Application of Electronic Health Records in Pharmacovigilance
A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Medication Management".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 834
Special Issue Editor
2. Laboratoire de Biométrie et Biologie Humaine, Équipe Évaluation et Modélisation des Effets Thérapeutiques, rue Guillaume-Paradin, BP8071, CEDEX 08, 69376 Lyon, France
Interests: application AI and automatic trigger tool in pharmacovigilance
Special Issue Information
Dear Colleagues,
Medicines and vaccines have transformed the prevention and treatment of diseases. In addition to their benefits, medicinal products may also have side effects, some of which may be undesirable and / or unexpected. Pharmacovigilance (PV) is the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine/vaccine related problem (WHO). Electronic health records (EHRs) has played an important role in pharmacovigilance. Nowadays, EHRs become a principal data source using in daily PV. Furthermore, artificial intelligence (AI) recently has emerged as a useful tool in pharmacovigilance. AI could help in early detection and prevention of moderate and serious adverse drug reactions. However, there are a number of challenges that need to be addressed before AI can be fully adopted in this field. One of the challenge is how to use routine electronic health records with AI application in promoting pro-active monitoring of ADRs in clinical practice. This special issue aim to address the use of EHRs in PV.
We are pleased to invite you to contribute your research works related to innovated tools using EHRs in pharmacovigilance.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:
- Using EHRs in pharmacovigilance
- Implementation of automatic or semiautomatic trigger tool to detect ADRs using EHRs
- AI application in pharmacovigilance
- Active monitoring of adverse drug reactions using EHRs
Using trigger words in unstructured, narrative text to detect adverse drug reactions (ADRs).
I look forward to receiving your contributions.
Dr. Kim An Nguyen
Guest Editor
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- pharmacovigilance
- drug-related side effects
- adverse drug reactions
- reporting systems
- medical records systems
- electronic health records
- deep learning
- machine learning
- data mining
- artificial intelligence.
