Scientific article
Open access

Intelligent Telehealth in Pharmacovigilance: A Future Perspective

Published inDrug safety, vol. 45, no. 5, p. 449-458
Publication date2022-05-17
First online date2022-05-17

Pharmacovigilance improves patient safety by detecting and preventing adverse drug events. However, challenges exist that limit adverse drug event detection, resulting in many adverse drug events being underreported or inaccurately reported. One challenge includes having access to large data sets from various sources including electronic health records and wearable medical devices. Artificial intelligence, including machine learning methods, such as natural language processing and deep learning, can detect and extract information about adverse drug events, thus automating the pharmacovigilance process and improving the surveillance of known and documented adverse drug events. In addition, with the increased demand for telehealth services, for managing both acute and chronic diseases, artificial intelligence methods can play a role in detecting and preventing adverse drug events. In this review, we discuss two use cases of how artificial intelligence methods may be useful to improve the quality of pharmacovigilance and the role of artificial intelligence in telehealth practices.

  • Adverse Drug Reaction Reporting Systems
  • Artificial Intelligence
  • Drug-Related Side Effects and Adverse Reactions / epidemiology
  • Drug-Related Side Effects and Adverse Reactions / prevention & control
  • Humans
  • Natural Language Processing
  • Pharmacovigilance
  • Telemedicine
Affiliation Not a UNIGE publication
Citation (ISO format)
EDREES, Heba et al. Intelligent Telehealth in Pharmacovigilance: A Future Perspective. In: Drug safety, 2022, vol. 45, n° 5, p. 449–458. doi: 10.1007/s40264-022-01172-5
Main files (1)
Article (Published version)
ISSN of the journal0114-5916

Technical informations

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