotype
Health care
Informatics
Interoperability
Laboratories
Laboratory tests
Life cycle assessment
Life cycles
Mapping
Medical research
Medicine
Medicine & Public Health
Pharmacology
Pharmacology/Toxicology
Pharmacovigilance
Product safety
Semantic web
Semantics
Standardization
Studies
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Summary:Pharmacovigilance (PV) encompasses all data gathering and processing activities related to the detection, assessment, understanding, and prevention of adverse effects throughout the entire life cycle of drugs. The current era of data explosion or big data affects the entire spectrum of health sciences, including PV. In particular, the data employed for PV have been recently extended, considering not only traditional/dominant data sources, i.e. spontaneous reporting systems, clinical trials, and the scientific literature, but also observational healthcare databases (i.e. electronic health records [EHR] and administrative claims) with potential linkage to genetic data, as well as social media platforms and mobile health (mHealth) apps. In the scope of multi-center EHR-based PV studies, various data elements such as diagnoses, medical procedures, medications, and laboratory tests shall be expressed uniformly by selecting and combining codes from diverse vocabularies as well as proprietary coding schemes. Using reference terminologies for this mapping process facilitates standardization and semantic interoperability.
ISSN:0114-5916
1179-1942
DOI:10.1007/s40264-018-00793-z