Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

© 2019 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). Vaccination against influenza is important in pregnancy for the health of both mother and unborn baby. Influenza introduces risks to pregnancy and to the baby who relies on maternal antibodies for protection. Because the data associated with pregnancy is fragmented across multiple providers of health care, it is challenging to conduct pregnancy-related public health surveillance using a single data source. We report the integration of a novel ontological approach to identifying pregnancies in routine data with a web-based dashboard that feeds back information to general practices in a sentinel network. As a result, practices receive information about how well they are performing influenza vaccination in pregnancy in near-real-time.

Original publication

DOI

10.3233/SHTI190682

Type

Journal article

Journal

Studies in Health Technology and Informatics

Publication Date

21/08/2019

Volume

264

Pages

1855 - 1856