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Information systems for vaccine safety surveillance
Immunization implementation in the community relies upon post-licensure vaccine safety surveillance to maintain safe vaccination programs and to detect rare AEFI not observed in clinical trials. The increasing availability of electronic health-care related data and correspondence from both health-re...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9746439/ https://www.ncbi.nlm.nih.gov/pubmed/36162040 http://dx.doi.org/10.1080/21645515.2022.2100173 |
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author | Buttery, Jim P Clothier, Hazel |
author_facet | Buttery, Jim P Clothier, Hazel |
author_sort | Buttery, Jim P |
collection | PubMed |
description | Immunization implementation in the community relies upon post-licensure vaccine safety surveillance to maintain safe vaccination programs and to detect rare AEFI not observed in clinical trials. The increasing availability of electronic health-care related data and correspondence from both health-related providers and internet-based media has revolutionized health-care information. Many and varied forms of health information related to adverse event following immunization (AEFI) are potentially suitable for vaccine safety surveillance. The utilization of these media ranges from more efficient use of electronic spontaneous reporting, automated solicited surveillance methods, screening various electronic health record types, and the utilization of natural language processing techniques to scan enormous amounts of internet-based data for AEFI mentions. Each of these surveillance types have advantages and disadvantages and are often complementary to each other. Most are “hypothesis generating,” detecting potential safety signals, where some, such as vaccine safety datalinking, may also serve as “hypothesis testing” to help verify and investigate those potential signals. |
format | Online Article Text |
id | pubmed-9746439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-97464392022-12-14 Information systems for vaccine safety surveillance Buttery, Jim P Clothier, Hazel Hum Vaccin Immunother Logistics SF – Review Immunization implementation in the community relies upon post-licensure vaccine safety surveillance to maintain safe vaccination programs and to detect rare AEFI not observed in clinical trials. The increasing availability of electronic health-care related data and correspondence from both health-related providers and internet-based media has revolutionized health-care information. Many and varied forms of health information related to adverse event following immunization (AEFI) are potentially suitable for vaccine safety surveillance. The utilization of these media ranges from more efficient use of electronic spontaneous reporting, automated solicited surveillance methods, screening various electronic health record types, and the utilization of natural language processing techniques to scan enormous amounts of internet-based data for AEFI mentions. Each of these surveillance types have advantages and disadvantages and are often complementary to each other. Most are “hypothesis generating,” detecting potential safety signals, where some, such as vaccine safety datalinking, may also serve as “hypothesis testing” to help verify and investigate those potential signals. Taylor & Francis 2022-09-26 /pmc/articles/PMC9746439/ /pubmed/36162040 http://dx.doi.org/10.1080/21645515.2022.2100173 Text en © 2022 The Author(s). Published with license by Taylor & Francis Group, LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
spellingShingle | Logistics SF – Review Buttery, Jim P Clothier, Hazel Information systems for vaccine safety surveillance |
title | Information systems for vaccine safety surveillance |
title_full | Information systems for vaccine safety surveillance |
title_fullStr | Information systems for vaccine safety surveillance |
title_full_unstemmed | Information systems for vaccine safety surveillance |
title_short | Information systems for vaccine safety surveillance |
title_sort | information systems for vaccine safety surveillance |
topic | Logistics SF – Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9746439/ https://www.ncbi.nlm.nih.gov/pubmed/36162040 http://dx.doi.org/10.1080/21645515.2022.2100173 |
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