Cargando…
Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study
INTRODUCTION: The holistic management of hearing loss (HL) requires an understanding of factors that predict hearing aid (HA) use and benefit beyond the acoustics of listening environments. Although several predictors have been identified, no study has explored the role of audiological, cognitive, b...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829902/ https://www.ncbi.nlm.nih.gov/pubmed/29449298 http://dx.doi.org/10.1136/bmjopen-2017-020978 |
_version_ | 1783302909368205312 |
---|---|
author | Dritsakis, Giorgos Kikidis, Dimitris Koloutsou, Nina Murdin, Louisa Bibas, Athanasios Ploumidou, Katherine Laplante-Lévesque, Ariane Pontoppidan, Niels Henrik Bamiou, Doris-Eva |
author_facet | Dritsakis, Giorgos Kikidis, Dimitris Koloutsou, Nina Murdin, Louisa Bibas, Athanasios Ploumidou, Katherine Laplante-Lévesque, Ariane Pontoppidan, Niels Henrik Bamiou, Doris-Eva |
author_sort | Dritsakis, Giorgos |
collection | PubMed |
description | INTRODUCTION: The holistic management of hearing loss (HL) requires an understanding of factors that predict hearing aid (HA) use and benefit beyond the acoustics of listening environments. Although several predictors have been identified, no study has explored the role of audiological, cognitive, behavioural and physiological data nor has any study collected real-time HA data. This study will collect ‘big data’, including retrospective HA logging data, prospective clinical data and real-time data via smart HAs, a mobile application and biosensors. The main objective is to enable the validation of the EVOTION platform as a public health policy-making tool for HL. METHODS AND ANALYSIS: This will be a big data international multicentre study consisting of retrospective and prospective data collection. Existing data from approximately 35 000 HA users will be extracted from clinical repositories in the UK and Denmark. For the prospective data collection, 1260 HA candidates will be recruited across four clinics in the UK and Greece. Participants will complete a battery of audiological and other assessments (measures of patient-reported HA benefit, mood, cognition, quality of life). Patients will be offered smart HAs and a mobile phone application and a subset will also be given wearable biosensors, to enable the collection of dynamic real-life HA usage data. Big data analytics will be used to detect correlations between contextualised HA usage and effectiveness, and different factors and comorbidities affecting HL, with a view to informing public health decision-making. ETHICS AND DISSEMINATION: Ethical approval was received from the London South East Research Ethics Committee (17/LO/0789), the Hippokrateion Hospital Ethics Committee (1847) and the Athens Medical Center’s Ethics Committee (KM140670). Results will be disseminated through national and international events in Greece and the UK, scientific journals, newsletters, magazines and social media. Target audiences include HA users, clinicians, policy-makers and the general public. TRIAL REGISTRATION NUMBER: NCT03316287; Pre-results. |
format | Online Article Text |
id | pubmed-5829902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-58299022018-03-01 Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study Dritsakis, Giorgos Kikidis, Dimitris Koloutsou, Nina Murdin, Louisa Bibas, Athanasios Ploumidou, Katherine Laplante-Lévesque, Ariane Pontoppidan, Niels Henrik Bamiou, Doris-Eva BMJ Open Public Health INTRODUCTION: The holistic management of hearing loss (HL) requires an understanding of factors that predict hearing aid (HA) use and benefit beyond the acoustics of listening environments. Although several predictors have been identified, no study has explored the role of audiological, cognitive, behavioural and physiological data nor has any study collected real-time HA data. This study will collect ‘big data’, including retrospective HA logging data, prospective clinical data and real-time data via smart HAs, a mobile application and biosensors. The main objective is to enable the validation of the EVOTION platform as a public health policy-making tool for HL. METHODS AND ANALYSIS: This will be a big data international multicentre study consisting of retrospective and prospective data collection. Existing data from approximately 35 000 HA users will be extracted from clinical repositories in the UK and Denmark. For the prospective data collection, 1260 HA candidates will be recruited across four clinics in the UK and Greece. Participants will complete a battery of audiological and other assessments (measures of patient-reported HA benefit, mood, cognition, quality of life). Patients will be offered smart HAs and a mobile phone application and a subset will also be given wearable biosensors, to enable the collection of dynamic real-life HA usage data. Big data analytics will be used to detect correlations between contextualised HA usage and effectiveness, and different factors and comorbidities affecting HL, with a view to informing public health decision-making. ETHICS AND DISSEMINATION: Ethical approval was received from the London South East Research Ethics Committee (17/LO/0789), the Hippokrateion Hospital Ethics Committee (1847) and the Athens Medical Center’s Ethics Committee (KM140670). Results will be disseminated through national and international events in Greece and the UK, scientific journals, newsletters, magazines and social media. Target audiences include HA users, clinicians, policy-makers and the general public. TRIAL REGISTRATION NUMBER: NCT03316287; Pre-results. BMJ Publishing Group 2018-02-15 /pmc/articles/PMC5829902/ /pubmed/29449298 http://dx.doi.org/10.1136/bmjopen-2017-020978 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Public Health Dritsakis, Giorgos Kikidis, Dimitris Koloutsou, Nina Murdin, Louisa Bibas, Athanasios Ploumidou, Katherine Laplante-Lévesque, Ariane Pontoppidan, Niels Henrik Bamiou, Doris-Eva Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study |
title | Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study |
title_full | Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study |
title_fullStr | Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study |
title_full_unstemmed | Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study |
title_short | Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study |
title_sort | clinical validation of a public health policy-making platform for hearing loss (evotion): protocol for a big data study |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829902/ https://www.ncbi.nlm.nih.gov/pubmed/29449298 http://dx.doi.org/10.1136/bmjopen-2017-020978 |
work_keys_str_mv | AT dritsakisgiorgos clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT kikidisdimitris clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT koloutsounina clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT murdinlouisa clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT bibasathanasios clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT ploumidoukatherine clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT laplantelevesqueariane clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT pontoppidannielshenrik clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy AT bamioudoriseva clinicalvalidationofapublichealthpolicymakingplatformforhearinglossevotionprotocolforabigdatastudy |