The University of Southampton
University of Southampton Institutional Repository

Leveraging real world data to improve cochlear implant outcomes: is the data available?

Leveraging real world data to improve cochlear implant outcomes: is the data available?
Leveraging real world data to improve cochlear implant outcomes: is the data available?

Objectives: a small but persistent proportion of individuals do not gain the expected benefit from cochlear implants(CI). A step-change in the understanding of factors affecting outcomes could come through data science. This study evaluates clinical data capture to assess the quality and utility of CI user's health records for data science, by assessing the recording of otitis media. Otitis media was selected as it is associated with the development of sensorineural hearing loss and may affect cochlear implant outcomes. 

Methods: a retrospective service improvement project evaluating the medical records of 594 people with a CI under the care of the University of Southampton Auditory Implant Service between 2014 and 2020. Results: The clinical records are suitable for data science research. Of the cohort studied 20% of Adults and more than 40% of the paediatric cases have a history of middle ear inflammation. 

Discussion: data science has potential to improve cochlear implant outcomes and improve understanding of the mechanisms underlying poor performance, through retrospective secondary analysis of real-world data. 

Conclusion: implant centres and the British Cochlear Implant Group National Hearing Implant Registry are urged to consider the importance of consistently and accurate recording of patient data over time for each CI user. Data where links to hearing loss have been identified, such as middle ear inflammation, may be particularly valuable in future analyses and to inform clinical trials.

Cochlear Implant, Data Science, Health Informatics, Otitis Media, Prognostic Factors, Real-world Data
1467-0100
178-189
Findlay, Callum
16e75504-207b-425c-8728-aead3a419bb9
Edwards, Matthew
ffdd47a6-e4ed-4d1c-9d4b-7f5eea5b796d
Hough, Kate
81d8630c-6e02-4bea-858a-377717476f6e
Grasmeder, Mary
206e6b44-d1cd-43f5-99ac-588ab02d44ef
Newman, Tracey
322290cb-2e9c-445d-a047-00b1bea39a25
Findlay, Callum
16e75504-207b-425c-8728-aead3a419bb9
Edwards, Matthew
ffdd47a6-e4ed-4d1c-9d4b-7f5eea5b796d
Hough, Kate
81d8630c-6e02-4bea-858a-377717476f6e
Grasmeder, Mary
206e6b44-d1cd-43f5-99ac-588ab02d44ef
Newman, Tracey
322290cb-2e9c-445d-a047-00b1bea39a25

Findlay, Callum, Edwards, Matthew, Hough, Kate, Grasmeder, Mary and Newman, Tracey (2023) Leveraging real world data to improve cochlear implant outcomes: is the data available? Cochlear Implants International, 24 (4), 178-189. (doi:10.1080/14670100.2023.2198792).

Record type: Article

Abstract

Objectives: a small but persistent proportion of individuals do not gain the expected benefit from cochlear implants(CI). A step-change in the understanding of factors affecting outcomes could come through data science. This study evaluates clinical data capture to assess the quality and utility of CI user's health records for data science, by assessing the recording of otitis media. Otitis media was selected as it is associated with the development of sensorineural hearing loss and may affect cochlear implant outcomes. 

Methods: a retrospective service improvement project evaluating the medical records of 594 people with a CI under the care of the University of Southampton Auditory Implant Service between 2014 and 2020. Results: The clinical records are suitable for data science research. Of the cohort studied 20% of Adults and more than 40% of the paediatric cases have a history of middle ear inflammation. 

Discussion: data science has potential to improve cochlear implant outcomes and improve understanding of the mechanisms underlying poor performance, through retrospective secondary analysis of real-world data. 

Conclusion: implant centres and the British Cochlear Implant Group National Hearing Implant Registry are urged to consider the importance of consistently and accurate recording of patient data over time for each CI user. Data where links to hearing loss have been identified, such as middle ear inflammation, may be particularly valuable in future analyses and to inform clinical trials.

Text
Leveraging real world data to improve cochlear implant outcomes Is the data available - Version of Record
Available under License Creative Commons Attribution.
Download (2MB)

More information

e-pub ahead of print date: 23 April 2023
Published date: 23 April 2023
Additional Information: Funding Information: Funding Callum Findlay, Academic Clinical Fellow, is funded by a National Institute of Health Research (NIHR) Academic Clinical fellowship with the University of Southampton alongside Health Education England. The views expressed in this publication are those of the authors and not necessarily those of the NIHR, University of Southampton, NHS or the UK Department of Health and Social Care. Kate Hough – EPSRC for PhD studentship funding and additional support from Oticon Medical. Supported by funding to Tracey Newman, from the Web Stimulus Fund, University of Southampton. Publisher Copyright: © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Keywords: Cochlear Implant, Data Science, Health Informatics, Otitis Media, Prognostic Factors, Real-world Data

Identifiers

Local EPrints ID: 476966
URI: http://eprints.soton.ac.uk/id/eprint/476966
ISSN: 1467-0100
PURE UUID: 2ff70ed6-20a0-4dd0-ad12-ed1c093e99ae
ORCID for Kate Hough: ORCID iD orcid.org/0000-0002-5160-2517
ORCID for Tracey Newman: ORCID iD orcid.org/0000-0002-3727-9258

Catalogue record

Date deposited: 22 May 2023 17:03
Last modified: 10 Apr 2024 02:08

Export record

Altmetrics

Contributors

Author: Callum Findlay
Author: Matthew Edwards
Author: Kate Hough ORCID iD
Author: Mary Grasmeder
Author: Tracey Newman ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×